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Kanefendt F, Dallmann A, Chen H, Francke K, Liu T, Brase C, Frechen S, Schultze-Mosgau MH. Assessment of the CYP3A4 Induction Potential by Carbamazepine: Insights from Two Clinical DDI Studies and PBPK Modeling. Clin Pharmacol Ther 2024; 115:1025-1032. [PMID: 38105467 DOI: 10.1002/cpt.3151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 11/15/2023] [Indexed: 12/19/2023]
Abstract
In the past, rifampicin was well-established as strong index CYP3A inducer in clinical drug-drug interaction (DDI) studies. However, due to identified potentially genotoxic nitrosamine impurities, it should not any longer be used in healthy volunteer studies. Available clinical data suggest carbamazepine as an alternative to rifampicin as strong index CYP3A4 inducer in clinical DDI studies. Further, physiologically-based pharmacokinetic (PBPK) modeling is a tool with increasing importance to support the DDI risk assessment of drugs during drug development. CYP3A4 induction properties and the safety profile of carbamazepine were investigated in two open-label, fixed sequence, crossover clinical pharmacology studies in healthy volunteers using midazolam as a sensitive index CYP3A4 substrate. Carbamazepine was up-titrated from 100 mg twice daily (b.i.d.) to 200 mg b.i.d., and to a final dose of 300 mg b.i.d. for 10 consecutive days. Mean area under plasma concentration-time curve from zero to infinity (AUC(0-∞)) of midazolam consistently decreased by 71.8% (ratio: 0.282, 90% confidence interval (CI): 0.235-0.340) and 67.7% (ratio: 0.323, 90% CI: 0.256-0.407) in study 1 and study 2, respectively. The effect was adequately described by an internally developed PBPK model for carbamazepine which has been made freely available to the scientific community. Further, carbamazepine was safe and well-tolerated in the investigated dosing regimen in healthy participants. The results demonstrated that the presented design is appropriate for the use of carbamazepine as alternative inducer to rifampicin in DDI studies acknowledging its CYP3A4 inductive potency and safety profile.
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Affiliation(s)
| | - André Dallmann
- Bayer HealthCare SAS, Loos, France, on behalf of Bayer AG, Pharmacometrics/Modeling and Simulation, Systems Pharmacology & Medicine - PBPK, Germany
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Reig-López J, Cuquerella-Gilabert M, Bandín-Vilar E, Merino-Sanjuán M, Mangas-Sanjuán V, García-Arieta A. Bioequivalence risk assessment of oral formulations containing racemic ibuprofen through a chiral physiologically based pharmacokinetic model of ibuprofen enantiomers. Eur J Pharm Biopharm 2024:114293. [PMID: 38641229 DOI: 10.1016/j.ejpb.2024.114293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 03/26/2024] [Accepted: 04/15/2024] [Indexed: 04/21/2024]
Abstract
The characterization of the time course of ibuprofen enantiomers can be useful in the selection of the most sensitive analyte in bioequivalence studies. Physiologically based pharmacokinetic (PBPK) modelling and simulation represents the most efficient methodology to virtually assess bioequivalence outcomes. In this work, we aim to develop and verify a PBPK model for ibuprofen enantiomers administered as a racemic mixture with different immediate release dosage forms to anticipate bioequivalence outcomes based on different particle size distributions. A PBPK model incorporating stereoselectivity and non-linearity in plasma protein binding and metabolism as well as R-to-S unidirectional inversion has been developed in Simcyp®. A dataset composed of 11 Phase I clinical trials with 54 scenarios (27 per enantiomer) and 14,452 observations (7129 for R-ibuprofen and 7323 for S-ibuprofen) was used. Prediction errors for AUC0-t and Cmax for both enantiomers fell within the 0.8-1.25 range in 50/54 (93 %) and 42/54 (78 %) of scenarios, respectively. Outstanding model performance, with 10/10 (100 %) of Cmax and 9/10 (90 %) of AUC0-t within the 0.9-1.1 range, was demonstrated for oral suspensions, which strongly supported its use for bioequivalence risk assessment. The deterministic bioequivalence risk assessment has revealed R-ibuprofen as the most sensitive analyte to detect differences in particle size distribution for oral suspensions containing 400 mg of racemic ibuprofen, suggesting that achiral bioanalytical methods would increase type II error and declare non-bioequivalence for formulations that are bioequivalent for the eutomer.
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Affiliation(s)
- Javier Reig-López
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, University of Valencia-Polytechnic University of Valencia, Spain
| | - Marina Cuquerella-Gilabert
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, University of Valencia-Polytechnic University of Valencia, Spain; Simulation Department, Empresarios Agrupados Internacional S.A., Madrid, Spain
| | - Enrique Bandín-Vilar
- Pharmacy Department, University Clinical Hospital Santiago de Compostela (CHUS), Spain; Clinical Pharmacology Group, Health Research Institute of Santiago de Compostela (IDIS), Spain; Pharmacology, Pharmacy and Pharmaceutical Technology Department, Faculty of Pharmacy, University of Santiago de Compostela (USC), Spain
| | - Matilde Merino-Sanjuán
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, University of Valencia-Polytechnic University of Valencia, Spain
| | - Víctor Mangas-Sanjuán
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, University of Valencia-Polytechnic University of Valencia, Spain.
| | - Alfredo García-Arieta
- Área de Farmacocinética y Medicamentos Genéricos, División de Farmacología y Evaluación Clínica, Departamento de Medicamentos de Uso Humano, Agencia Española de Medicamentos y Productos Sanitarios, Spain
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Alsmadi MM, Abudaqqa AA, Idkaidek N, Qinna NA, Al-Ghazawi A. The Effect of Inflammatory Bowel Disease and Irritable Bowel Syndrome on Pravastatin Oral Bioavailability: In vivo and in silico evaluation using bottom-up wbPBPK modeling. AAPS PharmSciTech 2024; 25:86. [PMID: 38605192 DOI: 10.1208/s12249-024-02803-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 04/01/2024] [Indexed: 04/13/2024] Open
Abstract
The common disorders irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD) can modify the drugs' pharmacokinetics via their induced pathophysiological changes. This work aimed to investigate the impact of these two diseases on pravastatin oral bioavailability. Rat models for IBS and IBD were used to experimentally test the effects of IBS and IBD on pravastatin pharmacokinetics. Then, the observations made in rats were extrapolated to humans using a mechanistic whole-body physiologically-based pharmacokinetic (wbPBPK) model. The rat in vivo studies done herein showed that IBS and IBD decreased serum albumin (> 11% for both), decreased PRV binding in plasma, and increased pravastatin absolute oral bioavailability (0.17 and 0.53 compared to 0.01) which increased plasma, muscle, and liver exposure. However, the wbPBPK model predicted muscle concentration was much lower than the pravastatin toxicity thresholds for myotoxicity and rhabdomyolysis. Overall, IBS and IBD can significantly increase pravastatin oral bioavailability which can be due to a combination of increased pravastatin intestinal permeability and decreased pravastatin gastric degradation resulting in higher exposure. This is the first study in the literature investigating the effects of IBS and IBD on pravastatin pharmacokinetics. The high interpatient variability in pravastatin concentrations as induced by IBD and IBS can be reduced by oral administration of pravastatin using enteric-coated tablets. Such disease (IBS and IBD)-drug interaction can have more drastic consequences for narrow therapeutic index drugs prone to gastric degradation, especially for drugs with low intestinal permeability.
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Affiliation(s)
- Motasem M Alsmadi
- Department of Pharmaceutical Technology, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan.
- Nanotechnology Institute, Jordan University of Science and Technology, Irbid, Jordan.
| | - Alla A Abudaqqa
- Faculty of Pharmacy and Biomedical Sciences, University of Petra, Amman, Jordan
| | - Nasir Idkaidek
- Faculty of Pharmacy and Biomedical Sciences, University of Petra, Amman, Jordan
| | - Nidal A Qinna
- Faculty of Pharmacy and Biomedical Sciences, University of Petra, Amman, Jordan
- University of Petra Pharmaceutical Center (UPPC), University of Petra, Amman, Jordan
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Moreau M, Simms L, Andersen ME, Trelles Sticken E, Wieczorek R, Pour SJ, Chapman F, Roewer K, Otte S, Fisher J, Stevenson M. Use of quantitative in vitro to in vivo extrapolation (QIVIVE) for the assessment of non-combustible next-generation product aerosols. Front Toxicol 2024; 6:1373325. [PMID: 38665213 PMCID: PMC11043521 DOI: 10.3389/ftox.2024.1373325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 03/28/2024] [Indexed: 04/28/2024] Open
Abstract
With the use of in vitro new approach methodologies (NAMs) for the assessment of non-combustible next-generation nicotine delivery products, new extrapolation methods will also be required to interpret and contextualize the physiological relevance of these results. Quantitative in vitro to in vivo extrapolation (QIVIVE) can translate in vitro concentrations into in-life exposures with physiologically-based pharmacokinetic (PBPK) modelling and provide estimates of the likelihood of harmful effects from expected exposures. A major challenge for evaluating inhalation toxicology is an accurate assessment of the delivered dose to the surface of the cells and the internalized dose. To estimate this, we ran the multiple-path particle dosimetry (MPPD) model to characterize particle deposition in the respiratory tract and developed a PBPK model for nicotine that was validated with human clinical trial data for cigarettes. Finally, we estimated a Human Equivalent Concentration (HEC) and predicted plasma concentrations based on the minimum effective concentration (MEC) derived after acute exposure of BEAS-2B cells to cigarette smoke (1R6F), or heated tobacco product (HTP) aerosol at the air liquid interface (ALI). The MPPD-PBPK model predicted the in vivo data from clinical studies within a factor of two, indicating good agreement as noted by WHO International Programme on Chemical Safety (2010) guidance. We then used QIVIVE to derive the exposure concentration (HEC) that matched the estimated in vitro deposition point of departure (POD) (MEC cigarette = 0.38 puffs or 11.6 µg nicotine, HTP = 22.9 puffs or 125.6 µg nicotine) and subsequently derived the equivalent human plasma concentrations. Results indicate that for the 1R6F cigarette, inhaling 1/6th of a stick would be required to induce the same effects observed in vitro, in vivo. Whereas, for HTP it would be necessary to consume 3 sticks simultaneously to induce in vivo the effects observed in vitro. This data further demonstrates the reduced physiological potency potential of HTP aerosol compared to cigarette smoke. The QIVIVE approach demonstrates great promise in assisting human health risk assessments, however, further optimization and standardization are required for the substantiation of a meaningful contribution to tobacco harm reduction by alternative nicotine delivery products.
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Affiliation(s)
| | - Liam Simms
- Imperial Brands PLC, Bristol, United Kingdom
| | | | | | - Roman Wieczorek
- Reemtsma Cigarettenfabriken GmbH, An Imperial Brands PLC Company, Hamburg, Germany
| | - Sarah Jean Pour
- Reemtsma Cigarettenfabriken GmbH, An Imperial Brands PLC Company, Hamburg, Germany
| | | | - Karin Roewer
- Reemtsma Cigarettenfabriken GmbH, An Imperial Brands PLC Company, Hamburg, Germany
| | - Sandra Otte
- Reemtsma Cigarettenfabriken GmbH, An Imperial Brands PLC Company, Hamburg, Germany
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Wang X, Wu J, Ye H, Zhao X, Zhu S. Research Landscape of Physiologically Based Pharmacokinetic Model Utilization in Different Fields: A Bibliometric Analysis (1999-2023). Pharm Res 2024; 41:609-622. [PMID: 38383936 DOI: 10.1007/s11095-024-03676-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 02/05/2024] [Indexed: 02/23/2024]
Abstract
PURPOSE The physiologically based pharmacokinetic (PBPK) modeling has received increasing attention owing to its excellent predictive abilities. However, there has been no bibliometric analysis about PBPK modeling. This research aimed to summarize the research development and hot points in PBPK model utilization overall through bibliometric analysis. METHODS We searched for publications related to the PBPK modeling from 1999 to 2023 in the Web of Science Core Collection (WoSCC) database. The Microsoft Office Excel, CiteSpace and VOSviewers were used to perform the analyses. RESULTS A total of 4,649 records from 1999 to 2023 were identified, and the largest number of publications focused in the period 2018-2023. The United States was the leading country, and the Environmental Protection Agency (EPA) was the leading institution. The journal Drug Metabolism and Disposition published and co-cited the most articles. Drug-drug interactions, special populations, and new drug development are the main topics in this research field. CONCLUSION We first visualize the research landscape and hotspots of the PBPK modeling through bibliometric methods. Our study provides a better understanding for researchers, especially beginners about the dynamization of PBPK modeling and presents the relevant trend in the future.
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Affiliation(s)
- Xin Wang
- Department of Pharmacy, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Jiangfan Wu
- School of Pharmacy, Chongqing Medical University, Chongqing, China
| | - Hongjiang Ye
- Department of Neurosurgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Xiaofang Zhao
- School of Pharmacy, Chongqing Medical University, Chongqing, China
- Qiandongnan Miao and Dong Autonomous Prefecture People's Hospital, Guizhou, 556000, China
| | - Shenyin Zhu
- Department of Pharmacy, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuzhong District, Chongqing, 400016, China.
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Hunt JP, Dubinsky S, McKnite AM, Cheung KWK, van Groen BD, Giacomini KM, de Wildt SN, Edginton AN, Watt KM. Maximum likelihood estimation of renal transporter ontogeny profiles for pediatric PBPK modeling. CPT Pharmacometrics Syst Pharmacol 2024; 13:576-588. [PMID: 38156758 PMCID: PMC11015082 DOI: 10.1002/psp4.13102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 12/01/2023] [Accepted: 12/14/2023] [Indexed: 01/03/2024] Open
Abstract
Optimal treatment of infants with many renally cleared drugs must account for maturational differences in renal transporter (RT) activity. Pediatric physiologically-based pharmacokinetic (PBPK) models may incorporate RT activity, but this requires ontogeny profiles for RT activity in children, especially neonates, to predict drug disposition. Therefore, RT expression measurements from human kidney postmortem cortical tissue samples were normalized to represent a fraction of mature RT activity. Using these data, maximum likelihood estimated the distributions of RT activity across the pediatric age spectrum, including preterm and term neonates. PBPK models of four RT substrates (acyclovir, ciprofloxacin, furosemide, and meropenem) were evaluated with and without ontogeny profiles using average fold error (AFE), absolute average fold error (AAFE), and proportion of observations within the 5-95% prediction interval. Novel maximum likelihood profiles estimated ontogeny distributions for the following RT: OAT1, OAT3, OCT2, P-gp, URAT1, BCRP, MATE1, MRP2, MRP4, and MATE-2 K. Profiles for OAT3, P-gp, and MATE1 improved infant furosemide and neonate meropenem PBPK model AFE from 0.08 to 0.70 and 0.53 to 1.34 and model AAFE from 12.08 to 1.44 and 2.09 to 1.36, respectively, and improved the percent of data within the 5-95% prediction interval from 48% to 98% for neonatal ciprofloxacin simulations, respectively. Even after accounting for other critical population-specific maturational differences, novel RT ontogeny profiles substantially improved neonatal PBPK model performance, providing validated estimates of maturational differences in RT activity for optimal dosing in children.
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Affiliation(s)
| | | | | | | | - Bianca D. van Groen
- Roche Pharma and Early Development (pRED), Roche Innovation Center BaselBaselSwitzerland
| | | | - Saskia N. de Wildt
- Erasmus MCRotterdamThe Netherlands
- Radboud UniversityNijmegenThe Netherlands
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Li T, Zhou S, Wang L, Zhao T, Wang J, Shao F. Docetaxel, cyclophosphamide, and epirubicin: application of PBPK modeling to gain new insights for drug-drug interactions. J Pharmacokinet Pharmacodyn 2024:10.1007/s10928-024-09912-z. [PMID: 38554227 DOI: 10.1007/s10928-024-09912-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Accepted: 02/20/2024] [Indexed: 04/01/2024]
Abstract
The new adjuvant chemotherapy of docetaxel, epirubicin, and cyclophosphamide has been recommended for treating breast cancer. It is necessary to investigate the potential drug-drug Interactions (DDIs) since they have a narrow therapeutic window in which slight differences in exposure might result in significant differences in treatment efficacy and tolerability. To guide clinical rational drug use, this study aimed to evaluate the DDI potentials of docetaxel, cyclophosphamide, and epirubicin in cancer patients using physiologically based pharmacokinetic (PBPK) models. The GastroPlus™ was used to develop the PBPK models, which were refined and validated with observed data. The established PBPK models accurately described the pharmacokinetics (PKs) of three drugs in cancer patients, and the predicted-to-observed ratios of all the PK parameters met the acceptance criterion. The PBPK model predicted no significant changes in plasma concentrations of these drugs during co-administration, which was consistent with the observed clinical phenomenon. Besides, the verified PBPK models were then used to predict the effect of other Cytochrome P450 3A4 (CYP3A4) inhibitors/inducers on these drug exposures. In the DDI simulation, strong CYP3A4 modulators changed the exposure of three drugs by 0.71-1.61 fold. Therefore, patients receiving these drugs in combination with strong CYP3A4 inhibitors should be monitored regularly to prevent adverse reactions. Furthermore, co-administration of docetaxel, cyclophosphamide, or epirubicin with strong CYP3A4 inducers should be avoided. In conclusion, the PBPK models can be used to further investigate the DDI potential of each drug and to develop dosage recommendations for concurrent usage by additional perpetrators or victims.
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Affiliation(s)
- Tongtong Li
- Phase I Clinical Trial Unit, The First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029, China
- Department of Clinical Pharmacology, School of Pharmacy College, Nanjing Medical University, Nanjing, 211166, China
| | - Sufeng Zhou
- Phase I Clinical Trial Unit, The First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029, China
| | - Lu Wang
- Phase I Clinical Trial Unit, The First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029, China
| | - Tangping Zhao
- Phase I Clinical Trial Unit, The First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029, China
- Department of Clinical Pharmacology, School of Pharmacy College, Nanjing Medical University, Nanjing, 211166, China
| | - Jue Wang
- Division of Breast Surgery, The First Affiliated Hospital With Nanjing Medical University, Guangzhou Road 300, Nanjing, 210029, Jiangsu Province, China
| | - Feng Shao
- Phase I Clinical Trial Unit, The First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029, China.
- Department of Clinical Pharmacology, School of Pharmacy College, Nanjing Medical University, Nanjing, 211166, China.
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Mehta K, Balazki P, van der Graaf PH, Guo T, van Hasselt JGC. Predictions of Bedaquiline Central Nervous System Exposure in Patients with Tuberculosis Meningitis Using Physiologically based Pharmacokinetic Modeling. Clin Pharmacokinet 2024:10.1007/s40262-024-01363-6. [PMID: 38530588 DOI: 10.1007/s40262-024-01363-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/15/2024] [Indexed: 03/28/2024]
Abstract
BACKGROUND AND OBJECTIVE The use of bedaquiline as a treatment option for drug-resistant tuberculosis meningitis (TBM) is of interest to address the increased prevalence of resistance to first-line antibiotics. To this end, we describe a whole-body physiologically based pharmacokinetic (PBPK) model for bedaquiline to predict central nervous system (CNS) exposure. METHODS A whole-body PBPK model was developed for bedaquiline and its metabolite, M2. The model included compartments for brain and cerebrospinal fluid (CSF). Model predictions were evaluated by comparison to plasma PK time profiles following different dosing regimens and sparse CSF concentrations data from patients. Simulations were then conducted to compare CNS and lung exposures to plasma exposure at clinically relevant dosing schedules. RESULTS The model appropriately described the observed plasma and CSF bedaquiline and M2 concentrations from patients with pulmonary tuberculosis (TB). The model predicted a high impact of tissue binding on target site drug concentrations in CNS. Predicted unbound exposures within brain interstitial exposures were comparable with unbound vascular plasma and unbound lung exposures. However, unbound brain intracellular exposures were predicted to be 7% of unbound vascular plasma and unbound lung intracellular exposures. CONCLUSIONS The whole-body PBPK model for bedaquiline and M2 predicted unbound concentrations in brain to be significantly lower than the unbound concentrations in the lung at clinically relevant doses. Our findings suggest that bedaquiline may result in relatively inferior efficacy against drug-resistant TBM when compared with efficacy against drug-resistant pulmonary TB.
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Affiliation(s)
- Krina Mehta
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
| | | | - Piet H van der Graaf
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Certara, Canterbury, UK
| | - Tingjie Guo
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - J G Coen van Hasselt
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
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Chen Y, Ke M, Fang W, Jiang Y, Lin R, Wu W, Huang P, Lin C. Physiologically based pharmacokinetic modeling to predict maternal pharmacokinetics and fetal carbamazepine exposure during pregnancy. Eur J Pharm Sci 2024; 194:106707. [PMID: 38244810 DOI: 10.1016/j.ejps.2024.106707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 01/11/2024] [Accepted: 01/17/2024] [Indexed: 01/22/2024]
Abstract
Carbamazepine is an antiepileptic drug commonly used in pregnant women, during which the physiological changes may affect its efficacy. The aim of this study was to establish a physiologically based pharmacokinetic (PBPK) model of carbamazepine and its active metabolite carbamazepine-10,11-epoxide, and simulate maternal and fetal pharmacokinetic changes of carbamazepine and carbamazepine-10,11-epoxide in different trimesters and propose dose adjustment. We established pregnancy PBPK models for carbamazepine and carbamazepine-10,11-epoxide in PK-Sim® and Mobi® and validated the models with observed data from clinical reports. The placental transfer parameters obtained using different methods were also imported into the model and compared with the observed data to establish and validate fetal pharmacokinetic curves. The simulated results showed that mean steady-state trough plasma concentration of carbamazepine decreased by 27, 43.1, and 52 % during the first, second, and third trimesters, respectively. Therefore, to achieve an optimum therapeutic concentration, administering at least 1.4, 1.8, and 2.1 times the baseline dose of carbamazepine in the first, second, and third trimesters, respectively can be used as a dose reference. In conclusion, this study established and validated a pregnancy PBPK model of carbamazepine and carbamazepine-10,11-epoxide to assess exposure in pregnant women and fetuses, which provided a reference for the dosage adjustment of carbamazepine during pregnancy.
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Affiliation(s)
- Yuying Chen
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, 20 Cha Zhong M. Rd, Fuzhou 350005, People's Republic of China; Department of Pharmacy, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China
| | - Meng Ke
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, 20 Cha Zhong M. Rd, Fuzhou 350005, People's Republic of China; Department of Pharmacy, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China
| | - Weipeng Fang
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, 20 Cha Zhong M. Rd, Fuzhou 350005, People's Republic of China; Department of Pharmacy, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China
| | - Yaojie Jiang
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, 20 Cha Zhong M. Rd, Fuzhou 350005, People's Republic of China; Department of Pharmacy, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China
| | - Rongfang Lin
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, 20 Cha Zhong M. Rd, Fuzhou 350005, People's Republic of China; Department of Pharmacy, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China
| | - Wanhong Wu
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, 20 Cha Zhong M. Rd, Fuzhou 350005, People's Republic of China; Department of Pharmacy, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China
| | - Pinfang Huang
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, 20 Cha Zhong M. Rd, Fuzhou 350005, People's Republic of China; Department of Pharmacy, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China
| | - Cuihong Lin
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, 20 Cha Zhong M. Rd, Fuzhou 350005, People's Republic of China; Department of Pharmacy, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China.
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Liu XI, Leong R, Burckart GJ, Dallmann A. Physiologically Based Pharmacokinetic Modeling of Nilotinib for Drug-Drug Interactions, Pediatric Patients, and Pregnancy and Lactation. J Clin Pharmacol 2024; 64:323-333. [PMID: 37909674 DOI: 10.1002/jcph.2379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 10/23/2023] [Indexed: 11/03/2023]
Abstract
Nilotinib is a second-generation BCR-ABL tyrosine kinase inhibitor for the treatment of Philadelphia chromosome-positive chronic myeloid leukemia in both adult and pediatric patients. The pharmacokinetics (PK) of nilotinib in specific populations such as pregnant and lactating people remain poorly understood. Therefore, the objectives of the current study were to develop a physiologically based pharmacokinetic (PBPK) model to predict nilotinib PK in virtual drug-drug interaction (DDI) studies, as well as in pediatric, pregnant, and lactating populations. The nilotinib PBPK model was built in PK-Sim, which is part of the free and open-source software Open Systems Pharmacology. The observed clinical data for the validation of the nilotinib models were obtained from the literature. The model reasonably predicted nilotinib concentrations in the adult population; the DDIs between nilotinib and rifampin or ketoconazole in the adult population; and the PK in the pediatric, pregnant, and lactating populations, although in the latter 2 populations plasma concentrations were slightly underestimated. The ratio of predicted versus observed PK parameters for the adult model ranged from 0.71 to 1.11 for area under the concentration-time curve and 0.55 to 0.95 for maximum concentration. For the DDI, the predicted area under the concentration-time curve ratio and maximum concentration ratio fell within the Guest criterion. The current study demonstrated the utility of using PBPK modeling to understand the mechanistic basis of PK differences between adults and specific populations, such as pediatrics, and pregnant and lactating individuals, indicating that this technology can potentially inform or optimize dosing conditions in specific populations.
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Affiliation(s)
- Xiaomei I Liu
- Division of Clinical Pharmacology, Children's National Hospital, Washington, DC, USA
| | - Ruby Leong
- Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, MD, USA
| | - Gilbert J Burckart
- Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, MD, USA
| | - André Dallmann
- Bayer HealthCare SAS, Loos, France, on behalf of: Pharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
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11
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Kang DW, Kim JH, Choi GW, Cho SJ, Cho HY. Physiologically-based pharmacokinetic model for evaluating gender-specific exposures of N-nitrosodimethylamine (NDMA). Arch Toxicol 2024; 98:821-835. [PMID: 38127128 DOI: 10.1007/s00204-023-03652-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 11/22/2023] [Indexed: 12/23/2023]
Abstract
N-nitrosodimethylamine (NDMA) is classified as a human carcinogen and could be produced by both natural and industrial processes. Although its toxicity and histopathology have been well-studied in animal species, there is insufficient data on the blood and tissue exposures that can be correlated with the toxicity of NDMA. The purpose of this study was to evaluate gender-specific pharmacokinetics/toxicokinetics (PKs/TKs), tissue distribution, and excretion after the oral administration of three different doses of NDMA in rats using a physiologically-based pharmacokinetic (PBPK) model. The major target tissues for developing the PBPK model and evaluating dose metrics of NDMA included blood, gastrointestinal (GI) tract, liver, kidney, lung, heart, and brain. The predictive performance of the model was validated using sensitivity analysis, (average) fold error, and visual inspection of observations versus predictions. Then, a Monte Carlo simulation was performed to describe the magnitudes of inter-individual variability and uncertainty of the single model predictions. The developed PBPK model was applied for the exposure simulation of daily oral NDMA to estimate blood concentration ranges affecting health effects following acute-duration (≤ 14 days), intermediate-duration (15-364 days), and chronic-duration (≥ 365 days) intakes. The results of the study could be used as a scientific basis for interpreting the correlation between in vivo exposures and toxicological effects of NDMA.
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Affiliation(s)
- Dong Wook Kang
- College of Pharmacy, CHA University, 335 Pangyo-Ro, Bundang-Gu, Seongnam-Si, Gyeonggi-Do, 13488, Republic of Korea
| | - Ju Hee Kim
- College of Pharmacy, CHA University, 335 Pangyo-Ro, Bundang-Gu, Seongnam-Si, Gyeonggi-Do, 13488, Republic of Korea
| | - Go-Wun Choi
- College of Pharmacy, CHA University, 335 Pangyo-Ro, Bundang-Gu, Seongnam-Si, Gyeonggi-Do, 13488, Republic of Korea
| | - Seok-Jin Cho
- College of Pharmacy, CHA University, 335 Pangyo-Ro, Bundang-Gu, Seongnam-Si, Gyeonggi-Do, 13488, Republic of Korea
| | - Hea-Young Cho
- College of Pharmacy, CHA University, 335 Pangyo-Ro, Bundang-Gu, Seongnam-Si, Gyeonggi-Do, 13488, Republic of Korea.
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12
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Lee JM, Yoon JH, Maeng HJ, Kim YC. Physiologically Based Pharmacokinetic (PBPK) Modeling to Predict CYP3A-Mediated Drug Interaction between Saxagliptin and Nicardipine: Bridging Rat-to-Human Extrapolation. Pharmaceutics 2024; 16:280. [PMID: 38399334 PMCID: PMC10892660 DOI: 10.3390/pharmaceutics16020280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 02/09/2024] [Accepted: 02/14/2024] [Indexed: 02/25/2024] Open
Abstract
The aim of this study was to predict the cytochrome P450 3A (CYP3A)-mediated drug-drug interactions (DDIs) between saxagliptin and nicardipine using a physiologically based pharmacokinetic (PBPK) model. Initially, in silico and in vitro parameters were gathered from experiments or the literature to construct PBPK models for each drug in rats. These models were integrated to predict the DDIs between saxagliptin, metabolized via CYP3A2, and nicardipine, exhibiting CYP3A inhibitory activity. The rat DDI PBPK model was completed by optimizing parameters using experimental rat plasma concentrations after co-administration of both drugs. Following co-administration in Sprague-Dawley rats, saxagliptin plasma concentration significantly increased, resulting in a 2.60-fold rise in AUC, accurately predicted by the rat PBPK model. Subsequently, the workflow of the rat PBPK model was applied to humans, creating a model capable of predicting DDIs between the two drugs in humans. Simulation from the human PBPK model indicated that nicardipine co-administration in humans resulted in a nearly unchanged AUC of saxagliptin, with an approximate 1.05-fold change, indicating no clinically significant changes and revealing a lack of direct translation of animal interaction results to humans. The animal-to-human PBPK model extrapolation used in this study could enhance the reliability of predicting drug interactions in clinical settings where DDI studies are challenging.
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Affiliation(s)
- Jeong-Min Lee
- Department of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of Korea;
| | - Jin-Ha Yoon
- College of Pharmacy, Gachon University, Incheon 21936, Republic of Korea;
| | - Han-Joo Maeng
- College of Pharmacy, Gachon University, Incheon 21936, Republic of Korea;
| | - Yu Chul Kim
- Department of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of Korea;
- Department of Pharmaceutical Engineering, Inje University, Gimhae 50834, Republic of Korea
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13
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Xu Y, Zhang L, Dou X, Dong Y, Guo X. Physiologically based pharmacokinetic modeling of apixaban to predict exposure in populations with hepatic and renal impairment and elderly populations. Eur J Clin Pharmacol 2024; 80:261-271. [PMID: 38099940 PMCID: PMC10847219 DOI: 10.1007/s00228-023-03602-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 12/02/2023] [Indexed: 02/07/2024]
Abstract
BACKGROUND Apixaban is a factor Xa inhibitor with a limited therapeutic index that belongs to the family of oral direct anticoagulants. The pharmacokinetic (PK) behavior of apixaban may be altered in elderly populations and populations with renal or hepatic impairment, necessitating dosage adjustments. METHODS This study was conducted to examine how the physiologically based pharmacokinetic (PBPK) model describes the PKs of apixaban in adult and elderly populations and to determine the PKs of apixaban in elderly populations with renal and hepatic impairment. After PBPK models were constructed using the reported physicochemical properties of apixaban and clinical data, they were validated using data from clinical studies involving various dose ranges. Comparing predicted and observed blood concentration data and PK parameters was utilized to evaluate the model's fit performance. RESULTS Doses should be reduced to approximately 70% of the healthy adult population for the healthy elderly population to achieve the same PK exposure; approximately 88%, 71%, and 89% of that for the elderly populations with mild, moderate, and severe renal impairment, respectively; and approximately 96%, 81%, and 58% of that for the Child Pugh-A, Child Pugh-B, and Child Pugh-C hepatic impairment elderly populations, respectively to achieve the same PK exposure. CONCLUSION The findings indicate that the renal and hepatic function might be considered for apixaban therapy in Chinese elderly patients and the PBPK model can be used to optimize dosage regimens for specific populations.
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Affiliation(s)
- Yichao Xu
- Center of Clinical Pharmacology, the Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, Zhejiang, China
| | - Lei Zhang
- Department of Pharmacy, the Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, Zhejiang, China
| | - Xiaofan Dou
- Center for Plastic & Reconstructive Surgery, Department of Orthopedics, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yongze Dong
- Center for Plastic & Reconstructive Surgery, Department of Orthopedics, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Xiangchai Guo
- Center for Plastic & Reconstructive Surgery, Department of Orthopedics, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China.
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Cho CK, Mo JY, Ko E, Kang P, Jang CG, Lee SY, Lee YJ, Bae JW, Choi CI. Physiologically based pharmacokinetic (PBPK) modeling of pitavastatin in relation to SLCO1B1 genetic polymorphism. Arch Pharm Res 2024; 47:95-110. [PMID: 38159179 DOI: 10.1007/s12272-023-01476-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024]
Abstract
Pitavastatin, a potent 3-hydroxymethylglutaryl coenzyme A reductase inhibitor, is indicated for the treatment of hypercholesterolemia and mixed dyslipidemia. Hepatic uptake of pitavastatin is predominantly occupied by the organic anion transporting polypeptide 1B1 (OATP1B1) and solute carrier organic anion transporter family member 1B1 (SLCO1B1) gene, which is a polymorphic gene that encodes OATP1B1. SLCO1B1 genetic polymorphism significantly alters the pharmacokinetics of pitavastatin. This study aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict pitavastatin pharmacokinetics according to SLCO1B1 genetic polymorphism. PK-Sim® version 10.0 was used to establish the whole-body PBPK model of pitavastatin. Our pharmacogenomic data and a total of 27 clinical pharmacokinetic data with different dose administration and demographic properties were used to develop and validate the model, respectively. Physicochemical properties and disposition characteristics of pitavastatin were acquired from previously reported data or optimized to capture the plasma concentration-time profiles in different SLCO1B1 diplotypes. Model evaluation was performed by comparing the predicted pharmacokinetic parameters and profiles to the observed data. Predicted plasma concentration-time profiles were visually similar to the observed profiles in the non-genotyped populations and different SLCO1B1 diplotypes. All fold error values for AUC and Cmax were included in the two fold range of observed values. Thus, the PBPK model of pitavastatin in different SLCO1B1 diplotypes was properly established. The present study can be useful to individualize the dose administration strategy of pitavastatin in individuals with various ages, races, and SLCO1B1 diplotypes.
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Affiliation(s)
- Chang-Keun Cho
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Ju Yeon Mo
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Eunvin Ko
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Pureum Kang
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Choon-Gon Jang
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Seok-Yong Lee
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
| | - Yun Jeong Lee
- College of Pharmacy, Dankook University, Cheonan, 31116, Republic of Korea
| | - Jung-Woo Bae
- College of Pharmacy, Keimyung University, Daegu, 42601, Republic of Korea
| | - Chang-Ik Choi
- College of Pharmacy, Dongguk University-Seoul, Goyang, 10326, Republic of Korea.
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15
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Verdegaal AA, Goodman AL. Integrating the gut microbiome and pharmacology. Sci Transl Med 2024; 16:eadg8357. [PMID: 38295186 DOI: 10.1126/scitranslmed.adg8357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 01/11/2024] [Indexed: 02/02/2024]
Abstract
The gut microbiome harbors trillions of organisms that contribute to human health and disease. These bacteria can also affect the properties of medical drugs used to treat these diseases, and drugs, in turn, can reshape the microbiome. Research addressing interdependent microbiome-host-drug interactions thus has broad impact. In this Review, we discuss these interactions from the perspective of drug bioavailability, absorption, metabolism, excretion, toxicity, and drug-mediated microbiome modulation. We survey approaches that aim to uncover the mechanisms underlying these effects and opportunities to translate this knowledge into new strategies to improve the development, administration, and monitoring of medical drugs.
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Affiliation(s)
- Andrew A Verdegaal
- Department of Microbial Pathogenesis and Microbial Sciences Institute, Yale University School of Medicine, New Haven, CT 06536, USA
| | - Andrew L Goodman
- Department of Microbial Pathogenesis and Microbial Sciences Institute, Yale University School of Medicine, New Haven, CT 06536, USA
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Frechen S, Ince I, Dallmann A, Gerisch M, Jungmann NA, Becker C, Lobmeyer M, Trujillo ME, Xu S, Burghaus R, Meyer M. Applied physiologically-based pharmacokinetic modeling to assess uridine diphosphate-glucuronosyltransferase-mediated drug-drug interactions for Vericiguat. CPT Pharmacometrics Syst Pharmacol 2024; 13:79-92. [PMID: 37794724 PMCID: PMC10787200 DOI: 10.1002/psp4.13059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 09/21/2023] [Accepted: 09/25/2023] [Indexed: 10/06/2023] Open
Abstract
Vericiguat (Verquvo; US: Merck, other countries: Bayer) is a novel drug for the treatment of chronic heart failure. Preclinical studies have demonstrated that the primary route of metabolism for vericiguat is glucuronidation, mainly catalyzed by uridine diphosphate-glucuronosyltransferase (UGT)1A9 and to a lesser extent UGT1A1. Whereas a drug-drug interaction (DDI) study of the UGT1A9 inhibitor mefenamic acid showed a 20% exposure increase, the effect of UGT1A1 inhibitors has not been assessed clinically. This modeling study describes a physiologically-based pharmacokinetic (PBPK) approach to complement the clinical DDI liability assessment and support prescription labeling. A PBPK model of vericiguat was developed based on in vitro and clinical data, verified against data from the mefenamic acid DDI study, and applied to assess the UGT1A1 DDI liability by running an in silico DDI study with the UGT1A1 inhibitor atazanavir. A minor effect with an area under the plasma concentration-time curve (AUC) ratio of 1.12 and a peak plasma concentration ratio of 1.04 was predicted, which indicates that there is no clinically relevant DDI interaction anticipated. Additionally, the effect of potential genetic polymorphisms of UGT1A1 and UGT1A9 was evaluated, which showed that an average modest increase of up to 1.7-fold in AUC may be expected in the case of concomitantly reduced UGT1A1 and UGT1A9 activity for subpopulations expressing non-wild-type variants for both isoforms. This study is a first cornerstone to qualify the PK-Sim platform for use of UGT-mediated DDI predictions, including PBPK models of perpetrators, such as mefenamic acid and atazanavir, and sensitive UGT substrates, such as dapagliflozin and raltegravir.
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Affiliation(s)
- Sebastian Frechen
- Pharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
| | - Ibrahim Ince
- Pharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
| | - André Dallmann
- Pharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
| | - Michael Gerisch
- DMPK, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
| | - Natalia A Jungmann
- DMPK, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
| | - Corina Becker
- Clinical Pharmacology, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
| | - Maximilian Lobmeyer
- Clinical Pharmacology, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
| | | | - Shiyao Xu
- Merck & Co., Inc., Rahway, New Jersey, USA
| | - Rolf Burghaus
- Pharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
| | - Michaela Meyer
- Pharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
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Guo L, Zhu X, Zhang L, Xu Y. Physiologically based pharmacokinetic modeling of candesartan to predict the exposure in hepatic and renal impairment and elderly populations. Ther Adv Drug Saf 2023; 14:20420986231220222. [PMID: 38157240 PMCID: PMC10752084 DOI: 10.1177/20420986231220222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 11/27/2023] [Indexed: 01/03/2024] Open
Abstract
Background Candesartan cilexetil is a widely used angiotensin II receptor blocker with minimal adverse effects and high tolerability for the treatment of hypertension. Candesartan is administered orally as the prodrug candesartan cilexetil, which is wholly and swiftly converted to the active metabolite candesartan by carboxylesterase during absorption in the intestinal tract. In populations with renal or hepatic impairment, candesartan's pharmacokinetic (PK) behavior may be altered, necessitating dosage adjustments. Objectives This study was conducted to examine how the physiologically based PK (PBPK) model characterizes the PKs of candesartan in adult and geriatric populations and to predict the PKs of candesartan in elderly populations with renal and hepatic impairment. Design After developing PBPK models using the reported physicochemical properties of candesartan and clinical data, these models were validated using data from clinical investigations involving various dose ranges. Methods Comparing predicted and observed blood concentration data and PK parameters was used to assess the fit performance of the models. Results Doses should be reduced to approximately 94% of Chinese healthy adults for the Chinese healthy elderly population; approximately 92%, 68%, and 64% of that of the Chinese healthy adult dose in elderly populations with mild, moderate, and severe renal impairment, respectively; and approximately 72%, 71%, and 52% of that of the Chinese healthy adult dose in elderly populations with Child-Pugh-A, Child-Pugh-B, and Child-Pugh-C hepatic impairment, respectively. Conclusion The results suggest that the PBPK model of candesartan can be utilized to optimize dosage regimens for special populations.
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Affiliation(s)
- Lingfeng Guo
- The First Affiliated Hospital of Zhejiang University Shengzhou Branch, School of Medicine, Shengzhou, Zhejiang, China
| | - Xinyu Zhu
- The First Affiliated Hospital of Zhejiang University Shengzhou Branch, School of Medicine, Shengzhou, Zhejiang, China
| | - Lei Zhang
- Department of Pharmacy, The Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, Zhejiang, China
| | - Yichao Xu
- Center of Clinical Pharmacology, The Second Affiliated Hospital of Zhejiang University, School of Medicine, 88 Jiefang Road, Hangzhou, Zhejiang 310009, China
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Alqahtani F, Alruwaili AH, Alasmari MS, Almazroa SA, Alsuhaibani KS, Rasool MF, Alruwaili AF, Alsanea S. A Physiologically Based Pharmacokinetic Model to Predict Systemic Ondansetron Concentration in Liver Cirrhosis Patients. Pharmaceuticals (Basel) 2023; 16:1693. [PMID: 38139819 PMCID: PMC10747545 DOI: 10.3390/ph16121693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 11/30/2023] [Accepted: 12/01/2023] [Indexed: 12/24/2023] Open
Abstract
INTRODUCTION Ondansetron is a drug that is routinely prescribed for the management of nausea and vomiting associated with cancer, radiation therapy, and surgical operations. It is mainly metabolized in the liver, and it might accumulate in patients with hepatic impairment and lead to unwanted adverse events. METHODS A physiologically based pharmacokinetic (PBPK) model was developed to predict the exposure of ondansetron in healthy and liver cirrhosis populations. The population-based PBPK simulator PK-Sim was utilized for simulating ondansetron exposure in healthy and liver cirrhosis populations. RESULTS The developed model successfully described the pharmacokinetics of ondansetron in healthy and liver cirrhosis populations. The predicted area under the curve, maximum systemic concentration, and clearance were within the allowed twofold range. The exposure of ondansetron in the population of Child-Pugh class C has doubled in comparison to Child-Pugh class A. The dose has to be adjusted for liver cirrhosis patients to ensure comparable exposure to a healthy population. CONCLUSION In this study, the developed PBPK model has described the pharmacokinetics of ondansetron successfully. The PBPK model has been successfully evaluated to be used as a tool for dose adjustments in liver cirrhosis patients.
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Affiliation(s)
- Faleh Alqahtani
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (F.A.); (A.H.A.); (S.A.A.); (K.S.A.)
| | - Abdullah H. Alruwaili
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (F.A.); (A.H.A.); (S.A.A.); (K.S.A.)
| | - Mohammed S. Alasmari
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (F.A.); (A.H.A.); (S.A.A.); (K.S.A.)
| | - Sultan A. Almazroa
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (F.A.); (A.H.A.); (S.A.A.); (K.S.A.)
| | - Khaled S. Alsuhaibani
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (F.A.); (A.H.A.); (S.A.A.); (K.S.A.)
| | - Muhammad F. Rasool
- Department of Pharmacy Practice, Faculty of Pharmacy, Bahauddin Zakariya University, Multan 60800, Pakistan;
| | - Abdulkarim F. Alruwaili
- Clinical Pharmacy Unit, Department of Pharmaceutical Services, Dallah Hospital, Riyadh 12381, Saudi Arabia;
| | - Sary Alsanea
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (F.A.); (A.H.A.); (S.A.A.); (K.S.A.)
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19
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Cho CK, Kang P, Jang CG, Lee SY, Lee YJ, Choi CI. Physiologically based pharmacokinetic (PBPK) modeling to predict the pharmacokinetics of irbesartan in different CYP2C9 genotypes. Arch Pharm Res 2023; 46:939-953. [PMID: 38064121 DOI: 10.1007/s12272-023-01472-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 11/22/2023] [Indexed: 12/17/2023]
Abstract
Irbesartan, a potent and selective angiotensin II type-1 (AT1) receptor blocker (ARB), is one of the representative medications for the treatment of hypertension. Cytochrome P450 (CYP) 2C9 is primarily involved in the oxidation of irbesartan. CYP2C9 is highly polymorphic, and genetic polymorphism of this enzyme is the leading cause of significant alterations in the pharmacokinetics of irbesartan. This study aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics of irbesartan in different CYP2C9 genotypes. The irbesartan PBPK model was established using the PK-Sim® software. Our previously reported pharmacogenomic data for irbesartan was leveraged in the development of the PBPK model and collected clinical pharmacokinetic data for irbesartan was used for the validation of the model. Physicochemical and ADME properties of irbesartan were obtained from previously reported data, predicted by the modeling software, or optimized to fit the observed plasma concentration-time profiles. Model evaluation was performed by comparing the predicted plasma concentration-time profiles and pharmacokinetic parameters to the observed results. Predicted plasma concentration-time profiles were visually similar to observed profiles. Predicted AUCinf in CYP2C9*1/*3 and CYP2C9*1/*13 genotypes were increased by 1.54- and 1.62-fold compared to CYP2C9*1/*1 genotype, respectively. All fold error values for AUC and Cmax in non-genotyped and CYP2C9 genotyped models were within the two-fold error criterion. We properly established the PBPK model of irbesartan in different CYP2C9 genotypes. It can be used to predict the pharmacokinetics of irbesartan for personalized pharmacotherapy in individuals of various races, ages, and CYP2C9 genotypes.
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Affiliation(s)
- Chang-Keun Cho
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Pureum Kang
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Choon-Gon Jang
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Seok-Yong Lee
- School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
| | - Yun Jeong Lee
- College of Pharmacy, Dankook University, Cheonan, 31116, Republic of Korea
| | - Chang-Ik Choi
- College of Pharmacy, Dongguk University-Seoul, Goyang, 10326, Republic of Korea.
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Llopis-Lorente J, Baroudi S, Koloskoff K, Mora MT, Basset M, Romero L, Benito S, Dayan F, Saiz J, Trenor B. Combining pharmacokinetic and electrophysiological models for early prediction of drug-induced arrhythmogenicity. Comput Methods Programs Biomed 2023; 242:107860. [PMID: 37844488 DOI: 10.1016/j.cmpb.2023.107860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/28/2023] [Accepted: 10/10/2023] [Indexed: 10/18/2023]
Abstract
BACKGROUND AND OBJECTIVE In silico methods are gaining attention for predicting drug-induced Torsade de Pointes (TdP) in different stages of drug development. However, many computational models tended not to account for inter-individual response variability due to demographic covariates, such as sex, or physiologic covariates, such as renal function, which may be crucial when predicting TdP. This study aims to compare the effects of drugs in male and female populations with normal and impaired renal function using in silico methods. METHODS Pharmacokinetic models considering sex and renal function as covariates were implemented from data published in pharmacokinetic studies. Drug effects were simulated using an electrophysiologically calibrated population of cellular models of 300 males and 300 females. The population of models was built by modifying the endocardial action potential model published by O'Hara et al. (2011) according to the experimentally measured gene expression levels of 12 ion channels. RESULTS Fifteen pharmacokinetic models for CiPA drugs were implemented and validated in this study. Eight pharmacokinetic models included the effect of renal function and four the effect of sex. The mean difference in action potential duration (APD) between male and female populations was 24.9 ms (p<0.05). Our simulations indicated that women with impaired renal function were particularly susceptible to drug-induced arrhythmias, whereas healthy men were less prone to TdP. Differences between patient groups were more pronounced for high TdP-risk drugs. The proposed in silico tool also revealed that individuals with impaired renal function, electrophysiologically simulated with hyperkalemia (extracellular potassium concentration [K+]o = 7 mM) exhibited less pronounced APD prolongation than individuals with normal potassium levels. The pharmacokinetic/electrophysiological framework was used to determine the maximum safe dose of dofetilide in different patient groups. As a proof of concept, 3D simulations were also run for dofetilide obtaining QT prolongation in accordance with previously reported clinical values. CONCLUSIONS This study presents a novel methodology that combines pharmacokinetic and electrophysiological models to incorporate the effects of sex and renal function into in silico drug simulations and highlights their impact on TdP-risk assessment. Furthermore, it may also help inform maximum dose regimens that ensure TdP-related safety in a specific sub-population of patients.
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Affiliation(s)
- Jordi Llopis-Lorente
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, 46022, Valencia, Spain
| | | | | | - Maria Teresa Mora
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, 46022, Valencia, Spain
| | | | - Lucía Romero
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, 46022, Valencia, Spain
| | | | | | - Javier Saiz
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, 46022, Valencia, Spain
| | - Beatriz Trenor
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, 46022, Valencia, Spain.
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21
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Maruyama T, Kimura T, Ebihara F, Kasai H, Matsunaga N, Hamada Y. Comparison of the predictive accuracy of the physiologically based pharmacokinetic (PBPK) model and population pharmacokinetic (PPK) model of vancomycin in Japanese patients with MRSA infection. J Infect Chemother 2023; 29:1152-1159. [PMID: 37673298 DOI: 10.1016/j.jiac.2023.08.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/26/2023] [Accepted: 08/29/2023] [Indexed: 09/08/2023]
Abstract
INTRODUCTION The latest therapeutic drug monitoring guidelines for vancomycin (VCM) recommend that area under the concentration-time curve is estimated based on model-informed precision dosing and used to evaluate efficacy and safety. Therefore, we predicted VCM concentrations in individual methicillin-resistant Staphylococcus aureus-infected patients using existing a physiologically based pharmacokinetic (PBPK) model and 1- and 2-compartment population pharmacokinetic (PPK) models and confirmed and verified the accuracy of the PBPK model in estimating VCM concentrations with the PPK model. METHODS The subjects of the study are 20 patients, and the predicted concentrations were evaluated by comparing the observed and predicted trough and peak values of VCM concentrations for individual patients. RESULTS The results showed good correlation between the observed and predicted trough and peak concentrations of VCM was observed generally in the PBPK model, R2 values of 0.72, 0.62, and 0.40 with trough values of 0.49, 0.40, and 0.34 with peak values for PBPK model, 1-compartment, and 2-compartment model, respectively. CONCLUSIONS Although the performance of the PBPK model is not as predictive as the PPK model, generally similar predictive trends were obtained, suggesting that it may be a valuable tool for rapid and accurate prediction of AUC for VCM.
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Affiliation(s)
- Takumi Maruyama
- Department of Pharmacy, Tokyo Women's Medical University Hospital, 8-1, Kawadacho, Shinjuku-ku, Tokyo, 162-8666, Japan
| | - Toshimi Kimura
- Department of Pharmacy, Juntendo University Hospital, 3-1-3 Hongo, Bunkyo-ku, Tokyo, 113-8431, Japan
| | - Fumiya Ebihara
- Department of Pharmacy, Tokyo Women's Medical University Hospital, 8-1, Kawadacho, Shinjuku-ku, Tokyo, 162-8666, Japan
| | - Hidefumi Kasai
- Laboratory of Pharmacometrics and Systems Pharmacology Keio Frontier Research and Education Collaboration Square (K-FRECS) at Tonomachi, Keio University Kawasaki, Kanagawa, 210-0821, Japan
| | - Nobuaki Matsunaga
- AMR Clinical Reference Center, National Center for Global Health and Medicine Hospital, 1-21-1, Toyama, Shinjuku-ku, Tokyo, 162-8655, Japan
| | - Yukihiro Hamada
- Department of Pharmacy, Tokyo Women's Medical University Hospital, 8-1, Kawadacho, Shinjuku-ku, Tokyo, 162-8666, Japan.
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22
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Fendt R, Ghallab A, Myllys M, Hofmann U, Hassan R, Hobloss Z, González D, Brackhagen L, Marchan R, Edlund K, Seddek AL, Abdelmageed N, Blank LM, Schlender JF, Holland CH, Hengstler JG, Kuepfer L. Increased sinusoidal export of drug glucuronides is a compensative mechanism in liver cirrhosis of mice. Front Pharmacol 2023; 14:1279357. [PMID: 38053838 PMCID: PMC10694292 DOI: 10.3389/fphar.2023.1279357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 11/01/2023] [Indexed: 12/07/2023] Open
Abstract
Rationale: Liver cirrhosis is known to affect drug pharmacokinetics, but the functional assessment of the underlying pathophysiological alterations in drug metabolism is difficult. Methods: Cirrhosis in mice was induced by repeated treatment with carbon tetrachloride for 12 months. A cocktail of six drugs was administered, and parent compounds as well as phase I and II metabolites were quantified in blood, bile, and urine in a time-dependent manner. Pharmacokinetics were modeled in relation to the altered expression of metabolizing enzymes. In discrepancy with computational predictions, a strong increase of glucuronides in blood was observed in cirrhotic mice compared to vehicle controls. Results: The deviation between experimental findings and computational simulations observed by analyzing different hypotheses could be explained by increased sinusoidal export and corresponded to increased expression of export carriers (Abcc3 and Abcc4). Formation of phase I metabolites and clearance of the parent compounds were surprisingly robust in cirrhosis, although the phase I enzymes critical for the metabolism of the administered drugs in healthy mice, Cyp1a2 and Cyp2c29, were downregulated in cirrhotic livers. RNA-sequencing revealed the upregulation of numerous other phase I metabolizing enzymes which may compensate for the lost CYP isoenzymes. Comparison of genome-wide data of cirrhotic mouse and human liver tissue revealed similar features of expression changes, including increased sinusoidal export and reduced uptake carriers. Conclusion: Liver cirrhosis leads to increased blood concentrations of glucuronides because of increased export from hepatocytes into the sinusoidal blood. Although individual metabolic pathways are massively altered in cirrhosis, the overall clearance of the parent compounds was relatively robust due to compensatory mechanisms.
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Affiliation(s)
- Rebekka Fendt
- Institute for Systems Medicine with Focus on Organ Interaction, University Hospital RWTH Aachen, Aachen, Germany
| | - Ahmed Ghallab
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany
- Department of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena, Egypt
| | - Maiju Myllys
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany
| | - Ute Hofmann
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology and University of Tübingen, Stuttgart, Germany
| | - Reham Hassan
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany
- Department of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena, Egypt
| | - Zaynab Hobloss
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany
| | - Daniela González
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany
| | - Lisa Brackhagen
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany
| | - Rosemarie Marchan
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany
| | - Karolina Edlund
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany
| | - Abdel-Latif Seddek
- Department of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena, Egypt
| | - Noha Abdelmageed
- Department of Pharmacology, Faculty of Veterinary Medicine, Sohag University, Sohag, Egypt
| | - Lars M. Blank
- Institute of Applied Microbiology—iAMB, Aachen Biology and Biotechnology—ABBt, RWTH Aachen University, Aachen, Germany
| | - Jan-Frederik Schlender
- Pharmacometrics, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
| | - Christian H. Holland
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany
| | - Jan G. Hengstler
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany
| | - Lars Kuepfer
- Institute for Systems Medicine with Focus on Organ Interaction, University Hospital RWTH Aachen, Aachen, Germany
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23
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van der Heijden JEM, Freriksen JJM, de Hoop-Sommen MA, Greupink R, de Wildt SN. Physiologically-Based Pharmacokinetic Modeling for Drug Dosing in Pediatric Patients: A Tutorial for a Pragmatic Approach in Clinical Care. Clin Pharmacol Ther 2023; 114:960-971. [PMID: 37553784 DOI: 10.1002/cpt.3023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 08/02/2023] [Indexed: 08/10/2023]
Abstract
It is well-accepted that off-label drug dosing recommendations for pediatric patients should be based on the best available evidence. However, the available traditional evidence is often low. To bridge this gap, physiologically-based pharmacokinetic (PBPK) modeling is a scientifically well-founded tool that can be used to enable model-informed dosing (MID) recommendations in children in clinical practice. In this tutorial, we provide a pragmatic, PBPK-based pediatric modeling workflow. For this approach to be successfully implemented in pediatric clinical practice, a thorough understanding of the model assumptions and limitations is required. More importantly, careful evaluation of an MID approach within the context of overall benefits and the potential risks is crucial. The tutorial is aimed to help modelers, researchers, and clinicians, to effectively use PBPK simulations to support pediatric drug dosing.
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Affiliation(s)
- Joyce E M van der Heijden
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jolien J M Freriksen
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marika A de Hoop-Sommen
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Rick Greupink
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Saskia N de Wildt
- Division of Pharmacology and Toxicology, Department of Pharmacy, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Pediatric and Neonatal Intensive Care, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
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24
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Kister B, Viehof A, Rolle-Kampczyk U, Schwentker A, Treichel NS, Jennings SA, Wirtz TH, Blank LM, Hornef MW, von Bergen M, Clavel T, Kuepfer L. A physiologically based model of bile acid metabolism in mice. iScience 2023; 26:107922. [PMID: 37817939 PMCID: PMC10561051 DOI: 10.1016/j.isci.2023.107922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 07/04/2023] [Accepted: 09/12/2023] [Indexed: 10/12/2023] Open
Abstract
Bile acid (BA) metabolism is a complex system that includes a wide variety of primary and secondary, as well as conjugated and unconjugated BAs that undergo continuous enterohepatic circulation (EHC). Alterations in both composition and dynamics of BAs have been associated with various diseases. However, a mechanistic understanding of the relationship between altered BA metabolism and related diseases is lacking. Computational modeling may support functional analyses of the physiological processes involved in the EHC of BAs along the gut-liver axis. In this study, we developed a physiologically based model of murine BA metabolism describing synthesis, hepatic and microbial transformations, systemic distribution, excretion, and EHC of BAs at the whole-body level. For model development, BA metabolism of specific pathogen-free (SPF) mice was characterized in vivo by measuring BA levels and composition in various organs, expression of transporters along the gut, and cecal microbiota composition. We found significantly different BA levels between male and female mice that could only be explained by adjusted expression of the hepatic enzymes and transporters in the model. Of note, this finding was in agreement with experimental observations. The model for SPF mice could also describe equivalent experimental data in germ-free mice by specifically switching off microbial activity in the intestine. The here presented model can therefore facilitate and guide functional analyses of BA metabolism in mice, e.g., the effect of pathophysiological alterations on BA metabolism and translation of results from mouse studies to a clinically relevant context through cross-species extrapolation.
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Affiliation(s)
- Bastian Kister
- Institute for Systems Medicine with Focus on Organ Interaction, University Hospital RWTH Aachen, Aachen, Germany
- Institute of Applied Microbiology - iAMB, Aachen Biology and Biotechnology - ABBt, RWTH Aachen University, Aachen, Germany
| | - Alina Viehof
- Functional Microbiome Research Group, Institute of Medical Microbiology, University Hospital RWTH Aachen, Aachen, Germany
| | - Ulrike Rolle-Kampczyk
- Department of Molecular Systems Biology, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany
| | - Annika Schwentker
- Institute of Medical Microbiology, University Hospital RWTH Aachen, Aachen, Germany
| | - Nicole Simone Treichel
- Functional Microbiome Research Group, Institute of Medical Microbiology, University Hospital RWTH Aachen, Aachen, Germany
| | - Susan A.V. Jennings
- Functional Microbiome Research Group, Institute of Medical Microbiology, University Hospital RWTH Aachen, Aachen, Germany
| | - Theresa H. Wirtz
- Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany
| | - Lars M. Blank
- Institute of Applied Microbiology - iAMB, Aachen Biology and Biotechnology - ABBt, RWTH Aachen University, Aachen, Germany
| | - Mathias W. Hornef
- Institute of Medical Microbiology, University Hospital RWTH Aachen, Aachen, Germany
| | - Martin von Bergen
- Department of Molecular Systems Biology, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Faculty of Life Sciences, Institute of Biochemistry, University of Leipzig, Leipzig, Germany
| | - Thomas Clavel
- Functional Microbiome Research Group, Institute of Medical Microbiology, University Hospital RWTH Aachen, Aachen, Germany
| | - Lars Kuepfer
- Institute for Systems Medicine with Focus on Organ Interaction, University Hospital RWTH Aachen, Aachen, Germany
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25
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Shao W, Shen C, Wang W, Sun H, Wang X, Geng K, Wang X, Xie H. Development and Validation of Physiologically Based Pharmacokinetic Model of Levetiracetam to Predict Exposure and Dose Optimization in Pediatrics. J Pharm Sci 2023; 112:2667-2675. [PMID: 37023853 DOI: 10.1016/j.xphs.2023.03.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 03/29/2023] [Accepted: 03/29/2023] [Indexed: 04/08/2023]
Abstract
Levetiracetam (Lev) is an antiepileptic drug that has been increasingly used in the epilepsy pediatric population in recent years, but its pharmacokinetic behavior in pediatric population needs to be characterized clearly. Clinical trials for the pediatric drug remain difficult to conduct due to ethical and practical factors. The purpose of this study was to use the physiologically based pharmacokinetic (PBPK) model to predict changes in plasma exposure of Lev in pediatric patients and to provide recommendations for dose adjustment. A PBPK model of Lev in adults was developed using PK-Sim® software and extrapolated to the entire age range of the pediatric population. The model was evaluated using clinical pharmacokinetic data. The results showed the good fit between predictions and observations of the adult and pediatric models. The recommended doses for neonates, infants and children are 0.78, 1.67 and 1.22 times that of adults, respectively. Moreover, at the same dose, plasma exposure in adolescents was similar to that of adults. The PBPK models of Lev for adults and pediatrics were successfully developed and validated to provide a reference for the rational administration of drugs in the pediatric population.
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Affiliation(s)
- Wenxin Shao
- Anhui Provincial Center for Drug Clinical Evaluation, Yijishan Hospital of Wannan Medical College, Wuhu 241001, Anhui, China
| | - Chaozhuang Shen
- Anhui Provincial Center for Drug Clinical Evaluation, Yijishan Hospital of Wannan Medical College, Wuhu 241001, Anhui, China
| | - Wenhui Wang
- Anhui Provincial Center for Drug Clinical Evaluation, Yijishan Hospital of Wannan Medical College, Wuhu 241001, Anhui, China
| | - Hua Sun
- Anhui Provincial Center for Drug Clinical Evaluation, Yijishan Hospital of Wannan Medical College, Wuhu 241001, Anhui, China
| | - Xiaohu Wang
- Anhui Provincial Center for Drug Clinical Evaluation, Yijishan Hospital of Wannan Medical College, Wuhu 241001, Anhui, China
| | - Kuo Geng
- Anhui Provincial Center for Drug Clinical Evaluation, Yijishan Hospital of Wannan Medical College, Wuhu 241001, Anhui, China
| | - Xingwen Wang
- Anhui Provincial Center for Drug Clinical Evaluation, Yijishan Hospital of Wannan Medical College, Wuhu 241001, Anhui, China
| | - Haitang Xie
- Anhui Provincial Center for Drug Clinical Evaluation, Yijishan Hospital of Wannan Medical College, Wuhu 241001, Anhui, China.
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26
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Zaid NRR, Kletting P, Beer AJ, Stallons TAR, Torgue JJ, Glatting G. Mathematical Modeling of In Vivo Alpha Particle Generators and Chelator Stability. Cancer Biother Radiopharm 2023; 38:528-535. [PMID: 33481653 DOI: 10.1089/cbr.2020.4112] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Background: Targeted α particle therapy using long-lived in vivo α particle generators is cytotoxic to target tissues. However, the redistribution of released radioactive daughters through the circulation should be considered. A mathematical model was developed to describe the physicochemical kinetics of 212Pb-labeled pharmaceuticals and its radioactive daughters. Materials and Methods: A bolus of 212Pb-labeled pharmaceuticals injected in a developed compartmental model was simulated. The contributions of chelated and free radionuclides to the total released energy were investigated for different dissociation fractions of 212Bi for different chelators, for example, 36% for DOTA. The compartmental model was applied to describe a 212Bi retention study and to assess the stability of the 212Bi-1,4,7,10-tetrakis(carbamoylmethyl)-1,4,7,10-tetraazacyclododecane (212Bi-DOTAM) complex after β- decay of 212Pb. Results: The simulation of the injection showed that α emissions contribute 75% to the total released energy, mostly from 212Po (72%). The simulation of the 212Bi retention study showed that (16 ± 5)% of 212Bi atoms dissociate from the 212Bi-DOTAM complexes. The fractions of energies released by free radionuclides were 21% and 38% for DOTAM and DOTA chelators, respectively. Conclusion: The developed α particle generator model allows for simulating the radioactive kinetics of labeled and unlabeled pharmaceuticals being released from the chelating system due to a preceding disintegration.
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Affiliation(s)
- Nouran R R Zaid
- Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany
- Department of Biomedical Sciences, Biophysics and Medical Imaging Program, Faculty of Medicine and Health Sciences, An-Najah National University, Nablus, Palestine
| | - Peter Kletting
- Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany
- Department of Nuclear Medicine, Ulm University, Ulm, Germany
| | - Ambros J Beer
- Department of Nuclear Medicine, Ulm University, Ulm, Germany
| | | | | | - Gerhard Glatting
- Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany
- Department of Nuclear Medicine, Ulm University, Ulm, Germany
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27
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Ali Daoud Y, Tebby C, Beaudouin R, Brochot C. Development of a physiologically based toxicokinetic model for lead in pregnant women: The role of bone tissue in the maternal and fetal internal exposure. Toxicol Appl Pharmacol 2023; 476:116651. [PMID: 37549741 DOI: 10.1016/j.taap.2023.116651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 08/01/2023] [Accepted: 08/04/2023] [Indexed: 08/09/2023]
Abstract
Epidemiological studies have shown associations between prenatal exposure to lead (Pb) and neurodevelopmental effects in young children. Prenatal exposure is generally characterized by measuring the concentration in the umbilical cord at delivery or in the maternal blood during pregnancy. To assess internal Pb exposure during prenatal life, we developed a pregnancy physiologically based pharmacokinetic (p-PBPK) model that to simulates Pb levels in blood and target tissues in the fetus, especially during critical periods for brain development. An existing Pb PBPK model was adapted to pregnant women and fetuses. Using data from literature, both the additional maternal bone remodeling, that causes Pb release into the blood, and the Pb placental transfers were estimated by Bayesian inference. Additional maternal bone remodeling was estimated to start at 21.6 weeks. Placental transfers were estimated between 4.6 and 283 L.day-1 at delivery with high interindividual variability. Once calibrated, the p-PBPK model was used to simulate fetal exposure to Pb. Internal fetal exposure greatly varies over the pregnancy with two peaks of Pb levels in blood and brain at the end of the 1st and 3rd trimesters. Sensitivity analysis shows that the fetal blood lead levels are affected by the maternal burden of bone Pb via maternal bone remodeling and by fetal bone formation at different pregnancy stages. Coupling the p-PBPK model with an effect model such as an adverse outcome pathway could help to predict the effects on children's neurodevelopment.
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Affiliation(s)
- Yourdasmine Ali Daoud
- Experimental toxicology and modeling unit (MIV/TEAM), Institut National de l'Environnement Industriel et des Risques, 60550 Verneuil-en-Halatte, France; Péritox, UMR-I 01, University of Picardie Jules Verne, 80025 Amiens, France
| | - Cleo Tebby
- Experimental toxicology and modeling unit (MIV/TEAM), Institut National de l'Environnement Industriel et des Risques, 60550 Verneuil-en-Halatte, France.
| | - Rémy Beaudouin
- Experimental toxicology and modeling unit (MIV/TEAM), Institut National de l'Environnement Industriel et des Risques, 60550 Verneuil-en-Halatte, France; Sebio, UMR-I 02, Institut National de l'Environnement Industriel et des Risques, 60550 Verneuil-en-Halatte, France
| | - Céline Brochot
- Experimental toxicology and modeling unit (MIV/TEAM), Institut National de l'Environnement Industriel et des Risques, 60550 Verneuil-en-Halatte, France; Certara UK Ltd, Simcyp Division, Sheffield, UK
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28
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Kopańska K, Rodríguez-Belenguer P, Llopis-Lorente J, Trenor B, Saiz J, Pastor M. Uncertainty assessment of proarrhythmia predictions derived from multi-level in silico models. Arch Toxicol 2023; 97:2721-2740. [PMID: 37528229 PMCID: PMC10474996 DOI: 10.1007/s00204-023-03557-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 07/12/2023] [Indexed: 08/03/2023]
Abstract
In silico methods can be used for an early assessment of arrhythmogenic properties of drug candidates. However, their use for decision-making is conditioned by the possibility to estimate the predictions' uncertainty. This work describes our efforts to develop uncertainty quantification methods for the predictions produced by multi-level proarrhythmia models. In silico models used in this field usually start with experimental or predicted IC50 values that describe drug-induced ion channel blockade. Using such inputs, an electrophysiological model computes how the ion channel inhibition, exerted by a drug in a certain concentration, translates to an altered shape and duration of the action potential in cardiac cells, which can be represented as arrhythmogenic risk biomarkers such as the APD90. Using this framework, we identify the main sources of aleatory and epistemic uncertainties and propose a method based on probabilistic simulations that replaces single-point estimates predicted using multiple input values, including the IC50s and the electrophysiological parameters, by distributions of values. Two selected variability types associated with these inputs are then propagated through the multi-level model to estimate their impact on the uncertainty levels in the output, expressed by means of intervals. The proposed approach yields single predictions of arrhythmogenic risk biomarkers together with value intervals, providing a more comprehensive and realistic description of drug effects on a human population. The methodology was tested by predicting arrhythmogenic biomarkers on a series of twelve well-characterised marketed drugs, belonging to different arrhythmogenic risk classes.
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Affiliation(s)
- Karolina Kopańska
- Research Programme on Biomedical Informatics (GRIB), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Hospital del Mar Research Institute, Barcelona, Spain
| | - Pablo Rodríguez-Belenguer
- Research Programme on Biomedical Informatics (GRIB), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Hospital del Mar Research Institute, Barcelona, Spain
- Department of Pharmacy and Pharmaceutical Technology and Parasitology, Universitat de València, Valencia, Spain
| | - Jordi Llopis-Lorente
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | - Beatriz Trenor
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | - Javier Saiz
- Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, Valencia, Spain
| | - Manuel Pastor
- Research Programme on Biomedical Informatics (GRIB), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Hospital del Mar Research Institute, Barcelona, Spain.
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Demeester C, Robins D, Edwina AE, Tournoy J, Augustijns P, Ince I, Lehmann A, Vertzoni M, Schlender JF. Physiologically based pharmacokinetic (PBPK) modelling of oral drug absorption in older adults - an AGePOP review. Eur J Pharm Sci 2023; 188:106496. [PMID: 37329924 DOI: 10.1016/j.ejps.2023.106496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 06/06/2023] [Accepted: 06/14/2023] [Indexed: 06/19/2023]
Abstract
The older population consisting of persons aged 65 years or older is the fastest-growing population group and also the major consumer of pharmaceutical products. Due to the heterogenous ageing process, this age group shows high interindividual variability in the dose-exposure-response relationship and, thus, a prediction of drug safety and efficacy is challenging. Although physiologically based pharmacokinetic (PBPK) modelling is a well-established tool to inform and confirm drug dosing strategies during drug development for special population groups, age-related changes in absorption are poorly accounted for in current PBPK models. The purpose of this review is to summarise the current state-of-knowledge in terms of physiological changes with increasing age that can influence the oral absorption of dosage forms. The capacity of common PBPK platforms to incorporate these changes and describe the older population is also discussed, as well as the implications of extrinsic factors such as drug-drug interactions associated with polypharmacy on the model development process. The future potential of this field will rely on addressing the gaps identified in this article, which can subsequently supplement in-vitro and in-vivo data for more robust decision-making on the adequacy of the formulation for use in older adults and inform pharmacotherapy.
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Affiliation(s)
- Cleo Demeester
- Systems Pharmacology & Medicine, Pharmaceuticals, Bayer AG, Leverkusen 51373, Germany; Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Gasthuisberg O&N II, Leuven, Belgium
| | - Donnia Robins
- Global CMC Development, Merck KGaA, Frankfurter Straße 250, Darmstadt, Germany; Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Zografou, Greece
| | - Angela Elma Edwina
- Gerontology and Geriatrics Unit, Department of Public Health and Primary care, KU Leuven - University of Leuven, Leuven, Belgium
| | - Jos Tournoy
- Gerontology and Geriatrics Unit, Department of Public Health and Primary care, KU Leuven - University of Leuven, Leuven, Belgium; Department of Geriatric Medicine, University Hospitals Leuven, Leuven, Belgium
| | - Patrick Augustijns
- Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Gasthuisberg O&N II, Leuven, Belgium
| | - Ibrahim Ince
- Systems Pharmacology & Medicine, Pharmaceuticals, Bayer AG, Leverkusen 51373, Germany
| | - Andreas Lehmann
- Global CMC Development, Merck KGaA, Frankfurter Straße 250, Darmstadt, Germany
| | - Maria Vertzoni
- Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, Zografou, Greece
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Van der Veken M, Brouwers J, Ozbey AC, Umehara K, Stillhart C, Knops N, Augustijns P, Parrott NJ. Investigating Tacrolimus Disposition in Paediatric Patients with a Physiologically Based Pharmacokinetic Model Incorporating CYP3A4 Ontogeny, Mechanistic Absorption and Red Blood Cell Binding. Pharmaceutics 2023; 15:2231. [PMID: 37765200 PMCID: PMC10536648 DOI: 10.3390/pharmaceutics15092231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 08/06/2023] [Accepted: 08/22/2023] [Indexed: 09/29/2023] Open
Abstract
Tacrolimus is a crucial immunosuppressant for organ transplant patients, requiring therapeutic drug monitoring due to its variable exposure after oral intake. Physiologically based pharmacokinetic (PBPK) modelling has provided insights into tacrolimus disposition in adults but has limited application in paediatrics. This study investigated age dependency in tacrolimus exposure at the levels of absorption, metabolism, and distribution. Based on the literature data, a PBPK model was developed to predict tacrolimus exposure in adults after intravenous and oral administration. This model was then extrapolated to the paediatric population, using a unique reference dataset of kidney transplant patients. Selecting adequate ontogeny profiles for hepatic and intestinal CYP3A4 appeared critical to using the model in children. The best model performance was achieved by using the Upreti ontogeny in both the liver and intestines. To mechanistically evaluate the impact of absorption on tacrolimus exposure, biorelevant in vitro solubility and dissolution data were obtained. A relatively fast and complete release of tacrolimus from its amorphous formulation was observed when mimicking adult or paediatric dissolution conditions (dose, fluid volume). In both the adult and paediatric PBPK models, the in vitro dissolution profiles could be adequately substituted by diffusion-layer-based dissolution modelling. At the level of distribution, sensitivity analysis suggested that differences in blood plasma partitioning of tacrolimus may contribute to the variability in exposure in paediatric patients.
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Affiliation(s)
- Matthias Van der Veken
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium; (M.V.d.V.); (J.B.); (P.A.)
| | - Joachim Brouwers
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium; (M.V.d.V.); (J.B.); (P.A.)
| | - Agustos Cetin Ozbey
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, 4070 Basel, Switzerland; (A.C.O.); (K.U.)
| | - Kenichi Umehara
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, 4070 Basel, Switzerland; (A.C.O.); (K.U.)
| | - Cordula Stillhart
- Pharmaceutical R&D, F. Hoffmann-La Roche Ltd., 4070 Basel, Switzerland;
| | - Noël Knops
- Laboratory for Pediatrics, Department of Development & Regeneration, KU Leuven, O&N3, Bus 817, 3000 Leuven, Belgium;
- Department of Pediatrics, Groene Hart Ziekenhuis, 2803 Gouda, The Netherlands
| | - Patrick Augustijns
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium; (M.V.d.V.); (J.B.); (P.A.)
| | - Neil John Parrott
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, 4070 Basel, Switzerland; (A.C.O.); (K.U.)
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Kumar P, Mehta D, Bissler JJ. Physiologically Based Pharmacokinetic Modeling of Extracellular Vesicles. Biology (Basel) 2023; 12:1178. [PMID: 37759578 PMCID: PMC10525702 DOI: 10.3390/biology12091178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 08/13/2023] [Accepted: 08/22/2023] [Indexed: 09/29/2023]
Abstract
Extracellular vesicles (EVs) are lipid membrane bound-cell-derived structures that are a key player in intercellular communication and facilitate numerous cellular functions such as tumor growth, metastasis, immunosuppression, and angiogenesis. They can be used as a drug delivery platform because they can protect drugs from degradation and target specific cells or tissues. With the advancement in the technologies and methods in EV research, EV-therapeutics are one of the fast-growing domains in the human health sector. Therapeutic translation of EVs in clinics requires assessing the quality, safety, and efficacy of the EVs, in which pharmacokinetics is very crucial. We report here the application of physiologically based pharmacokinetic (PBPK) modeling as a principal tool for the prediction of absorption, distribution, metabolism, and excretion of EVs. To create a PBPK model of EVs, researchers would need to gather data on the size, shape, and composition of the EVs, as well as the physiological processes that affect their behavior in the body. The PBPK model would then be used to predict the pharmacokinetics of drugs delivered via EVs, such as the rate at which the drug is absorbed and distributed throughout the body, the rate at which it is metabolized and eliminated, and the maximum concentration of the drug in the body. This information can be used to optimize the design of EV-based drug delivery systems, including the size and composition of the EVs, the route of administration, and the dose of the drug. There has not been any dedicated review article that describes the PBPK modeling of EV. This review provides an overview of the absorption, distribution, metabolism, and excretion (ADME) phenomena of EVs. In addition, we will briefly describe the different computer-based modeling approaches that may help in the future of EV-based therapeutic research.
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Affiliation(s)
- Prashant Kumar
- Division of Biochemical Toxicology, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, AR 72079, USA;
| | - Darshan Mehta
- Division of Biochemical Toxicology, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, AR 72079, USA;
| | - John J. Bissler
- Department of Pediatrics, Division of Pediatrics Nephrology, University of Tennessee Health Science Center, Memphis, TN 38103, USA;
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Dabke A, Ghosh S, Dabke P, Sawant K, Khopade A. Revisiting the in-vitro and in-vivo considerations for in-silico modelling of complex injectable drug products. J Control Release 2023; 360:185-211. [PMID: 37353161 DOI: 10.1016/j.jconrel.2023.06.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 05/24/2023] [Accepted: 06/19/2023] [Indexed: 06/25/2023]
Abstract
Complex injectable drug products (CIDPs) have often been developed to modulate the pharmacokinetics along with efficacy for therapeutic agents used for remediation of chronic disorders. The effective development of CIDPs has exhibited complex kinetics associated with multiphasic drug release from the prepared formulations. Consequently, predictability of pharmacokinetic modelling for such CIDPs has been difficult and there is need for advanced complex computational models for the establishment of accurate prediction models for in-vitro-in-vivo correlation (IVIVC). The computational modelling aims at supplementing the existing knowledge with mathematical equations to develop formulation strategies for generation of predictable and discriminatory IVIVC. Such an approach would help in reduction of the burden of effect of hidden factors on preclinical to clinical translations. Computational tools like physiologically based pharmacokinetics (PBPK) modelling have combined physicochemical and physiological properties along with IVIVC characteristics of clinically used formulations. Such techniques have helped in prediction and understanding of variability in pharmacodynamic parameters of potential generic products to clinically used formulations like Doxil®, Ambisome®, Abraxane® in healthy and diseased population using mathematical equations. The current review highlights the important formulation characteristics, in-vitro, preclinical in-vivo aspects which need to be considered while developing a stimulatory predictive PBPK model in establishment of an IVIVC and in-vitro-in-vivo relationship (IVIVR).
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Affiliation(s)
- Amit Dabke
- Faculty of Pharmacy, Kalabhavan Campus, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat 390001, India; Formulation Research & Development- Biopharmaceutics, Sun Pharmaceutical Industries Ltd, Vadodara, Gujarat 390012, India
| | - Saikat Ghosh
- Faculty of Pharmacy, Kalabhavan Campus, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat 390001, India
| | - Pallavi Dabke
- Faculty of Pharmacy, Kalabhavan Campus, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat 390001, India
| | - Krutika Sawant
- Faculty of Pharmacy, Kalabhavan Campus, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat 390001, India.
| | - Ajay Khopade
- Faculty of Pharmacy, Kalabhavan Campus, The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat 390001, India; Formulation Research & Development- Novel Drug Delivery Systems, Sun Pharmaceutical Industries Ltd, Vadodara, Gujarat 390012, India.
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Alasmari F, Alasmari MS, Muwainea HM, Alomar HA, Alasmari AF, Alsanea S, Alshamsan A, Rasool MF, Alqahtani F. Physiologically-based pharmacokinetic modeling for single and multiple dosing regimens of ceftriaxone in healthy and chronic kidney disease populations: a tool for model-informed precision dosing. Front Pharmacol 2023; 14:1200828. [PMID: 37547336 PMCID: PMC10398570 DOI: 10.3389/fphar.2023.1200828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 07/04/2023] [Indexed: 08/08/2023] Open
Abstract
Introduction: Ceftriaxone is one of commonly prescribed beta-lactam antibiotics with several label and off-label clinical indications. A high fraction of administered dose of ceftriaxone is excreted renally in an unchanged form, and it may accumulate significantly in patients with impaired renal functions, which may lead to toxicity. Methods: In this study, we employed a physiologically-based pharmacokinetic (PBPK) modeling, as a tool for precision dosing, to predict the biological exposure of ceftriaxone in a virtually-constructed healthy and chronic kidney disease patient populations, with subsequent dosing optimizations. We started developing the model by integrating the physicochemical properties of the drug with biological system information in a PBPK software platform. A PBPK model in an adult healthy population was developed and evaluated visually and numerically with respect to experimental pharmacokinetic data. The model performance was evaluated based on the fold error criteria of the predicted and reported values for different pharmacokinetic parameters. Then, the model was applied to predict drug exposure in CKD patient populations with various degrees of severity. Results: The developed PBPK model was able to precisely describe the pharmacokinetic behavior of ceftriaxone in adult healthy population and in mild, moderate, and severe CKD patient populations. Decreasing the dose by approximately 25% in mild and 50% in moderate to severe renal disease provided a comparable exposure to the healthy population. Based on the simulation of multiple dosing regimens in severe CKD population, it has been found that accumulation of 2 g every 24 h is lower than the accumulation of 1 g every 12 h dosing regimen. Discussion: In this study, the observed concentration time profiles and pharmacokinetic parameters for ceftriaxone were successfully reproduced by the developed PBPK model and it has been shown that PBPK modeling can be used as a tool for precision dosing to suggest treatment regimens in population with renal impairment.
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Affiliation(s)
- Fawaz Alasmari
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Mohammed S. Alasmari
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Hussa Mubarak Muwainea
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Hatun A. Alomar
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Abdullah F. Alasmari
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Sary Alsanea
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Aws Alshamsan
- Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Muhammad F. Rasool
- Department of Pharmacy Practice, Faculty of Pharmacy, Bahauddin Zakariya University, Multan, Pakistan
| | - Faleh Alqahtani
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
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Karnati P, Murthy A, Gundeti M, Ahmed T. Modelling Based Approaches to Support Generic Drug Regulatory Submissions-Practical Considerations and Case Studies. AAPS J 2023; 25:63. [PMID: 37353655 DOI: 10.1208/s12248-023-00831-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 06/03/2023] [Indexed: 06/25/2023] Open
Abstract
Model informed drug development (MiDD) is useful to predict in vivo exposure of drugs during various stages of the drug development process. This approach employs a variety of quantitative tools to assess the risks during the drug development process. One important tool in the MiDD tool kit is the Physiologically Based Pharmacokinetic Modelling (PBPK). This tool is extensively used to reduce the development cost and to accelerate the access of medicines to the patients. In this work, we provide an overview of PBPK modelling approaches in the generic drug development process, with a special emphasis on the bio-waiver applications. We describe herein approaches and common pitfalls while submitting model based justifications as a response to the regulatory deficiencies during the generic drug development process. With some in-house case studies, we have attempted to provide a clear path for PBPK model based justifications for bio-waivers. With this review, the gap between theoretical knowledge and practical application of modelling and simulation tools for generic drug product development could be potentially reduced.
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Affiliation(s)
- Prajwala Karnati
- Biopharmaceutics Department, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Hyderabad, India
| | - Aditya Murthy
- Biopharmaceutics Department, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Hyderabad, India
| | - Manoj Gundeti
- Biopharmaceutics Department, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Hyderabad, India
| | - Tausif Ahmed
- Biopharmaceutics Department, Global Clinical Management, Dr. Reddy's Laboratories Ltd., Hyderabad, India.
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Nauwelaerts N, Macente J, Deferm N, Bonan RH, Huang MC, Van Neste M, Bibi D, Badee J, Martins FS, Smits A, Allegaert K, Bouillon T, Annaert P. Generic Workflow to Predict Medicine Concentrations in Human Milk Using Physiologically-Based Pharmacokinetic (PBPK) Modelling-A Contribution from the ConcePTION Project. Pharmaceutics 2023; 15:pharmaceutics15051469. [PMID: 37242712 DOI: 10.3390/pharmaceutics15051469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 04/28/2023] [Accepted: 05/03/2023] [Indexed: 05/28/2023] Open
Abstract
Women commonly take medication during lactation. Currently, there is little information about the exposure-related safety of maternal medicines for breastfed infants. The aim was to explore the performance of a generic physiologically-based pharmacokinetic (PBPK) model to predict concentrations in human milk for ten physiochemically diverse medicines. First, PBPK models were developed for "non-lactating" adult individuals in PK-Sim/MoBi v9.1 (Open Systems Pharmacology). The PBPK models predicted the area-under-the-curve (AUC) and maximum concentrations (Cmax) in plasma within a two-fold error. Next, the PBPK models were extended to include lactation physiology. Plasma and human milk concentrations were simulated for a three-months postpartum population, and the corresponding AUC-based milk-to-plasma (M/P) ratios and relative infant doses were calculated. The lactation PBPK models resulted in reasonable predictions for eight medicines, while an overprediction of human milk concentrations and M/P ratios (>2-fold) was observed for two medicines. From a safety perspective, none of the models resulted in underpredictions of observed human milk concentrations. The present effort resulted in a generic workflow to predict medicine concentrations in human milk. This generic PBPK model represents an important step towards an evidence-based safety assessment of maternal medication during lactation, applicable in an early drug development stage.
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Affiliation(s)
- Nina Nauwelaerts
- Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Julia Macente
- Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Neel Deferm
- Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
- Simcyp Division, Certara UK Ltd., Sheffield S1 2BJ, UK
| | | | - Miao-Chan Huang
- Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Martje Van Neste
- Clinical Pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
| | - David Bibi
- Global Research and Development, Teva Pharmaceutical Industries Ltd., Netanya 42504, Israel
| | - Justine Badee
- Novartis Institutes for BioMedical Research, Novartis, CH-4056 Basel, Switzerland
| | - Frederico S Martins
- Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
| | - Anne Smits
- Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium
- L-C&Y, KU Leuven Child & Youth Institute, 3000 Leuven, Belgium
- Neonatal Intensive Care Unit, University Hospitals Leuven, 3000 Leuven, Belgium
| | - Karel Allegaert
- Clinical Pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
- Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium
- L-C&Y, KU Leuven Child & Youth Institute, 3000 Leuven, Belgium
- Department of Hospital Pharmacy, Erasmus University Medical Center, 3000 CA Rotterdam, The Netherlands
| | | | - Pieter Annaert
- Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium
- BioNotus GCV, 2845 Niel, Belgium
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Hummler H, Sarwinska D, Weitschies W, Gollasch M, Page S. Parameters to Consider for Successful Medication Use in Older Adults - an AGePOP Review. Eur J Pharm Sci 2023:106453. [PMID: 37149104 DOI: 10.1016/j.ejps.2023.106453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 03/27/2023] [Accepted: 04/24/2023] [Indexed: 05/08/2023]
Abstract
Older adults are the main users of medicine and due to their multimorbidity are often faced/confronted with a complex medication management. This review article provides a brief overview on aspects of medication management such as maintaining a stock of the required medicine, understanding and following the instructions for use, coping with the primary and secondary packaging as well as preparation prior to use. The main focus however is on the drug intake itself and provides an overview about the current understanding of real life dosing conditions of older adults and geriatric patients. Furthermore, it elaborates the acceptability of dosage forms, in particular solid oral dosage forms as they represent the majority of dosage forms taken by these patient populations. An improved understanding of the needs of older adults and geriatric patients, their acceptability of various dosage forms and the circumstances under which they manage their medications, will make the design of more patient-centric drug products possible.
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Affiliation(s)
- Henriette Hummler
- Pharma Technical Development, F. Hoffmann-La Roche Ltd., Grenzacher Str. 124, CH-4070, Basel, Switzerland
| | - Dorota Sarwinska
- Center of Drug Absorption and Transport, Department of Biopharmaceutics and Pharmaceutical Technology, Institute of Pharmacy, University of Greifswald, Felix-Hausdorff-Str. 3, 17489, Greifswald, Germany
| | - Werner Weitschies
- Center of Drug Absorption and Transport, Department of Biopharmaceutics and Pharmaceutical Technology, Institute of Pharmacy, University of Greifswald, Felix-Hausdorff-Str. 3, 17489, Greifswald, Germany
| | - Maik Gollasch
- Department of Internal Medicine and Geriatrics, University Medicine Greifswald, Ferdinand-Sauerbruch-Straße, 17475, Greifswald, Germany
| | - Susanne Page
- Pharma Technical Development, F. Hoffmann-La Roche Ltd., Grenzacher Str. 124, CH-4070, Basel, Switzerland.
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Rajput AJ, Aldibani HKA, Rostami-Hodjegan A. In-depth analysis of patterns in selection of different physiologically based pharmacokinetic modeling tools: PartI - Applications and rationale behind the use of open source-code software. Biopharm Drug Dispos 2023. [PMID: 37083200 DOI: 10.1002/bdd.2357] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 03/29/2023] [Accepted: 04/04/2023] [Indexed: 04/22/2023]
Abstract
PBPK applications published in the literature support a greater adoption of non-open source-code (NOSC) software as opposed to open source-code (OSC) alternatives. However, a significant number of PBPK modelers are still using OSC software, understanding the rationale for the use of this modality is important and may help those embarking on PBPK modeling. No previous analysis of PBPK modeling trends has included the rationale of the modeler. An in-depth analysis of PBPK applications of OSC software is warranted to determine the true impact of OSC software on the rise of PBPK. Publications focussing on PBPK modeling applications, which used OSC software, were identified by systematically searching the scientific literature for original articles. A total of 171 articles were extracted from the narrowed subset. The rise in the use of OSC software for PBPK applications was greater than the general discipline of pharmacokinetics (9 vs. 4), but less than the overall growth of the PBPK area (9 vs. 43). Our report demonstrates conclusively that the surge in PBPK usage is primarily attributable to the availability and implementations of NOSC software. Modelers preferred not to share the reasons for their selection of certain modeling software and no 'explicit' rationale was given to support the use of OSC analysed by this study. As the preference for NOSC versus OSC software tools in the PBPK area continues to be divided, initiatives to add the rationale in using one form over another to every future PBPK modeling report will be a welcomed and informative addition.
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Affiliation(s)
- Arham Jamaal Rajput
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | | | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
- Certara UK Limited, Sheffield, UK
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Khalid K, Rox K. All Roads Lead to Rome: Enhancing the Probability of Target Attainment with Different Pharmacokinetic/Pharmacodynamic Modelling Approaches. Antibiotics (Basel) 2023; 12:antibiotics12040690. [PMID: 37107052 PMCID: PMC10135278 DOI: 10.3390/antibiotics12040690] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 03/29/2023] [Accepted: 03/30/2023] [Indexed: 04/05/2023] Open
Abstract
In light of rising antimicrobial resistance and a decreasing number of antibiotics with novel modes of action, it is of utmost importance to accelerate development of novel treatment options. One aspect of acceleration is to understand pharmacokinetics (PK) and pharmacodynamics (PD) of drugs and to assess the probability of target attainment (PTA). Several in vitro and in vivo methods are deployed to determine these parameters, such as time-kill-curves, hollow-fiber infection models or animal models. However, to date the use of in silico methods to predict PK/PD and PTA is increasing. Since there is not just one way to perform the in silico analysis, we embarked on reviewing for which indications and how PK and PK/PD models as well as PTA analysis has been used to contribute to the understanding of the PK and PD of a drug. Therefore, we examined four recent examples in more detail, namely ceftazidime-avibactam, omadacycline, gepotidacin and zoliflodacin as well as cefiderocol. Whereas the first two compound classes mainly relied on the ‘classical’ development path and PK/PD was only deployed after approval, cefiderocol highly profited from in silico techniques that led to its approval. Finally, this review shall highlight current developments and possibilities to accelerate drug development, especially for anti-infectives.
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Affiliation(s)
- Kashaf Khalid
- Department of Chemical Biology, Helmholtz Centre for Infection Research (HZI), Inhoffenstraße 7, 38124 Braunschweig, Germany
| | - Katharina Rox
- Department of Chemical Biology, Helmholtz Centre for Infection Research (HZI), Inhoffenstraße 7, 38124 Braunschweig, Germany
- German Center for Infection Research (DZIF), Partner Site Hannover-Braunschweig, 38124 Braunschweig, Germany
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Singh AV, Varma M, Laux P, Choudhary S, Datusalia AK, Gupta N, Luch A, Gandhi A, Kulkarni P, Nath B. Artificial intelligence and machine learning disciplines with the potential to improve the nanotoxicology and nanomedicine fields: a comprehensive review. Arch Toxicol 2023; 97:963-979. [PMID: 36878992 PMCID: PMC10025217 DOI: 10.1007/s00204-023-03471-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 02/20/2023] [Indexed: 03/08/2023]
Abstract
The use of nanomaterials in medicine depends largely on nanotoxicological evaluation in order to ensure safe application on living organisms. Artificial intelligence (AI) and machine learning (MI) can be used to analyze and interpret large amounts of data in the field of toxicology, such as data from toxicological databases and high-content image-based screening data. Physiologically based pharmacokinetic (PBPK) models and nano-quantitative structure-activity relationship (QSAR) models can be used to predict the behavior and toxic effects of nanomaterials, respectively. PBPK and Nano-QSAR are prominent ML tool for harmful event analysis that is used to understand the mechanisms by which chemical compounds can cause toxic effects, while toxicogenomics is the study of the genetic basis of toxic responses in living organisms. Despite the potential of these methods, there are still many challenges and uncertainties that need to be addressed in the field. In this review, we provide an overview of artificial intelligence (AI) and machine learning (ML) techniques in nanomedicine and nanotoxicology to better understand the potential toxic effects of these materials at the nanoscale.
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Affiliation(s)
- Ajay Vikram Singh
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Straße 8-10, 10589, Berlin, Germany.
| | - Mansi Varma
- Department of Regulatory Toxicology, National Institute of Pharmaceutical Education and Research (NIPER-Raebareli), Lucknow, 229001, India
| | - Peter Laux
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Straße 8-10, 10589, Berlin, Germany
| | - Sunil Choudhary
- Department of Radiotherapy and Radiation Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, 221005, India
| | - Ashok Kumar Datusalia
- Department of Regulatory Toxicology, National Institute of Pharmaceutical Education and Research (NIPER-Raebareli), Lucknow, 229001, India
| | - Neha Gupta
- Department of Radiation Oncology, Apex Hospital, Varanasi, 221005, India
| | - Andreas Luch
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Straße 8-10, 10589, Berlin, Germany
| | - Anusha Gandhi
- Elisabeth-Selbert-Gymnasium, Tübinger Str. 71, 70794, Filderstadt, Germany
| | - Pranav Kulkarni
- Seeta Nursing Home, Shivaji Nagar, Nashik, Maharashtra, 422002, India
| | - Banashree Nath
- Department of Obstetrics and Gynaecology, All India Institute of Medical Sciences, Raebareli, Uttar Pradesh, 229405, India
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Korzekwa K, Nagar S. Process and System Clearances in Pharmacokinetic Models: Our Basic Clearance Concepts Are Correct. Drug Metab Dispos 2023; 51:532-542. [PMID: 36623886 PMCID: PMC10043942 DOI: 10.1124/dmd.122.001060] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 12/07/2022] [Accepted: 12/15/2022] [Indexed: 01/11/2023] Open
Abstract
Clearances are important parameters in pharmacokinetic (PK) models. All clearances in PK models are either process clearances that include diffusion, transport, and metabolism clearances or system clearances that include organ and systemic clearance. Clearance and volume of distribution are two independent parameters that characterize drug disposition in both individual compartments and systems of compartments. In this minireview, we show that systemic and organ clearances are net clearances that can be easily derived by partition analysis. When drugs are eliminated from the central compartment by first-order processes, systemic clearance is constant. When drugs are eliminated from a peripheral compartment, instantaneous systemic clearance will vary with time. However, average clearance and clearance at steady state will be constant and will equal dose divided by area under the curve. We show that peripheral elimination will not have a large impact on most pharmacokinetic analyses and that standard models of organ and systemic clearance are useful and appropriate. SIGNIFICANCE STATEMENT: There are two basic kinds of clearances used in pharmacokinetic models, process and system clearances. We show that organ and systemic clearances are net clearances with blood or plasma as the driving concentration. For linear pharmacokinetics, clearance is constant for elimination from the central compartment but varies with time for peripheral elimination. Despite the different kinds of clearance parameters and models, standard clearance models and concepts remain valid.
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Affiliation(s)
- Ken Korzekwa
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, Pennsylvania
| | - Swati Nagar
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, Pennsylvania
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Maass C, Schaller S, Dallmann A, Bothe K, Müller D. Considering developmental neurotoxicity in vitro data for human health risk assessment using physiologically-based kinetic modeling: deltamethrin case study. Toxicol Sci 2023; 192:59-70. [PMID: 36637193 PMCID: PMC10025876 DOI: 10.1093/toxsci/kfad007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
Developmental neurotoxicity (DNT) is a potential hazard of chemicals. Recently, an in vitro testing battery (DNT IVB) was established to complement existing rodent in vivo approaches. Deltamethrin (DLT), a pyrethroid with a well-characterized neurotoxic mode of action, has been selected as a reference chemical to evaluate the performance of the DNT IVB. The present study provides context for evaluating the relevance of these DNT IVB results for the human health risk assessment of DLT by estimating potential human fetal brain concentrations after maternal exposure to DLT. We developed a physiologically based kinetic (PBK) model for rats which was then translated to humans considering realistic in vivo exposure conditions (acceptable daily intake [ADI] for DLT). To address existing uncertainties, we designed case studies considering the most relevant drivers of DLT uptake and distribution. Calculated human fetal brain concentrations were then compared with the lowest benchmark concentration achieved in the DNT IVB. The developed rat PBK model was validated on in vivo rat toxicokinetic data of DLT over a broad range of doses. The uncertainty based case study evaluation confirmed that repeated exposure to DLT at an ADI level would likely result in human fetal brain concentrations far below the in vitro benchmark. The presented results indicate that DLT concentrations in the human fetal brain are highly unlikely to reach concentrations associated with in vitro findings under realistic exposure conditions. Therefore, the new in vitro DNT results are considered to have no impact on the current risk assessment approach.
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Affiliation(s)
| | | | - André Dallmann
- Pharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen 51373, Germany
| | - Kathrin Bothe
- Regulatory Toxicology, Research and Development, Bayer AG, CropScience, 40789 Monheim am Rhein, Germany
| | - Dennis Müller
- Regulatory Toxicology, Research and Development, Bayer AG, CropScience, 40789 Monheim am Rhein, Germany
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Macente J, Nauwelaerts N, Russo FM, Deprest J, Allegaert K, Lammens B, Hernandes Bonan R, Turner JM, Kumar S, Diniz A, Martins FS, Annaert P. PBPK-based dose finding for sildenafil in pregnant women for antenatal treatment of congenital diaphragmatic hernia. Front Pharmacol 2023; 14:1068153. [PMID: 36998614 PMCID: PMC10043195 DOI: 10.3389/fphar.2023.1068153] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 02/20/2023] [Indexed: 03/17/2023] Open
Abstract
Sildenafil is a potent vasodilator and phosphodiesterase type five inhibitor, commercially known as Revatio® and approved for the treatment of pulmonary arterial hypertension. Maternal administration of sildenafil during pregnancy is being evaluated for antenatal treatment of several conditions, including the prevention of pulmonary hypertension in fetuses with congenital diaphragmatic hernia. However, determination of a safe and effective maternal dose to achieve adequate fetal exposure to sildenafil remains challenging, as pregnancy almost always is an exclusion criterion in clinical studies. Physiologically-based pharmacokinetic (PBPK) modelling offers an attractive approach for dose finding in this specific population. The aim of this study is to exploit physiologically-based pharmacokinetic modelling to predict the required maternal dose to achieve therapeutic fetal exposure for the treatment congenital diaphragmatic hernia. A full-PBPK model was developed for sildenafil and N-desmethyl-sildenafil using the Simcyp simulator V21 platform, and verified in adult reference individuals, as well as in pregnant women, taking into account maternal and fetal physiology, along with factors known to determine hepatic disposition of sildenafil. Clinical pharmacokinetic data in mother and fetus were previously obtained in the RIDSTRESS study and were used for model verification purposes. Subsequent simulations were performed relying either on measured values for fetal fraction unbound (fu = 0.108) or on values predicted by the simulator (fu = 0.044). Adequate doses were predicted according to the efficacy target of 15 ng/mL (or 38 ng/mL) and safety target of 166 ng/mL (or 409 ng/mL), assuming measured (or predicted) fu values, respectively. Considering simulated median profiles for average steady state sildenafil concentrations, dosing regimens of 130 mg/day or 150 mg/day (administered as t.i.d.), were within the therapeutic window, assuming either measured or predicted fu values, respectively. For safety reasons, dosing should be initiated at 130 mg/day, under therapeutic drug monitoring. Additional experimental measurements should be performed to confirm accurate fetal (and maternal) values for fu. Additional characterization of pharmacodynamics in this specific population is required and may lead to further optimization of the dosing regimen.
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Affiliation(s)
- Julia Macente
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - Nina Nauwelaerts
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | | | - Jan Deprest
- Gynecology and Obstetrics, UZ Leuven, Leuven, Belgium
| | - Karel Allegaert
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium
- Department of Clinical Pharmacy, Erasmus MC, Rotterdam, Netherlands
| | | | | | - Jessica M. Turner
- Mater Research Institute, University of Queensland, Brisbane, QLD, Australia
| | - Sailesh Kumar
- Mater Research Institute, University of Queensland, Brisbane, QLD, Australia
| | - Andrea Diniz
- Pharmacokinetics and Biopharmaceutical Laboratory (PKBio), Department of Pharmacy, State University of Maringa, Maringa, Brazil
| | - Frederico S. Martins
- Pharmacokinetics and Biopharmaceutical Laboratory (PKBio), Department of Pharmacy, State University of Maringa, Maringa, Brazil
| | - Pieter Annaert
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
- BioNotus GCV, Niel, Belgium
- *Correspondence: Pieter Annaert,
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Sharma S, Singh DK, Mettu VS, Yue G, Ahire D, Basit A, Heyward S, Prasad B. Quantitative Characterization of Clinically Relevant Drug-Metabolizing Enzymes and Transporters in Rat Liver and Intestinal Segments for Applications in PBPK Modeling. Mol Pharm 2023; 20:1737-1749. [PMID: 36791335 DOI: 10.1021/acs.molpharmaceut.2c00950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Rats are extensively used as a preclinical model for assessing drug pharmacokinetics (PK) and tissue distribution; however, successful translation of the rat data requires information on the differences in drug metabolism and transport mechanisms between rats and humans. To partly fill this knowledge gap, we quantified clinically relevant drug-metabolizing enzymes and transporters (DMETs) in the liver and different intestinal segments of Sprague-Dawley rats. The levels of DMET proteins in rats were quantified using the global proteomics-based total protein approach (TPA) and targeted proteomics. The abundance of the major DMET proteins was largely comparable using quantitative global and targeted proteomics. However, global proteomics-based TPA was able to detect and quantify a comprehensive list of 66 DMET proteins in the liver and 37 DMET proteins in the intestinal segments of SD rats without the need for peptide standards. Cytochrome P450 (Cyp) and UDP-glycosyltransferase (Ugt) enzymes were mainly detected in the liver with the abundance ranging from 8 to 6502 and 74 to 2558 pmol/g tissue. P-gp abundance was higher in the intestine (124.1 pmol/g) as compared to that in the liver (26.6 pmol/g) using the targeted analysis. Breast cancer resistance protein (Bcrp) was most abundant in the intestinal segments, whereas organic anion transporting polypeptides (Oatp) 1a1, 1a4, 1b2, and 2a1 and multidrug resistance proteins (Mrp) 2 and 6 were predominantly detected in the liver. To demonstrate the utility of these data, we modeled digoxin PK by integrating protein abundance of P-gp and Cyp3a2 into a physiologically based PK (PBPK) model constructed using PK-Sim software. The model was able to reliably predict the systemic as well as tissue concentrations of digoxin in rats. These findings suggest that proteomics-informed PBPK models in preclinical species can allow mechanistic PK predictions in animal models including tissue drug concentrations.
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Affiliation(s)
- Sheena Sharma
- College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington 99202, United States
| | - Dilip K Singh
- College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington 99202, United States
| | - Vijay S Mettu
- College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington 99202, United States
| | - Guihua Yue
- College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington 99202, United States
| | - Deepak Ahire
- College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington 99202, United States
| | - Abdul Basit
- College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington 99202, United States
| | | | - Bhagwat Prasad
- College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington 99202, United States
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44
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Cordes H, Rapp H. Gene expression databases for physiologically based pharmacokinetic modeling of humans and animal species. CPT Pharmacometrics Syst Pharmacol 2023; 12:311-319. [PMID: 36715173 PMCID: PMC10014062 DOI: 10.1002/psp4.12904] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 12/05/2022] [Accepted: 12/08/2022] [Indexed: 01/31/2023] Open
Abstract
In drug research, developing a sound understanding of the key mechanistic drivers of pharmacokinetics (PK) for new molecular entities is essential for human PK and dose predictions. Here, characterizing the absorption, distribution, metabolism, and excretion (ADME) processes is crucial for a mechanistic understanding of the drug-target and drug-body interactions. Sufficient knowledge on ADME processes enables reliable interspecies and human PK estimations beyond allometric scaling. The physiologically based PK (PBPK) modeling framework allows the explicit consideration of organ-specific ADME processes. The sum of all passive and active ADME processes results in the observed plasma PK. Gene expression information can be used as surrogate for protein abundance and activity within PBPK models. The absolute and relative expression of ADME genes can differ between species and strains. This is affecting both, the PK and pharmacodynamics and is therefore posing a challenge for the extrapolation from preclinical findings to humans. We developed an automated workflow that generates whole-body gene expression databases for humans and other species relevant in drug development, animal health, nutritional sciences, and toxicology. Solely, bulk RNA-seq data curated and provided by the Swiss Institute of Bioinformatics from healthy, normal, and untreated primary tissue samples were considered as an unbiased reference of normal gene expression. The databases are interoperable with the Open Systems Pharmacology Suite (PK-Sim and MoBi) and enable seamless access to a central source of curated cross-species gene expression data. This will increase data transparency, increase reliability and reproducibility of PBPK model simulations, and accelerate mechanistic PBPK model development in the future.
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Affiliation(s)
- Henrik Cordes
- Drug Metabolism & Pharmacokinetics, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt am Main, Germany
| | - Hermann Rapp
- Research Drug Metabolism & Pharmacokinetics, Drug Discovery Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
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45
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Kardynska M, Kogut D, Pacholczyk M, Smieja J. Mathematical modeling of regulatory networks of intracellular processes - Aims and selected methods. Comput Struct Biotechnol J 2023; 21:1523-1532. [PMID: 36851915 PMCID: PMC9958294 DOI: 10.1016/j.csbj.2023.02.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/03/2023] [Accepted: 02/03/2023] [Indexed: 02/11/2023] Open
Abstract
Regulatory networks structure and signaling pathways dynamics are uncovered in time- and resource consuming experimental work. However, it is increasingly supported by modeling, analytical and computational techniques as well as discrete mathematics and artificial intelligence applied to to extract knowledge from existing databases. This review is focused on mathematical modeling used to analyze dynamics and robustness of these networks. This paper presents a review of selected modeling methods that facilitate advances in molecular biology.
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Affiliation(s)
- Malgorzata Kardynska
- Dept. of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Gliwice, Poland
| | - Daria Kogut
- Dept. of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Gliwice, Poland.,Dept. of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
| | - Marcin Pacholczyk
- Dept. of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Gliwice, Poland.,Dept. of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
| | - Jaroslaw Smieja
- Dept. of Biosensors and Processing of Biomedical Signals, Silesian University of Technology, Gliwice, Poland.,Dept. of Systems Biology and Engineering, Silesian University of Technology, Gliwice, Poland
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46
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Kuepfer L, Fuellen G, Stahnke T. Quantitative systems pharmacology of the eye: Tools and data for ocular QSP. CPT Pharmacometrics Syst Pharmacol 2023; 12:288-299. [PMID: 36708082 PMCID: PMC10014063 DOI: 10.1002/psp4.12918] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 12/21/2022] [Accepted: 01/02/2023] [Indexed: 01/29/2023] Open
Abstract
Good eyesight belongs to the most-valued attributes of health, and diseases of the eye are a significant healthcare burden. Case numbers are expected to further increase in the next decades due to an aging society. The development of drugs in ophthalmology, however, is difficult due to limited accessibility of the eye, in terms of drug administration and in terms of sampling of tissues for drug pharmacokinetics (PKs) and pharmacodynamics (PDs). Ocular quantitative systems pharmacology models provide the opportunity to describe the distribution of drugs in the eye as well as the resulting drug-response in specific segments of the eye. In particular, ocular physiologically-based PK (PBPK) models are necessary to describe drug concentration levels in different regions of the eye. Further, ocular effect models using molecular data from specific cellular systems are needed to develop dose-response correlations. We here describe the current status of PK/PBPK as well as PD models for the eyes and discuss cellular systems, data repositories, as well as animal models in ophthalmology. The application of the various concepts is highlighted for the development of new treatments for postoperative fibrosis after glaucoma surgery.
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Affiliation(s)
- Lars Kuepfer
- Institute for Systems Medicine with Focus on Organ Interaction, University Hospital RWTH Aachen, Aachen, Germany
| | - Georg Fuellen
- Institute for Biostatistics and Informatics in Medicine and Aging Research (IBIMA), Rostock University Medical Center, Rostock, Germany
| | - Thomas Stahnke
- Institute for ImplantTechnology and Biomaterials e.V., Rostock, Germany.,Department of Ophthalmology, Rostock University Medical Center, Rostock, Germany
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Kumar M, Kulkarni P, Liu S, Chemuturi N, Shah DK. Nanoparticle biodistribution coefficients: A quantitative approach for understanding the tissue distribution of nanoparticles. Adv Drug Deliv Rev 2023; 194:114708. [PMID: 36682420 DOI: 10.1016/j.addr.2023.114708] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 12/26/2022] [Accepted: 01/17/2023] [Indexed: 01/22/2023]
Abstract
The objective of this manuscript is to provide quantitative insights into the tissue distribution of nanoparticles. Published pharmacokinetics of nanoparticles in plasma, tumor and 13 different tissues of mice were collected from literature. A total of 2018 datasets were analyzed and biodistribution of graphene oxide, lipid, polymeric, silica, iron oxide and gold nanoparticles in different tissues was quantitatively characterized using Nanoparticle Biodistribution Coefficients (NBC). It was observed that typically after intravenous administration most of the nanoparticles are accumulated in the liver (NBC = 17.56 %ID/g) and spleen (NBC = 12.1 %ID/g), while other tissues received less than 5 %ID/g. NBC values for kidney, lungs, heart, bones, brain, stomach, intestine, pancreas, skin, muscle and tumor were found to be 3.1 %ID/g, 2.8 %ID/g, 1.8 %ID/g, 0.9 %ID/g, 0.3 %ID/g, 1.2 %ID/g, 1.8 %ID/g, 1.2 %ID/g, 1.0 %ID/g, 0.6 %ID/g and 3.4 %ID/g, respectively. Significant variability in nanoparticle distribution was observed in certain organs such as liver, spleen and lungs. A large fraction of this variability could be explained by accounting for the differences in nanoparticle physicochemical properties such as size and material. A critical overview of published nanoparticle physiologically-based pharmacokinetic (PBPK) models is provided, and limitations in our current knowledge about in vitro and in vivo pharmacokinetics of nanoparticles that restrict the development of robust PBPK models is also discussed. It is hypothesized that robust quantitative assessment of whole-body pharmacokinetics of nanoparticles and development of mathematical models that can predict their disposition can improve the probability of successful clinical translation of these modalities.
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Affiliation(s)
- Mokshada Kumar
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, The State University of New York at Buffalo, United States
| | - Priyanka Kulkarni
- Drug Metabolism and Pharmacokinetics, R&D, Takeda Pharmaceuticals, Cambridge, MA, United States
| | - Shufang Liu
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, The State University of New York at Buffalo, United States
| | - Nagendra Chemuturi
- Drug Metabolism and Pharmacokinetics, R&D, Takeda Pharmaceuticals, Cambridge, MA, United States.
| | - Dhaval K Shah
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, The State University of New York at Buffalo, United States.
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48
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Dichamp J, Cellière G, Ghallab A, Hassan R, Boissier N, Hofmann U, Reinders J, Sezgin S, Zühlke S, Hengstler JG, Drasdo D. In vitro to in vivo acetaminophen hepatotoxicity extrapolation using classical schemes, pharmacodynamic models and a multiscale spatial-temporal liver twin. Front Bioeng Biotechnol 2023; 11:1049564. [PMID: 36815881 PMCID: PMC9932319 DOI: 10.3389/fbioe.2023.1049564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 01/10/2023] [Indexed: 02/05/2023] Open
Abstract
In vitro to in vivo extrapolation represents a critical challenge in toxicology. In this paper we explore extrapolation strategies for acetaminophen (APAP) based on mechanistic models, comparing classical (CL) homogeneous compartment pharmacodynamic (PD) models and a spatial-temporal (ST), multiscale digital twin model resolving liver microarchitecture at cellular resolution. The models integrate consensus detoxification reactions in each individual hepatocyte. We study the consequences of the two model types on the extrapolation and show in which cases these models perform better than the classical extrapolation strategy that is based either on the maximal drug concentration (Cmax) or the area under the pharmacokinetic curve (AUC) of the drug blood concentration. We find that an CL-model based on a well-mixed blood compartment is sufficient to correctly predict the in vivo toxicity from in vitro data. However, the ST-model that integrates more experimental information requires a change of at least one parameter to obtain the same prediction, indicating that spatial compartmentalization may indeed be an important factor.
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Affiliation(s)
- Jules Dichamp
- Group SIMBIOTX, INRIA Saclay-Île-de-France, Palaiseau, France,Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany,Group MAMBA, INRIA Paris, Paris, France
| | | | - Ahmed Ghallab
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany,Department of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena, Egypt
| | - Reham Hassan
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany,Department of Forensic Medicine and Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena, Egypt
| | - Noemie Boissier
- Group SIMBIOTX, INRIA Saclay-Île-de-France, Palaiseau, France
| | - Ute Hofmann
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology and University of Tübingen, Stuttgart, Germany
| | - Joerg Reinders
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany
| | - Selahaddin Sezgin
- Faculty of Chemistry and Chemical Biology, TU Dortmund, Dortmund, Germany
| | - Sebastian Zühlke
- Center for Mass Spectrometry (CMS), Faculty of Chemistry and Chemical Biology, TU Dortmund University, Dortmund, Germany
| | - Jan G. Hengstler
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany
| | - Dirk Drasdo
- Group SIMBIOTX, INRIA Saclay-Île-de-France, Palaiseau, France,Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, Dortmund, Germany,Group MAMBA, INRIA Paris, Paris, France,*Correspondence: Dirk Drasdo,
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49
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Fairman K, Choi MK, Gonnabathula P, Lumen A, Worth A, Paini A, Li M. An Overview of Physiologically-Based Pharmacokinetic Models for Forensic Science. Toxics 2023; 11:126. [PMID: 36851001 PMCID: PMC9964742 DOI: 10.3390/toxics11020126] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 12/16/2022] [Accepted: 01/25/2023] [Indexed: 06/18/2023]
Abstract
A physiologically-based pharmacokinetic (PBPK) model represents the structural components of the body with physiologically relevant compartments connected via blood flow rates described by mathematical equations to determine drug disposition. PBPK models are used in the pharmaceutical sector for drug development, precision medicine, and the chemical industry to predict safe levels of exposure during the registration of chemical substances. However, one area of application where PBPK models have been scarcely used is forensic science. In this review, we give an overview of PBPK models successfully developed for several illicit drugs and environmental chemicals that could be applied for forensic interpretation, highlighting the gaps, uncertainties, and limitations.
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Affiliation(s)
- Kiara Fairman
- Division of Biochemical Toxicology, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, AR 72079, USA
| | - Me-Kyoung Choi
- Division of Biochemical Toxicology, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, AR 72079, USA
| | - Pavani Gonnabathula
- Division of Biochemical Toxicology, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, AR 72079, USA
| | - Annie Lumen
- Division of Biochemical Toxicology, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, AR 72079, USA
| | - Andrew Worth
- European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy
| | | | - Miao Li
- Division of Biochemical Toxicology, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, AR 72079, USA
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Yang M, Wang AQ, Padilha EC, Shah P, Hagen NR, Ryu C, Shamim K, Huang W, Xu X. Use of physiological based pharmacokinetic modeling for cross-species prediction of pharmacokinetic and tissue distribution profiles of a novel niclosamide prodrug. Front Pharmacol 2023; 14:1099425. [PMID: 37113753 PMCID: PMC10126473 DOI: 10.3389/fphar.2023.1099425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 02/13/2023] [Indexed: 04/29/2023] Open
Abstract
Introduction: Niclosamide (Nc) is an FDA-approved anthelmintic drug that was recently identified in a drug repurposing screening to possess antiviral activity against SARS-CoV-2. However, due to the low solubility and permeability of Nc, its in vivo efficacy was limited by its poor oral absorption. Method: The current study evaluated a novel prodrug of Nc (PDN; NCATS-SM4705) in improving in vivo exposure of Nc and predicted pharmacokinetic profiles of PDN and Nc across different species. ADME properties of the prodrug were determined in humans, hamsters, and mice, while the pharmacokinetics (PK) of PDN were obtained in mice and hamsters. Concentrations of PDN and Nc in plasma and tissue homogenates were measured by UPLC-MS/MS. A physiologically based pharmacokinetic (PBPK) model was developed based on physicochemical properties, pharmacokinetic and tissue distribution data in mice, validated by the PK profiles in hamsters and applied to predict pharmacokinetic profiles in humans. Results: Following intravenous and oral administration of PDN in mice, the total plasma clearance (CLp) and volume of distribution at steady-state (Vdss) were 0.061-0.063 L/h and 0.28-0.31 L, respectively. PDN was converted to Nc in both liver and blood, improving the systemic exposure of Nc in mice and hamsters after oral administration. The PBPK model developed for PDN and in vivo formed Nc could adequately simulate plasma and tissue concentration-time profiles in mice and plasma profiles in hamsters. The predicted human CLp/F and Vdss/F after an oral dose were 2.1 L/h/kg and 15 L/kg for the prodrug respectively. The predicted Nc concentrations in human plasma and lung suggest that a TID dose of 300 mg PDN would provide Nc lung concentrations at 8- to 60-fold higher than in vitro IC50 against SARS-CoV-2 reported in cell assays. Conclusion: In conclusion, the novel prodrug PDN can be efficiently converted to Nc in vivo and improves the systemic exposure of Nc in mice after oral administration. The developed PBPK model adequately depicts the mouse and hamster pharmacokinetic and tissue distribution profiles and highlights its potential application in the prediction of human pharmacokinetic profiles.
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