In-Depth Analysis of the Selection of PBPK Modeling Tools: Bibliometric and Social Network Analysis of the Open Systems Pharmacology Community

Since the Open Source Initiative laid the foundation for the open source software environment in 1998, the popularity of free and open source software has been steadily increasing. Model-informed drug discovery and development (MID3), a key component of pharmaceutical research and development, heavily makes use of computational models which can be developed using various software including the Open Systems Pharmacology (OSP) software (PK-Sim/MoBi), a free and open source software tool for physiologically based pharmacokinetic (PBPK) modeling. In this study, we aimed to investigate the impact, application areas, and reach of the OSP software as well as the relationships and collaboration patterns between organizations having published OSP-related articles between 2017 and 2023. Therefore, we conducted a bibliometric analysis of OSP-related publications and a social network analysis of the organizations with which authors of OSP-related publications were affiliated. On several levels, we found evidence for a significant growth in the size of the OSP community as well as its visibility in the MID3 community since OSP's establishment in 2017. Specifically, the annual publication rate of PubMed-indexed PBPK-related articles using the OSP software outpaced that of PBPK-related articles using any software. Our bibliometric analysis and network analysis demonstrated that the expansion of the OSP community was predominantly driven by new authors and organizations without prior connections to the community involving the generation of research clusters de novo and an overall diversification of the network. These findings suggest an ongoing evolution of the OSP community toward a more segmented, diverse, and inclusive network.

Assessment of the CYP3A4 Induction Potential by Carbamazepine: Insights from Two Clinical DDI Studies and PBPK Modeling

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.

Physiologically Based Pharmacokinetic Modeling in Pregnancy, during Lactation and in Neonates: Achievements, Challenges and Future Directions

Obstetric subjects represent a special population in pharmacology [...].

Physiologically Based Pharmacokinetic Modeling of Nilotinib for Drug-Drug Interactions, Pediatric Patients, and Pregnancy and Lactation

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.

Physiologically based pharmacokinetic modeling of ritonavir-oxycodone drug interactions and its implication for dosing strategy

The concomitant administration of ritonavir and oxycodone may significantly increase the plasma concentrations of oxycodone. This study was aimed to simulate DDI between ritonavir and oxycodone, a widely used opioid, and to formulate dosing protocols for oxycodone by using physiologically based pharmacokinetic (PBPK) modeling. We developed a ritonavir PBPK model incorporating induction and competitive and time-dependent inhibition of CYP3A4 and competitive inhibition of CYP2D6. The ritonavir model was evaluated with observed clinical pharmacokinetic data and validated for its CYP3A4 inhibition potency. We then used the model to simulate drug interactions between oxycodone and ritonavir under various dosing scenarios. The developed model captured the pharmacokinetic characteristics of ritonavir from clinical studies. The model also accurately predicts exposure changes of midazolam, triazolam, and oxycodone in the presence of ritonavir. According to model simulations, the steady-state maximum, minimum and average concentrations of oxycodone increased by up to 166% after co-administration with ritonavir, and the total exposure increased by approximately 120%. To achieve similar steady-state concentrations, halving the dose with an unchanged dosing interval or doubling the dosing interval with an unaltered single dose should be practical for oxycodone, whether formulated in uncoated or controlled-release tablets during long-term co-medication with ritonavir. The results revealed exposure-related risks of oxycodone-ritonavir interactions that have not been studied clinically and emphasized PBPK as a workable method to direct judicious dosage.

Development of a Generic Fetal Physiologically Based Pharmacokinetic Model and Prediction of Human Maternal and Fetal Organ Concentrations of Cefuroxime

BACKGROUND AND OBJECTIVE

Physiologically based pharmacokinetic (PBPK) models for pregnant women have recently been successfully used to predict maternal and umbilical cord pharmacokinetics (PK). Because there is very limited opportunity for conducting clinical and PK investigations for fetal drug exposure, PBPK models may provide further insights. The objectives of this study were to extend a whole-body pregnancy PBPK model by multiple compartments representing fetal organs, and to predict the PK of cefuroxime in the maternal and fetal plasma, the amniotic fluid, and several fetal organs.

METHODS

To this end, a previously developed pregnancy PBPK model for cefuroxime was updated using the open-source software Open Systems Pharmacology (PK-Sim®/MoBi®). Multiple compartments were implemented to represent fetal organs including brain, heart, liver, lungs, kidneys, the gastrointestinal tract (GI), muscles, and fat tissue, as well as another compartment lumping organs and tissues not explicitly represented.

RESULTS

This novel PBPK model successfully predicted cefuroxime concentrations in maternal blood, umbilical cord, amniotic fluid, and several fetal organs including heart, liver, and lungs. Further model validation with additional clinical PK data is needed to build confidence in the model.

CONCLUSIONS

Being developed with an open-source software, the presented generic model can be freely re-used and tailored to address specific questions at hand, e.g., to assist the design of clinical studies in the context of drug research or to predict fetal organ concentrations of chemicals in the context of fetal health risk assessment.

Applied physiologically-based pharmacokinetic modeling to assess uridine diphosphate-glucuronosyltransferase-mediated drug-drug interactions for Vericiguat

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.

Leveraging the use of in vitro and computational methods to support the development of enabling oral drug products: An InPharma commentary

Due to the strong tendency towards poorly soluble drugs in modern development pipelines, enabling drug formulations such as amorphous solid dispersions, cyclodextrins, co-crystals and lipid-based formulations are frequently applied to solubilize or generate supersaturation in gastrointestinal fluids, thus enhancing oral drug absorption. Although many innovative in vitro and in silico tools have been introduced in recent years to aid development of enabling formulations, significant knowledge gaps still exist with respect to how best to implement them. As a result, the development strategy for enabling formulations varies considerably within the industry and many elements of empiricism remain. The InPharma network aims to advance a mechanistic, animal-free approach to the assessment of drug developability. This commentary focuses current status and next steps that will be taken in InPharma to identify and fully utilize 'best practice' in vitro and in silico tools for use in physiologically based biopharmaceutic models.

Mechanistic Modeling of the Drug-Drug Interaction Between Efavirenz and Dolutegravir: Is This Interaction Clinically Relevant When Switching From Efavirenz to Dolutegravir During Pregnancy?

Following the 2021 World Health Organization's updated recommendations on the management of HIV infection, millions of people living with HIV are currently switched from efavirenz-based antiretroviral therapy to dolutegravir-based antiretroviral therapy. Pregnant individuals transitioning from efavirenz to dolutegravir might be at increased risk of insufficient viral suppression in the immediate postswitch period because both efavirenz- and pregnancy-related increases in hormone levels induce enzymes involved in dolutegravir metabolism, namely, cytochrome P450 3A4 and uridine 5'-diphospho-glucuronosyltransferase 1A1. This study aimed at developing physiologically based pharmacokinetic models to simulate the switch from efavirenz to dolutegravir in the late second and third trimester. To this end, the drug-drug interaction between efavirenz and the uridine 5'-diphospho-glucuronosyltransferase 1A1 substrates dolutegravir and raltegravir was first simulated in nonpregnant subjects. After successful validation, the physiologically based pharmacokinetic models were translated to pregnancy and dolutegravir pharmacokinetics following efavirenz discontinuation were predicted. Modeling results indicated that, at the end of the second trimester, both efavirenz concentrations and dolutegravir trough concentrations fell below respective pharmacokinetic target thresholds (defined as reported thresholds producing 90%-95% of the maximum effect) during the time interval from 9.75 to 11 days after dolutegravir initiation. At the end of the third trimester, this time interval spanned from 10.3 days to >4 weeks after dolutegravir initiation. These findings suggest that dolutegravir exposure in the immediate post-efavirenz switch period during pregnancy may be suboptimal, leading to HIV viremia and, potentially, resistance. The clinical implications of these findings remain to be substantiated by future studies.

Considering developmental neurotoxicity in vitro data for human health risk assessment using physiologically-based kinetic modeling: deltamethrin case study

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.

Hydroxyurea treatment for sickle cell anemia during pregnancy and lactation: current evidence and knowledge gaps

Sickle cell anemia (SCA) is a life-threatening genetic condition contributing to high-risk pregnancies affecting both the mother and fetus. With improved management of children with SCA, this life-threatening hematological disorder has evolved into a chronic disease of adults, and consequently parenthood has now become a possible and important life goal for many patients. Providing continuous management with healthy red blood cell function and avoiding SCA-associated complications, such as pain crises, acute chest syndrome, and stroke, are crucial for a healthy pregnancy. Despite its excellent safety profile in non-pregnant adults and children, and based on theoretical concerns derived from data using animal models and supraphysiological dosing, hydroxyurea is currently contraindicated for pregnant and lactating women with SCA. Clinical experience of hydroxyurea use during pregnancy is increasingly reported, however, and has shown inconsistent results of fetal or infant adverse effects. How the hydroxyurea exposure level may correlate with pregnancy outcomes is still unclear. Accordingly, efforts should be made to systemically evaluate exposure and safety of hydroxyurea treatment during pregnancy and lactation. Novel approaches such as physiologically based pharmacokinetic (PBPK) modeling, coupled with the ex vivo human placental cotyledon perfusion assay, provide opportunities to understand hydroxyurea exposure not only in pregnant women but also in the developing fetus. Combined with animal data, research using these approaches might be able to define safe and effective hydroxyurea dosing regimens for pregnant and lactating women with SCA, when the benefits of continuing hydroxyurea treatment likely outweigh the risks of non-treatment, by avoiding substantial morbidity and even mortality for both mothers and infants.

Physiologically-based pharmacokinetic modeling of remdesivir and its metabolites in pregnant women with COVID-19

Pregnant individuals are at high risk for severe illness from COVID-19, and there is an urgent need to identify safe and effective therapeutics for this population. Remdesivir (RDV) is a SARS-CoV-2 nucleotide analog RNA polymerase inhibitor. Limited RDV pharmacokinetic (PK) and safety data are available for pregnant women receiving RDV. The aims of this study were to translate a previously published nonpregnant adult physiologically based PK (PBPK) model for RDV to pregnancy and evaluate model performance with emerging clinical PK data in pregnant women with COVID-19. The pregnancy model was built in the Open Systems Pharmacology software suite (Version 10) including PK-Sim® and MoBi® with pregnancy-related changes of relevant enzymes applied. PK were predicted in a virtual population of 1000 pregnant subjects, and prediction results were compared with in vivo PK data from the International Maternal, Pediatric, Adolescent AIDS Clinical Trials (IMPAACT) Network  2032 study. The developed PBPK model successfully captured RDV and its metabolites' plasma concentrations during pregnancy. The ratios of prediction versus observation for RDV area under the curve from time 0 to infinity (AUC0-∞ ) and maximum concentration (Cmax ) were 1.61 and 1.17, respectively. For GS-704277, the ratios of predicted versus observed were 0.94 for AUC0-∞ and 1.20 for Cmax . For GS-441524, the ratios of predicted versus observed were 1.03 for AUC0-24 , 1.05 for Cmax , and 1.07 for concentrations at 24 h. All predictions of AUC and Cmax for RDV and its metabolites were within a twofold error range, and about 60% of predictions were within a 10% error range. These findings demonstrate the feasibility of translating PBPK models to pregnant women to potentially guide trial design, clinical decision making, and drug development.

Pyridine Controlled Tin Perovskite Crystallization

Controlling the crystallization of perovskite in a thin film is essential in making solar cells. Processing tin-based perovskite films from solution is challenging because of the uncontrollable faster crystallization of tin than the most used lead perovskite. The best performing devices are prepared by depositing perovskite from dimethyl sulfoxide because it slows down the assembly of the tin-iodine network that forms perovskite. However, while dimethyl sulfoxide seems the best solution to control the crystallization, it oxidizes tin during processing. This work demonstrates that 4-(tert-butyl) pyridine can replace dimethyl sulfoxide to control the crystallization without oxidizing tin. We show that tin perovskite films deposited from pyridine have a 1 order of magnitude lower defect density, which promotes charge mobility and photovoltaic performance.

Evaluation of a rapid, generic human gestational dose model

Chemical risk assessment considers potentially susceptible populations including pregnant women and developing fetuses. Humans encounter thousands of chemicals in their environments, few of which have been fully characterized. Toxicokinetic (TK) information is needed to relate chemical exposure to potentially bioactive tissue concentrations. Observational data describing human gestational exposures are unavailable for most chemicals, but physiologically based TK (PBTK) models estimate such exposures. Development of chemical-specific PBTK models requires considerable time and resources. As an alternative, generic PBTK approaches describe a standardized physiology and characterize chemicals with a set of standard physical and TK descriptors - primarily plasma protein binding and hepatic clearance. Here we report and evaluate a generic PBTK model of a human mother and developing fetus. We used a published set of formulas describing the major anatomical and physiological changes that occur during pregnancy to augment the High-Throughput Toxicokinetics (httk) software package. We simulated the ratio of concentrations in maternal and fetal plasma and compared to literature in vivo measurements. We evaluated the model with literature in vivo time-course measurements of maternal plasma concentrations in pregnant and non-pregnant women. Finally, we prioritized chemicals measured in maternal serum based on predicted fetal brain concentrations. This new model can be used for TK simulations of 859 chemicals with existing human-specific in vitro TK data as well as any new chemicals for which such data become available. This gestational model may allow for in vitro to in vivo extrapolation of point of departure doses relevant to reproductive and developmental toxicity.

Antidepressants and Antipsychotics in Human Pregnancy: Transfer Across the Placenta and Opportunities for Modeling Studies

There is limited information about the transfer of antidepressants and antipsychotics across the human placenta. The objective of the current review was to systematically screen the scientific literature using relevant keywords to collect quantitative data on placental transfer of these drugs in humans and to give an overview of current modeling approaches used in this context. The collected data encompassed clinically measured fetal:maternal (F:M) concentration ratios (ie, the ratio between drug concentrations measured in the umbilical cord and drug concentrations measured in the mother) and transfer data obtained from ex vivo cotyledon perfusion experiments. These data were found for 18 antidepressants and some of their pharmacologically active metabolites, and for 10 antipsychotics and the metabolites thereof. Based on the collected data, similar maternal and fetal exposure could be observed for only a few compounds (eg, norfluoxetine and desvenlafaxine), whereas for most drugs (eg, paroxetine, sertraline, and quetiapine), fetal exposure appeared to be on average lower than maternal exposure. Venlafaxine appeared to be an exception in that the data indicated equivalent or higher concentrations in the umbilical cord than in the mother. Physiologically based pharmacokinetic (PBPK) models were sporadically used to investigate maternal pharmacokinetics of antidepressants or antipsychotics (eg, for sertraline, aripiprazole, and olanzapine), although without explicitly addressing fetal drug exposure. It is recommended that PBPK modeling is applied more frequently to these drugs. Although no substitute for clinical studies, these tools can help to better understand pregnancy-induced pharmacokinetic changes and ultimately contribute to a more evidence-based pharmacotherapy of depression and psychosis in pregnant subjects.

Development of a Generic Physiologically-Based Pharmacokinetic Model for Lactation and Prediction of Maternal and Infant Exposure to Ondansetron via Breast Milk

Ondansetron is commonly used in breastfeeding mothers to treat nausea and vomiting. There is limited information in humans regarding safety of ondansetron exposure to nursing infants and no adequate study looking at ondansetron pharmacokinetics during lactation. We developed a generic physiologically-based pharmacokinetic lactation model for small molecule drugs and applied this model to predict ondansetron transfer into breast milk and characterize infant exposure. Drug-specific model inputs were parameterized using data from the literature. Population-specific inputs were derived from a previously conducted systematic literature review of anatomic and physiologic changes in postpartum women. Model predictions were evaluated using ondansetron plasma and breast milk concentration data collected prospectively from 78 women in the Commonly Used Drugs During Lactation and infant Exposure (CUDDLE) study. The final model predicted breast milk and plasma exposures following a single 4 mg dose of intravenous ondansetron in 1,000 simulated women who were 2 days postpartum. Model predictions showed good agreement with observed data. Breast milk median prediction error (MPE) was 18.4% and median absolute prediction error (MAPE) was 53.0%. Plasma MPE was 32.5% and MAPE was 43.2%. The model-predicted daily and relative infant doses were 0.005 mg/kg/day and 3.0%, respectively. This model adequately predicted ondansetron passage into breast milk. The calculated low relative infant dose indicates that mothers receiving ondansetron can safely breastfeed. The model building blocks and population database are open-source and can be adapted to other drugs.

Physiologically Based Pharmacokinetic Modeling in Pregnant Women Suggests Minor Decrease in Maternal Exposure to Olanzapine

Pregnancy is accompanied by significant physiological changes that might affect the in vivo drug disposition. Olanzapine is prescribed to pregnant women with schizophrenia, while its pharmacokinetics during pregnancy remains unclear. This study aimed to develop a physiologically based pharmacokinetic (PBPK) model of olanzapine in the pregnant population. With the contributions of each clearance pathway determined beforehand, a full PBPK model was developed and validated in the non-pregnant population. This model was then extrapolated to predict steady-state pharmacokinetics in the three trimesters of pregnancy by introducing gestation-related alterations. The model adequately simulated the reported time-concentration curves. The geometric mean fold error of Cmax and AUC was 1.14 and 1.09, respectively. The model predicted that under 10 mg daily dose, the systematic exposure of olanzapine had minor changes (less than 28%) throughout pregnancy. We proposed that the reduction in cytochrome P4501A2 activity is counteracted by the induction of other enzymes, especially glucuronyltransferase1A4. In conclusion, the PBPK model simulations suggest that, at least at the tested stages of pregnancy, dose adjustment of olanzapine can hardly be recommended for pregnant women if effective treatment was achieved before the onset of pregnancy and if fetal toxicity can be ruled out.

Mechanistic Modeling of Placental Drug Transfer in Humans: How Do Differences in Maternal/Fetal Fraction of Unbound Drug and Placental Influx/Efflux Transfer Rates Affect Fetal Pharmacokinetics?

Background: While physiologically based pharmacokinetic (PBPK) models generally predict pharmacokinetics in pregnant women successfully, the confidence in predicting fetal pharmacokinetics is limited because many parameters affecting placental drug transfer have not been mechanistically accounted for. Objectives: The objectives of this study were to implement different maternal and fetal unbound drug fractions in a PBPK framework; to predict fetal pharmacokinetics of eight drugs in the third trimester; and to quantitatively investigate how alterations in various model parameters affect predicted fetal pharmacokinetics. Methods: The ordinary differential equations of previously developed pregnancy PBPK models for eight drugs (acyclovir, cefuroxime, diazepam, dolutegravir, emtricitabine, metronidazole, ondansetron, and raltegravir) were amended to account for different unbound drug fractions in mother and fetus. Local sensitivity analyses were conducted for various parameters relevant to placental drug transfer, including influx/efflux transfer clearances across the apical and basolateral membrane of the trophoblasts. Results: For the highly-protein bound drugs diazepam, dolutegravir and ondansetron, the lower fraction unbound in the fetus vs. mother affected predicted pharmacokinetics in the umbilical vein by ≥10%. Metronidazole displayed blood flow-limited distribution across the placenta. For all drugs, umbilical vein concentrations were highly sensitive to changes in the apical influx/efflux transfer clearance ratio. Additionally, transfer clearance across the basolateral membrane was a critical parameter for cefuroxime and ondansetron. Conclusion: In healthy pregnancies, differential protein binding characteristics in mother and fetus give rise to minor differences in maternal-fetal drug exposure. Further studies are needed to differentiate passive and active transfer processes across the apical and basolateral trophoblast membrane.

Mechanistic Coupling of a Novel in silico Cotyledon Perfusion Model and a Physiologically Based Pharmacokinetic Model to Predict Fetal Acetaminophen Pharmacokinetics at Delivery

Little is known about placental drug transfer and fetal pharmacokinetics despite increasing drug use in pregnant women. While physiologically based pharmacokinetic (PBPK) models can help in some cases to shed light on this knowledge gap, adequate parameterization of placental drug transfer remains challenging. A novel in silico model with seven compartments representing the ex vivo cotyledon perfusion assay was developed and used to describe placental transfer and fetal pharmacokinetics of acetaminophen. Unknown parameters were optimized using observed data. Thereafter, values of relevant model parameters were copied to a maternal-fetal PBPK model and acetaminophen pharmacokinetics were predicted at delivery after oral administration of 1,000 mg. Predictions in the umbilical vein were evaluated with data from two clinical studies. Simulations from the in silico cotyledon perfusion model indicated that acetaminophen accumulates in the trophoblasts; simulated steady state concentrations in the trophoblasts were 4.31-fold higher than those in the perfusate. The whole-body PBPK model predicted umbilical vein concentrations with a mean prediction error of 24.7%. Of the 62 concentration values reported in the clinical studies, 50 values (81%) were predicted within a 2-fold error range. In conclusion, this study presents a novel in silico cotyledon perfusion model that is structurally congruent with the placenta implemented in our maternal-fetal PBPK model. This allows transferring parameters from the former model into our PBPK model for mechanistically exploring whole-body pharmacokinetics and concentration-effect relationships in the placental tissue. Further studies should investigate acetaminophen accumulation and metabolism in the placenta as the former might potentially affect placental prostaglandin synthesis and subsequent fetal exposure.

Fluoride Chemistry in Tin Halide Perovskites

Tin is the frontrunner for substituting toxic lead in perovskite solar cells. However, tin suffers the detrimental oxidation of Sn^II to Sn^IV . Most of reported strategies employ SnF₂ in the perovskite precursor solution to prevent Sn^IV formation. Nevertheless, the working mechanism of this additive remains debated. To further elucidate it, we investigate the fluoride chemistry in tin halide perovskites by complementary analytical tools. NMR analysis of the precursor solution discloses a strong preferential affinity of fluoride anions for Sn^IV over Sn^II , selectively complexing it as SnF₄ . Hard X-ray photoelectron spectroscopy on films shows the lower tendency of SnF₄ than SnI₄ to get included in the perovskite structure, hence preventing the inclusion of Sn^IV in the film. Finally, small-angle X-ray scattering reveals the strong influence of fluoride on the colloidal chemistry of precursor dispersions, directly affecting perovskite crystallization.

Evaluation of Physiologically Based Pharmacokinetic Models to Predict the Absorption of BCS Class I Drugs in Different Pediatric Age Groups

Age-related changes in many parameters affecting drug absorption remain poorly characterized. The objective of this study was to apply physiologically based pharmacokinetic (PBPK) models in pediatric patients to investigate the absorption and pharmacokinetics of 4 drugs belonging to the Biopharmaceutics Classification System (BCS) class I administered as oral liquid formulations. Pediatric PBPK models built with PK-Sim/MoBi were used to predict the pharmacokinetics of acetaminophen, emtricitabine, theophylline, and zolpidem in different pediatric populations. The model performance for predicting drug absorption and pharmacokinetics was assessed by comparing the predicted absorption profile with the deconvoluted dose fraction absorbed over time and predicted with observed plasma concentration-time profiles. Sensitivity analyses were performed to analyze the effects of changes in relevant input parameters on the model output. Overall, most pharmacokinetic parameters were predicted within a 2-fold error range. The absorption profiles were generally reasonably predicted, but relatively large differences were observed for acetaminophen. Sensitivity analyses showed that the predicted absorption profile was most sensitive to changes in the gastric emptying time (GET) and the specific intestinal permeability. The drug's solubility played only a minor role. These findings confirm that gastric emptying time, more than intestinal permeability or solubility, is a key factor affecting BCS class I drug absorption in children. As gastric emptying time is prolonged in the fed state, a better understanding of the interplay between food intake and gastric emptying time in children is needed, especially in the very young in whom the (semi)fed condition is the prevailing prandial state, and hence prolonged gastric emptying time seems more plausible than the fasting state.

Predictive Performance of Physiology-Based Pharmacokinetic Dose Estimates for Pediatric Trials: Evaluation With 10 Bayer Small-Molecule Compounds in Children

Development and guidance of dosing schemes in children have been supported by physiology-based pharmacokinetic (PBPK) modeling for many years. PBPK models are built on a generic basis, where compound- and system-specific parameters are separated and can be exchanged, allowing the translation of these models from adults to children by accounting for physiological differences. Owing to these features, PBPK modeling is a valuable approach to support clinical decision making for dosing in children. In this analysis, we evaluate pediatric PBPK models for 10 small-molecule compounds that were applied to support clinical decision processes at Bayer for their predictive power in different age groups. Ratios of PBPK-predicted to observed PK parameters for the evaluated drugs in different pediatric age groups were estimated. Predictive performance was analyzed on the basis of a 2-fold error range and the bioequivalence range (ie, 0.8 ≤ predicted/observed ≤ 1.25). For all 10 compounds, all predicted-to-observed PK ratios were within a 2-fold error range (n = 27), with two-thirds of the ratios within the bioequivalence range (n = 18). The findings demonstrate that the pharmacokinetics of these compounds was successfully and adequately predicted in different pediatric age groups. This illustrates the applicability of PBPK for guiding dosing schemes in the pediatric population.

A generic framework for the physiologically-based pharmacokinetic platform qualification of PK-Sim and its application to predicting cytochrome P450 3A4-mediated drug-drug interactions

The success of applications of physiologically‐based pharmacokinetic (PBPK) modeling in drug development and drug labeling has triggered regulatory agencies to demand rigorous demonstration of the predictive capability of the specific PBPK platform for a particular intended application purpose. The effort needed to comply with such qualification requirements exceeds the costs for any individual PBPK application. Because changes or updates of a PBPK platform would require (re‐)qualification, a reliable and efficient generic qualification framework is needed. We describe the development and implementation of an agile and sustainable technical framework for automatic PBPK platform (re‐)qualification of PK‐Sim^® embedded in the open source and open science GitHub landscape of Open Systems Pharmacology. The qualification approach enables the efficient assessment of all aspects relevant to the qualification of a particular purpose and provides transparency and traceability for all stakeholders. As a showcase example for the power and versatility of the qualification framework, we present the qualification of PK‐Sim^® for the intended purpose of predicting cytochrome P450 3A4 (CYP3A4)–mediated drug–drug interactions (DDIs). Several perpetrator PBPK models featuring various degrees of CYP3A4 modulation and different types of mechanisms (competitive inhibition, mechanism‐based inactivation, and induction) were coupled with a set of PBPK models of sensitive CYP3A4 victim drugs. Simulations were compared to a comprehensive data set of 135 observations from published clinical DDI studies. The platform's overall predictive performance showed reasonable accuracy and precision (geometric mean fold error of 1.4 for both area under the plasma concentration‐time curve ratios and peak plasma concentration ratios with/without perpetrator) and suggests that PK‐Sim^® can be applied to quantitatively assess CYP3A4‐mediated DDI in clinically untested scenarios.

Structural Determination of an Unusual CuI -Porphyrin-π-Bond in a Hetero-Pacman Cu-Zn-Complex

The synthesis and characterization of a hetero‐dinuclear compound is presented, in which a copper(I) trishistidine type coordination unit is positioned directly above a zinc porphyrin unit. The close distance between the two coordination fragments is secured by a rigid xanthene backbone, and a unique (intramolecular) copper porphyrin‐π‐bond was determined for the first time in the molecular structure. This structural motif was further analyzed by temperature‐dependent NMR studies: In solution at room temperature the coordinative bond fluctuates, while it can be frozen at low temperatures. Preliminary reactivity studies revealed a reduced reactivity of the copper(I) moiety towards dioxygen. The results adumbrate why nature is avoiding metal porphyrin‐π‐bonds by fixing reactive metal centers in a predetermined distance to each other within multimetallic enzymatic reaction centers.

Physiologically Based Pharmacokinetic Modeling Framework to Predict Neonatal Pharmacokinetics of Transplacentally Acquired Emtricitabine, Dolutegravir, and Raltegravir

BACKGROUND AND OBJECTIVE

Little is understood about neonatal pharmacokinetics immediately after delivery and during the first days of life following intrauterine exposure to maternal medications. Our objective was to develop and evaluate a novel, physiologically based pharmacokinetic modeling workflow for predicting perinatal and postnatal disposition of commonly used antiretroviral drugs administered prenatally to pregnant women living with human immunodeficiency virus.

METHODS

Using previously published, maternal-fetal, physiologically based pharmacokinetic models for emtricitabine, dolutegravir, and raltegravir built with PK-Sim/MoBi^®, placental drug transfer was predicted in late pregnancy. The total drug amount in fetal compartments at term delivery was estimated and subsequently integrated as initial conditions in different tissues of a whole-body, neonatal, physiologically based pharmacokinetic model to predict drug concentrations in the neonatal elimination phase after birth. Neonatal elimination processes were parameterized according to published data. Model performance was assessed by clinical data.

RESULTS

Neonatal physiologically based pharmacokinetic models generally captured the initial plasma concentrations after delivery but underestimated concentrations in the terminal phase. The mean percentage error for predicted plasma concentrations was - 71.5%, - 33.8%, and 76.7% for emtricitabine, dolutegravir, and raltegravir, respectively. A sensitivity analysis suggested that the activity of organic cation transporter 2 and uridine diphosphate glucuronosyltransferase 1A1 during the first postnatal days in term newborns is ~11% and ~30% of that in adults, respectively.

CONCLUSIONS

These findings demonstrate the general feasibility of applying physiologically based pharmacokinetic models to predict washout concentrations of transplacentally acquired drugs in newborns. These models can increase the understanding of pharmacokinetics during the first postnatal days and allow the prediction of drug exposure in this vulnerable population.

Physiologically-based pharmacokinetic (PBPK) exploration of extrinsic factors influencing vericiguat pharmacokinetics

Introduction

Vericiguat is a once daily, novel oral stimulator of soluble guanylate cyclase (sGC) that showed clinical benefit in the Phase III VICTORIA study in heart failure patients with reduced ejection fraction (HFrEF, NCT02861534). Nonclinical and clinical studies demonstrated that the primary route of elimination of vericiguat was glucuronidation to an inactive metabolite M-1 (N-glucuronide). This glucuronidation was catalyzed by uridine 5'-diphospho-glucuronosyltransferases (UGT)1A9 as well as UGT1A1, thus vericiguat may have a potential for victim drug-drug interaction (DDI) when co-administered with potent UGT inhibitors.

Purpose

In a clinical DDI study with mefenamic acid as an UGT1A9 inhibitor no clinically relevant increase in vericiguat exposure in healthy subjects was observed (EudraCT 2014–000764–17). This analysis aims to prospectively investigate as extrinsic factors the DDI potential with atazanavir as a selective UGT1A1 inhibitor via full dynamic physiologically-based pharmacokinetic (PBPK) modelling.

Methods

A PBPK model for vericiguat and M-1 in healthy adults was built with PK-Sim (PBPK platform as part of the Open Systems Pharmacology Suite) by integrating physicochemical, in vitro metabolism and transporter data as well as PK data from clinical pharmacology studies in order to assess the victim DDI potential of vericiguat when co-administered with UGT inhibitors. First, PBPK models for mefenamic acid and atazanavir were separately developed and verified using published literature data. The PBPK model for vericiguat was then verified with regard to its fraction of metabolism by UGTs by comparing simulated and observed data of the clinical mefenamic acid DDI study. Finally, the UGT1A1 DDI potential of vericiguat was prospectively predicted by simulating an in silico study between the UGT1A1 inhibitor atazanavir and vericiguat.

Results

In line with the results of the clinical DDI study with mefenamic acid, an increase in total vericiguat exposure by 14% (area under the concentration time curve ratio (AUCR) of 1.14 (geoCV 5.3%; 90% population interval: 1.06 to 1.25) and peak exposure increase by 6% (CmaxR of 1.06; geoCV 5.9%; 90% population interval: 1.01 to 1.20) was simulated using the PBPK model. A prospective prediction of a virtual DDI trial between the UGT1A1 inhibitor atazanavir yielded an AUCR of 1.12 (geoCV 2.9%; 90% population interval: 1.07 to 1.17) and a CmaxR of 1.04 (geoCV 1.1%; 90% population interval: 1.03 to 1.06). The proposed population intervals for AUCR and CmaxR for both DDI studies lie within the default no-effect boundary of 0.80 to 1.25 according to the to January 2020 FDA DDI guideline.

Conclusion(s)

Results of UGT1A9-DDI simulations were consistent with those of the clinical study-The prospective UGT1A1-DDI simulation results suggest a low potential for vericiguat to be subject to DDI when co-administered with UGT1A1 inhibitors.

Funding Acknowledgement

Type of funding source: Private company. Main funding source(s): Funding for this research was provided by Bayer and Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA

Highly Cooperative Photoswitching in Dihydropyrene Dimers

We present a strategy to achieve highly cooperative photoswitching, where the initial switching event greatly facilitates subsequent switching of the neighboring unit. By linking donor/acceptor substituted dihydropyrenes via suitable π-conjugated bridges, the quantum yield of the second photochemical ring-opening process could be enhanced by more than two orders of magnitude as compared to the first ring-opening. As a result, the intermediate mixed switching state is not detected during photoisomerization although it is formed during the thermal back reaction. Comparing the switching behavior of various dimers, both experimentally and computationally, helped to unravel the crucial role of the bridging moiety connecting both photochromic units. The presented dihydropyrene dimer serves as model system for longer cooperative switching chains, which, in principle, should enable efficient and directional transfer of information along a molecularly defined path. Moreover, our concept allows to enhance the photosensitivity in oligomeric and polymeric systems and materials thereof.

Best Practices in the Development and Validation of Physiologically Based Biopharmaceutics Modeling. A Workshop Summary Report

This workshop report summarizes the proceedings of Day 2 of a three-day workshop on "Current State and Future Expectations of Translational Modeling Strategies toSupportDrug Product Development, Manufacturing Changes and Controls". From a drug product quality perspective, physiologically based biopharmaceutics modeling (PBBM) is a tool to link variations in the drug product quality attributes to in vivo outcomes enabling the establishment of clinically relevant drug product specifications (CRDPS). Day 2 of the workshop focused on best practices in developing, verifying and validating PBBM. This manuscript gives an overview of podium presentations and summarizes breakout (BO) session discussions related to (1) challenges and opportunities for using PBBM to assess the clinical impact of formulation and manufacturing changes on the in vivo performance of a drug product, (2) best practices to account for parameter uncertainty and variability during model development, (3) best practices in the development, verification and validation of PBBM and (4) opportunities and knowledge gaps related to leveraging PBBM for virtual bioequivalence simulations.

In Vitro Biopredictive Methods: A Workshop Summary Report

This workshop report summarizes the proceedings of Day 1 of a three-day workshop on "Current State and Future Expectations of Translational Modeling Strategies to Support Drug Product Development, Manufacturing Changes and Controls". Physiologically based biopharmaceutics models (PBBM) are tools which enable the drug product quality attributes to be linked to the in vivo performance. These tools rely on key quality inputs in order to provide reliable predictions. After introducing the objectives of the workshop and the expectations from the breakout sessions, Day 1 of the workshop focused on the best practices and challenges in measuring in vitro inputs needed for modeling, such as the drug solubility, the dissolution rate of the drug product, potential precipitation of the drug and drug permeability. This paper reports the podium presentations and summarizes breakout session discussions related to A) the best strategies for determining solubility, supersaturation and critical supersaturation; B) the best strategies for the development of biopredictive (clinically relevant) dissolution methods; C) the challenges associated with describing gastro-intestinal systems parameters such as mucus, liquid volume and motility; and D) the challenges with translating biopharmaceutical measures of drug permeability along the gastrointestinal tract to a meaningful model parameter.

Predictive Pediatric Modeling and Simulation Using Ontogeny Information

Food and Drug Administration submissions of physiologically based pharmacokinetic (PBPK) modeling and simulation of small-molecule drugs document the relevance of pediatric drug development and, in particular, information on dosing strategies in children. The most relevant prerequisite for reliable PBPK-based translation of adult pharmacokinetics of a small molecule to children is knowledge of the drug-specific absorption, distribution, metabolism, and elimination (ADME) processes in adults together with existing information about ontogeny of ADME processes relevant for the drug. All mechanisms driving a drug's clearance are of specific importance. For other drug modalities, our knowledge of ADME processes and ontogeny is still limited. More research is required, for example, to understand why some therapeutic proteins show complex differences in pharmacokinetics between adults and children, whereas other proteins seem to follow simple allometric scaling rules. Ontogeny information originates from various sources, such as (semi)quantitative mRNA expression, in vitro activity data, and deconvolution of in vivo pharmacokinetic data. The workflow for pediatric predictions is well described in several articles documenting successful translation from adults to children. The technical hurdles for PBPK modeling are low. State-of-the-art PBPK modeling software tools provide integrated pediatric translation workflows. For example, PK-Sim and MoBi are freely available as fully transparent open-source software via Open Systems Pharmacology (OSP). With the latest 2019 software release, version 8.0, OSP even provides a fully integrated technical framework for the qualification (and requalification) of any specific intended PBPK use in line with Food and Drug Administration and European Medicines Agency PBPK guidance. Qualification packages for pediatric translation are available on the OSP platform.

Anatomical and physiological alterations of pregnancy

The extensive metabolic demands of pregnancy require specific physiological and anatomical changes. These changes affect almost all organ systems, including the cardiovascular, respiratory, renal, gastrointestinal, and hematologic system. The placenta adds another layer of complexity. These changes make it challenging for clinicians to understand presenting signs and symptoms, or to interpret laboratory and radiological tests. Furthermore, these physiological alterations can affect the pharmacokinetics and pharmacodynamics of drugs. Drug safety in lactation is only supported by limited evidence. In addition, the teratogenic effects of medications are often extrapolated from animals, which further adds uncertainties. Unfortunately, pregnant women are only rarely included in clinical drug trials, while doses, regimens, and side effects are often extrapolated from studies conducted in non-pregnant populations. In this comprehensive review, we present the changes occurring in each system with its effects on the pharmacokinetic variables. Understanding these physiological changes throughout normal pregnancy helps clinicians to optimize the health of pregnant women and their fetuses. Furthermore, the information on pregnancy-related physiology is also critical to guide study design in this vulnerable 'orphan' population, and provides a framework to explore pregnancy-related pathophysiology such as pre-eclampsia.

Prediction of Maternal and Fetal Pharmacokinetics of Dolutegravir and Raltegravir Using Physiologically Based Pharmacokinetic Modeling

BACKGROUND

Predicting drug pharmacokinetics in pregnant women including placental drug transfer remains challenging. This study aimed to develop and evaluate maternal-fetal physiologically based pharmacokinetic models for two antiretroviral drugs, dolutegravir and raltegravir.

Mercaptothiacalixarenes Steer 24 Copper(I) Centers to form a Hollow-Sphere Structure Featuring Cu2 S2 Motifs with Exceptionally Short Cu⋅⋅⋅Cu Distances

Tetramercaptotetrathiacalix[4]arene (LH₄) can be used as a coordination platform to bind four Cu^I ions at the thiolate and thioether S atoms. Donor ligands such as phosphanes can stabilize the resulting [LCu₄] units, which then remain monomeric ([(Ph₃PCu)₄L]). In the absence of donor ligands, they aggregate, providing a hexamer ([LCu₄]₆) in high yields, with a hollow‐sphere structure formed by an unprecedented Cu₂₄S₄₈ cage that is surrounded by the organic framework of the calixarene chalices. Preliminary NMR experiments with regard to the host‐guest chemistry in solution showed that the compound represents a polytopic host for acetonitrile and methane.

Clinical Pharmacokinetic Studies in Pregnant Women and the Relevance of Pharmacometric Tools

BACKGROUND

In clinical pharmacokinetic (PK) studies, pregnant women are significantly underrepresented because of ethical and legal reasons which lead to a paucity of information on potential PK changes in this population. As a consequence, pharmacometric tools became instrumental to explore and quantify the impact of PK changes during pregnancy.

METHODS

We explore and discuss the typical characteristics of population PK and physiologically based pharmacokinetic (PBPK) models with a specific focus on pregnancy and postpartum.

RESULTS

Population PK models enable the analysis of dense, sparse or unbalanced data to explore covariates in order to (partly) explain inter-individual variability (including pregnancy) and to individualize dosing. For population PK models, we subsequently used an illustrative approach with ketorolac data to highlight the relevance of enantiomer specific modeling for racemic drugs during pregnancy, while data on antibiotic prophylaxis (cefazolin) during surgery illustrate the specific characteristics of the fetal compartments in the presence of timeconcentration profiles. For PBPK models, an overview on the current status of reports and papers during pregnancy is followed by a PBPK cefuroxime model to illustrate the added benefit of PBPK in evaluating dosing regimens in pregnant women.

CONCLUSIONS

Pharmacometric tools became very instrumental to improve perinatal pharmacology. However, to reach their full potential, multidisciplinary collaboration and structured efforts are needed to generate more information from already available datasets, to share data and models, and to stimulate cross talk between clinicians and pharmacometricians to generate specific observations (pathophysiology during pregnancy, breastfeeding) needed to further develop the field.

Integration of Placental Transfer in a Fetal-Maternal Physiologically Based Pharmacokinetic Model to Characterize Acetaminophen Exposure and Metabolic Clearance in the Fetus

BACKGROUND AND OBJECTIVE

Although acetaminophen is frequently used during pregnancy, little is known about fetal acetaminophen pharmacokinetics. Acetaminophen safety evaluation has typically focused on hepatotoxicity, while other events (fetal ductal closure/constriction) are also relevant. We aimed to develop a fetal-maternal physiologically based pharmacokinetic (PBPK) model (f-m PBPK) to quantitatively predict placental acetaminophen transfer, characterize fetal acetaminophen exposure, and quantify the contributions of specific clearance pathways in the term fetus.

METHODS

An acetaminophen pregnancy PBPK model was extended with a compartment representing the fetal liver, which included maturation of relevant enzymes. Different approaches to describe placental transfer were evaluated (ex vivo cotyledon perfusion experiments, placental transfer prediction based on Caco-2 cell permeability or physicochemical properties [MoBi^®]). Predicted maternal and fetal acetaminophen profiles were compared with in vivo observations.

RESULTS

Tested approaches to predict placental transfer showed comparable performance, although the ex vivo approach showed highest prediction accuracy. Acetaminophen exposure in maternal venous blood was similar to fetal venous umbilical cord blood. Prediction of fetal acetaminophen clearance indicated that the median molar dose fraction converted to acetaminophen-sulphate and N-acetyl-p-benzoquinone imine was 0.8% and 0.06%, respectively. The predicted mean acetaminophen concentration in the arterial umbilical cord blood was 3.6 mg/L.

CONCLUSION

The median dose fraction of acetaminophen converted to its metabolites in the term fetus was predicted. The various placental transfer approaches supported the development of a generic f-m PBPK model incorporating in vivo placental drug transfer. The predicted arterial umbilical cord acetaminophen concentration was far below the suggested postnatal threshold (24.47 mg/L) for ductal closure.

Physiologically Based Pharmacokinetic Models to Predict Maternal Pharmacokinetics and Fetal Exposure to Emtricitabine and Acyclovir

Pregnancy is associated with physiological changes that may impact drug pharmacokinetics (PK). The goals of this study were to build maternal-fetal physiologically based pharmacokinetic (PBPK) models for acyclovir and emtricitabine, 2 anti(retro)viral drugs with active renal net secretion, and to (1) evaluate the predicted maternal PK at different stages of pregnancy; (2) predict the changes in PK target parameters following the current dosing regimen of these drugs throughout pregnancy; (3) evaluate the predicted concentrations of these drugs in the umbilical vein at delivery; (4) compare the model performance for predicting maternal PK of emtricitabine in the third trimester with that of previously published PBPK models; and (5) compare different previously published approaches for estimating the placental permeability of these 2 drugs. Results showed that the pregnancy PBPK model for acyclovir predicted all maternal concentrations within a 2-fold error range, whereas the model for emtricitabine predicted 79% of the maternal concentrations values within that range. Extrapolation of these models to earlier stages of pregnancy indicated that the change in the median PK target parameters remained well above the target threshold. Concentrations of acyclovir and emtricitabine in the umbilical vein were overall adequately predicted. The comparison of different emtricitabine PBPK models suggested an overall similar predictive performance in the third trimester, but the comparison of different approaches for estimating placental drug permeability revealed large differences. These models can enhance the understanding of the PK behavior of renally excreted drugs, which may ultimately inform pharmacotherapeutic decision making in pregnant women and their fetuses.

Drug Transporters Expressed in the Human Placenta and Models for Studying Maternal-Fetal Drug Transfer

Tremendous efforts have been directed to investigate the ontogeny of drug transporters in fetuses, neonates, infants, and children based on their importance for understanding drug pharmacokinetics. During development (ie, in the fetus and newborn infant), there is special interest in transporters expressed in the placenta that modulate placental drug transfer. Many of these transporters can decrease or increase drug concentrations in the fetus and at birth, stressing the relevance of elucidating expression in the placenta and potential gestational age-dependent changes therein. Hence, the main objective of this review was to summarize the current knowledge about expression and ontogeny of transporters in the human placenta in healthy pregnant women. In addition, various in vitro, ex vivo, and in silico models that can be used to investigate placental drug transfer, namely, placental cancer cell lines, ex vivo cotyledon perfusion experiments, and physiologically based pharmacokinetic (PBPK) models, are discussed together with their advantages and shortcomings. A particular focus was placed on PBPK models because these models can integrate different types of information, such as expression data, ontogeny information, and observations obtained from the ex vivo cotyledon perfusion experiment. Such a mechanistic modeling framework may leverage the available information and ultimately help to improve knowledge about the adequacy and safety of pharmacotherapy in pregnant women and their fetuses.

A Physiologically Based Pharmacokinetic Model for Pregnant Women to Predict the Pharmacokinetics of Drugs Metabolized Via Several Enzymatic Pathways

BACKGROUND

Physiologically based pharmacokinetic modeling is considered a valuable tool for predicting pharmacokinetic changes in pregnancy to subsequently guide in-vivo pharmacokinetic trials in pregnant women. The objective of this study was to extend and verify a previously developed physiologically based pharmacokinetic model for pregnant women for the prediction of pharmacokinetics of drugs metabolized via several cytochrome P450 enzymes.

METHODS

Quantitative information on gestation-specific changes in enzyme activity available in the literature was incorporated in a pregnancy physiologically based pharmacokinetic model and the pharmacokinetics of eight drugs metabolized via one or multiple cytochrome P450 enzymes was predicted. The tested drugs were caffeine, midazolam, nifedipine, metoprolol, ondansetron, granisetron, diazepam, and metronidazole. Pharmacokinetic predictions were evaluated by comparison with in-vivo pharmacokinetic data obtained from the literature.

RESULTS

The pregnancy physiologically based pharmacokinetic model successfully predicted the pharmacokinetics of all tested drugs. The observed pregnancy-induced pharmacokinetic changes were qualitatively and quantitatively reasonably well predicted for all drugs. Ninety-seven percent of the mean plasma concentrations predicted in pregnant women fell within a twofold error range and 63% within a 1.25-fold error range. For all drugs, the predicted area under the concentration-time curve was within a 1.25-fold error range.

CONCLUSION

The presented pregnancy physiologically based pharmacokinetic model can quantitatively predict the pharmacokinetics of drugs that are metabolized via one or multiple cytochrome P450 enzymes by integrating prior knowledge of the pregnancy-related effect on these enzymes. This pregnancy physiologically based pharmacokinetic model may thus be used to identify potential exposure changes in pregnant women a priori and to eventually support informed decision making when clinical trials are designed in this special population.

Monoclonal Antibodies and Fc-Fusion Proteins for Pediatric Use: Dosing, Immunogenicity, and Modeling and Simulation in Data Submitted to the US Food and Drug Administration

The experience with the use of monoclonal antibodies and Fc-fusion proteins (mAb/Fc) in the pediatric population is limited. The objective of this study is to review those factors impacting the clinical efficacy and product safety of mAb/Fc products in pediatric patients during drug development. We reviewed the list of biologic products in the US Food and Drug Administration's Purple Book as of March 2018 with a focus on mAb/Fc products that are indicated for use in both adults and pediatric patients. Of 68 mAb/Fc products in the Purple Book (excluding biosimilars), 20 products have approved indications in both adults and children. Thirteen products had concurrent approval for both adult and pediatric populations. The sample size of pediatric studies generally ranged from approximately 2% to 70% of the sample size of adult studies with the same indication. In general, pediatric dosing regimens were found to be more based on body weight and weight tiered than the regimens for adults. Modeling and simulation techniques comprised mainly population pharmacokinetic and pharmacodynamic models. A review of the immunogenicity incidence did not reveal any notable difference in the 5 products having data on both pediatric and adult patients. In conclusion, most of the mAb/Fc products have a different weight-based dosing regimen for pediatric patients versus adults. An understanding of the comparative experience in drug development for mAb/Fc products between adult and pediatric patients coupled with the application of advanced modeling and simulation methods should assist future development of new mAb/Fc products for pediatric patients.

Specific Decoration of a Discrete Bismuth Oxido Cluster by Selected Peptides towards the Design of Metal Tags

Metal tags find application in a multitude of biomedical systems and the combination with laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) offers an opportunity for multiplexing. To lay the foundation for an increase of the signal intensities in such processes, we herein present a general approach for efficient functionalization of a well-defined metal oxido cluster [Bi₆ O₄ (OH)₄ (SO₃ CF₃ )₆ (CH₃ CN)₆ ]⋅2 CH₃ CN (1), which can be realized by selecting 7mer peptide sequences via combinatorial means from large one-bead one-compound peptide libraries. Selective cluster-binding peptide sequences (CBS) for 1 were discriminated from non-binders by treatment with H₂ S gas to form the reduction product Bi₂ S₃ , clearly visible to the naked eye. Interactions were further confirmed by NMR experiments. Extension of a binding peptide with a maleimide linker (Mal) introduces the possibility to covalently attach thiol-bearing moieties such as biological probes and for their analysis the presence of the cluster instead of mononuclear entities should lead to an increase of signal intensities in LA-ICP-MS measurements. To prove this, CBS-Mal was covalently bound onto thiol-presenting glass substrates, which then captured 1 effectively, so that LA-ICP-MS measurements demonstrated drastic signal amplification compared to single lanthanide tags.

Characterization of Maternal and Neonatal Pharmacokinetic Behavior of Ceftazidime

Ceftazidime is a parenteral cephalosporin frequently used in pregnant women for treatment of urinary tract or intrauterine infections. Despite its regular use in pregnant women, ceftazidime disposition in both mother and fetus is not well understood, and a pharmacokinetic (PK) model that allows characterization and simulation of both maternal and preterm neonatal ceftazidime disposition is not available. In this study, 10 pregnant women with suspected or proven intrauterine infections in the late second and early third trimester were treated with 1 g of ceftazidime intravenously every 6 hours. During ceftazidime treatment, one maternal and umbilical cord blood sample was taken at delivery to quantify ceftazidime concentrations in the mother and preterm neonate. Data showed that ceftazidime concentrations in the mother were comparable to those observed in the neonate. Based on these data, a PK model was developed to describe maternal disposition, ceftazidime distribution over the placenta, and elimination in the neonate. The maternal substructure of the model was parameterized according to a previously reported ceftazidime model with minor adjustments to account for pregnancy-related effects on renal elimination of ceftazidime. The expanded population PK model with an additional neonatal compartment was fitted to measured drug concentrations in the neonate. The neonatal elimination rate constant at delivery was close to that estimated for the mother. The presented results show that ceftazidime readily crosses the placenta and indicate that perinatal PK behavior of ceftazidime in preterm neonates can be expected to be similar to those observed in their mothers.