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Sun M, Manson ML, Guo T, de Lange ECM. CNS Viral Infections-What to Consider for Improving Drug Treatment: A Plea for Using Mathematical Modeling Approaches. CNS Drugs 2024; 38:349-373. [PMID: 38580795 PMCID: PMC11026214 DOI: 10.1007/s40263-024-01082-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/10/2024] [Indexed: 04/07/2024]
Abstract
Neurotropic viruses may cause meningitis, myelitis, encephalitis, or meningoencephalitis. These inflammatory conditions of the central nervous system (CNS) may have serious and devastating consequences if not treated adequately. In this review, we first summarize how neurotropic viruses can enter the CNS by (1) crossing the blood-brain barrier or blood-cerebrospinal fluid barrier; (2) invading the nose via the olfactory route; or (3) invading the peripheral nervous system. Neurotropic viruses may then enter the intracellular space of brain cells via endocytosis and/or membrane fusion. Antiviral drugs are currently used for different viral CNS infections, even though their use and dosing regimens within the CNS, with the exception of acyclovir, are minimally supported by clinical evidence. We therefore provide considerations to optimize drug treatment(s) for these neurotropic viruses. Antiviral drugs should cross the blood-brain barrier/blood cerebrospinal fluid barrier and pass the brain cellular membrane to inhibit these viruses inside the brain cells. Some antiviral drugs may also require intracellular conversion into their active metabolite(s). This illustrates the need to better understand these mechanisms because these processes dictate drug exposure within the CNS that ultimately determine the success of antiviral drugs for CNS infections. Finally, we discuss mathematical model-based approaches for optimizing antiviral treatments. Thereby emphasizing the potential of CNS physiologically based pharmacokinetic models because direct measurement of brain intracellular exposure in living humans faces ethical restrictions. Existing physiologically based pharmacokinetic models combined with in vitro pharmacokinetic/pharmacodynamic information can be used to predict drug exposure and evaluate efficacy of antiviral drugs within the CNS, to ultimately optimize the treatments of CNS viral infections.
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Affiliation(s)
- Ming Sun
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Martijn L Manson
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Tingjie Guo
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Elizabeth C M de Lange
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Center for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands.
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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] [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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Shi M, Dong Y, Bouwmeester H, Rietjens IMCM, Strikwold M. In vitro-in silico-based prediction of inter-individual and inter-ethnic variations in the dose-dependent cardiotoxicity of R- and S-methadone in humans. Arch Toxicol 2022; 96:2361-2380. [PMID: 35604418 PMCID: PMC9217890 DOI: 10.1007/s00204-022-03309-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Accepted: 04/27/2022] [Indexed: 12/02/2022]
Abstract
New approach methodologies predicting human cardiotoxicity are of interest to support or even replace in vivo-based drug safety testing. The present study presents an in vitro–in silico approach to predict the effect of inter-individual and inter-ethnic kinetic variations in the cardiotoxicity of R- and S-methadone in the Caucasian and the Chinese population. In vitro cardiotoxicity data, and metabolic data obtained from two approaches, using either individual human liver microsomes or recombinant cytochrome P450 enzymes (rCYPs), were integrated with physiologically based kinetic (PBK) models and Monte Carlo simulations to predict inter-individual and inter-ethnic variations in methadone-induced cardiotoxicity. Chemical specific adjustment factors were defined and used to derive dose–response curves for the sensitive individuals. Our simulations indicated that Chinese are more sensitive towards methadone-induced cardiotoxicity with Margin of Safety values being generally two-fold lower than those for Caucasians for both methadone enantiomers. Individual PBK models using microsomes and PBK models using rCYPs combined with Monte Carlo simulations predicted similar inter-individual and inter-ethnic variations in methadone-induced cardiotoxicity. The present study illustrates how inter-individual and inter-ethnic variations in cardiotoxicity can be predicted by combining in vitro toxicity and metabolic data, PBK modelling and Monte Carlo simulations. The novel methodology can be used to enhance cardiac safety evaluations and risk assessment of chemicals.
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Affiliation(s)
- Miaoying Shi
- Division of Toxicology, Wageningen University, Stippeneng 4, 6708 WE, Wageningen, The Netherlands. .,NHC Key Laboratory of Food Safety Risk Assessment, Chinese Academy of Medical Sciences Research Unit (No. 2019RU014), China National Center for Food Safety Risk Assessment, Beijing, 100021, China.
| | - Yumeng Dong
- Division of Toxicology, Wageningen University, Stippeneng 4, 6708 WE, Wageningen, The Netherlands
| | - Hans Bouwmeester
- Division of Toxicology, Wageningen University, Stippeneng 4, 6708 WE, Wageningen, The Netherlands
| | - Ivonne M C M Rietjens
- Division of Toxicology, Wageningen University, Stippeneng 4, 6708 WE, Wageningen, The Netherlands
| | - Marije Strikwold
- Van Hall Larenstein University of Applied Sciences, 8901 BV, Leeuwarden, The Netherlands
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Sato M, Toshimoto K, Tomaru A, Yoshikado T, Tanaka Y, Hisaka A, Lee W, Sugiyama Y. Physiologically Based Pharmacokinetic Modeling of Bosentan Identifies the Saturable Hepatic Uptake As a Major Contributor to Its Nonlinear Pharmacokinetics. Drug Metab Dispos 2018; 46:740-748. [PMID: 29475833 DOI: 10.1124/dmd.117.078972] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Accepted: 02/21/2018] [Indexed: 01/02/2023] Open
Abstract
Bosentan is a substrate of hepatic uptake transporter organic anion-transporting polypeptides (OATPs), and undergoes extensive hepatic metabolism by cytochrome P450 (P450), namely, CYP3A4 and CYP2C9. Several clinical investigations have reported a nonlinear relationship between bosentan doses and its systemic exposure, which likely involves the saturation of OATP-mediated uptake, P450-mediated metabolism, or both in the liver. Yet, the underlying causes for the nonlinear bosentan pharmacokinetics are not fully delineated. To address this, we performed physiologically based pharmacokinetic (PBPK) modeling analyses for bosentan after its intravenous administration at different doses. As a bottom-up approach, PBPK modeling analyses were performed using in vitro kinetic parameters, other relevant parameters, and scaling factors. As top-down approaches, three different types of PBPK models that incorporate the saturation of hepatic uptake, metabolism, or both were compared. The prediction from the bottom-up approach (models 1 and 2) yielded blood bosentan concentration-time profiles and their systemic clearance values that were not in good agreement with the clinically observed data. From top-down approaches (models 3, 4, 5-1, and 5-2), the prediction accuracy was best only with the incorporation of the saturable hepatic uptake for bosentan. Taken together, the PBPK models for bosentan were successfully established, and the comparison of different PBPK models identified the saturation of the hepatic uptake process as a major contributing factor for the nonlinear pharmacokinetics of bosentan.
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Affiliation(s)
- Masanobu Sato
- Advanced Review with Electronic Data Promotion Group, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan (M.S.); Sugiyama Laboratory, RIKEN Innovation Center, Research Cluster for Innovation, RIKEN, Kanagawa, Japan (K.T., A.T., T.Y., Y.S.); DMPK Research Laboratory, Watarase Research Center, Kyorin Pharmaceutical Co., Ltd., Tochigi, Japan (Y.T); Graduate School and Faculty of Pharmaceutical Sciences, Chiba University, Chiba, Japan (A.H.); and College of Pharmacy, Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Korea (W.L.)
| | - Kota Toshimoto
- Advanced Review with Electronic Data Promotion Group, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan (M.S.); Sugiyama Laboratory, RIKEN Innovation Center, Research Cluster for Innovation, RIKEN, Kanagawa, Japan (K.T., A.T., T.Y., Y.S.); DMPK Research Laboratory, Watarase Research Center, Kyorin Pharmaceutical Co., Ltd., Tochigi, Japan (Y.T); Graduate School and Faculty of Pharmaceutical Sciences, Chiba University, Chiba, Japan (A.H.); and College of Pharmacy, Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Korea (W.L.)
| | - Atsuko Tomaru
- Advanced Review with Electronic Data Promotion Group, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan (M.S.); Sugiyama Laboratory, RIKEN Innovation Center, Research Cluster for Innovation, RIKEN, Kanagawa, Japan (K.T., A.T., T.Y., Y.S.); DMPK Research Laboratory, Watarase Research Center, Kyorin Pharmaceutical Co., Ltd., Tochigi, Japan (Y.T); Graduate School and Faculty of Pharmaceutical Sciences, Chiba University, Chiba, Japan (A.H.); and College of Pharmacy, Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Korea (W.L.)
| | - Takashi Yoshikado
- Advanced Review with Electronic Data Promotion Group, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan (M.S.); Sugiyama Laboratory, RIKEN Innovation Center, Research Cluster for Innovation, RIKEN, Kanagawa, Japan (K.T., A.T., T.Y., Y.S.); DMPK Research Laboratory, Watarase Research Center, Kyorin Pharmaceutical Co., Ltd., Tochigi, Japan (Y.T); Graduate School and Faculty of Pharmaceutical Sciences, Chiba University, Chiba, Japan (A.H.); and College of Pharmacy, Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Korea (W.L.)
| | - Yuta Tanaka
- Advanced Review with Electronic Data Promotion Group, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan (M.S.); Sugiyama Laboratory, RIKEN Innovation Center, Research Cluster for Innovation, RIKEN, Kanagawa, Japan (K.T., A.T., T.Y., Y.S.); DMPK Research Laboratory, Watarase Research Center, Kyorin Pharmaceutical Co., Ltd., Tochigi, Japan (Y.T); Graduate School and Faculty of Pharmaceutical Sciences, Chiba University, Chiba, Japan (A.H.); and College of Pharmacy, Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Korea (W.L.)
| | - Akihiro Hisaka
- Advanced Review with Electronic Data Promotion Group, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan (M.S.); Sugiyama Laboratory, RIKEN Innovation Center, Research Cluster for Innovation, RIKEN, Kanagawa, Japan (K.T., A.T., T.Y., Y.S.); DMPK Research Laboratory, Watarase Research Center, Kyorin Pharmaceutical Co., Ltd., Tochigi, Japan (Y.T); Graduate School and Faculty of Pharmaceutical Sciences, Chiba University, Chiba, Japan (A.H.); and College of Pharmacy, Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Korea (W.L.)
| | - Wooin Lee
- Advanced Review with Electronic Data Promotion Group, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan (M.S.); Sugiyama Laboratory, RIKEN Innovation Center, Research Cluster for Innovation, RIKEN, Kanagawa, Japan (K.T., A.T., T.Y., Y.S.); DMPK Research Laboratory, Watarase Research Center, Kyorin Pharmaceutical Co., Ltd., Tochigi, Japan (Y.T); Graduate School and Faculty of Pharmaceutical Sciences, Chiba University, Chiba, Japan (A.H.); and College of Pharmacy, Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Korea (W.L.)
| | - Yuichi Sugiyama
- Advanced Review with Electronic Data Promotion Group, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan (M.S.); Sugiyama Laboratory, RIKEN Innovation Center, Research Cluster for Innovation, RIKEN, Kanagawa, Japan (K.T., A.T., T.Y., Y.S.); DMPK Research Laboratory, Watarase Research Center, Kyorin Pharmaceutical Co., Ltd., Tochigi, Japan (Y.T); Graduate School and Faculty of Pharmaceutical Sciences, Chiba University, Chiba, Japan (A.H.); and College of Pharmacy, Research Institute of Pharmaceutical Sciences, Seoul National University, Seoul, Korea (W.L.)
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