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.
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http://dx.doi.org/10.1002/psp4.12636 | DOI Listing |
PLoS One
January 2025
ESQlabs Gmbh, Saterland, Germany.
Digital twins, driven by data and mathematical modelling, have emerged as powerful tools for simulating complex biological systems. In this work, we focus on modelling the clearance on a liver-on-chip as a digital twin that closely mimics the clearance functionality of the human liver. Our approach involves the creation of a compartmental physiological model of the liver using ordinary differential equations (ODEs) to estimate pharmacokinetic (PK) parameters related to on-chip liver clearance.
View Article and Find Full Text PDFJ Psychopharmacol
January 2025
Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Background: Delirium is a severe neuropsychiatric disorder associated with increased morbidity and mortality. Numerous precipitating factors and etiologies merge into the pathophysiology of this condition which can be marked by agitation and psychosis. Judicious use of antipsychotic medications such as intravenous haloperidol reduces these symptoms and distress in critically ill individuals.
View Article and Find Full Text PDFClin Pharmacol Ther
January 2025
European Medicines Agency, Amsterdam, The Netherlands.
Physiologically Based Pharmacokinetic (PBPK) Models are routinely used in drug development and therefore appear frequently in marketing authorization applications (MAAs) to the European Medicines Agency (EMA). For a model to be a key source of evidence for a regulatory decision, it must be considered qualified for the intended use. Advice on the data expected to allow qualification of a PBPK model or platform is provided in the EMA Guideline on the reporting of PBPK modeling and simulation.
View Article and Find Full Text PDFCPT Pharmacometrics Syst Pharmacol
December 2024
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, USA.
Ritonavir (RTV) is a potent CYP3A inhibitor that is widely used as a pharmacokinetic (PK) enhancer to increase exposure to select protease inhibitors. However, as a strong and complex perpetrator of CYP3A interactions, RTV can also enhance the exposure of other co-administered CYP3A substrates, potentially causing toxicity. Therefore, the prediction of drug-drug interactions (DDIs) and estimation of dosing requirements for concomitantly administered drugs is imperative.
View Article and Find Full Text PDFClin Pharmacokinet
December 2024
School of Pharmacy, University of Waterloo, Kitchener, ON, Canada.
Background And Objective: Although breastfeeding ensures optimal infant development and maternal health, mothers taking medications may abandon breastfeeding because of uncertainties regarding toxicity to infants. Current methods in predicting infant risk to maternal medication exposure do not account for breastfeeding-related variability or in utero exposure via the umbilical cord (UC). Previously, our workflow integrated variability in infant anatomy and physiology, breast milk intake volume, and drug concentrations in breast milk using physiologically based pharmacokinetic (PBPK) modeling.
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