Abstract
Over the past few decades, physiologically-based pharmacokinetic modelling (PBPK) has been anticipated to be a powerful tool to improve the productivity of drug discovery and development. However, recently, multiple systematic evaluation studies independently suggested that the predictive power of current oral absorption (OA) PBPK models needs significant improvement. There is some disagreement between the industry and regulators about the credibility of OA PBPK modelling. Recently, the editorial board of AMDET&DMPK has announced the policy for the articles related to PBPK modelling (Modelling and simulation ethics). In this feature article, the background of this policy is explained: (1) Requirements for scientific writing of PBPK modelling, (2) Scientific literacy for PBPK modelling, and (3) Middle-out approaches. PBPK models are a useful tool if used correctly. This article will hopefully help advance the science of OA PBPK models.
Highlights
Over the past few decades, physiologically-based pharmacokinetic modelling (PBPK) has been anticipated to be a powerful tool to improve the productivity of drug discovery and development
Plenty of case study reports have been published in peer-reviewed journals, showing nearly perfect prediction, prediction error being much smaller than the variation in the clinical plasma concentration (Cp) - time profile. It seems that we already have achieved a “prediction paradise”[1]. ...Really? Recently, multiple systematic evaluation studies independently suggested that the “bottom-up” predictive power of current oral absorption (OA) PBPK models needs significant improvement [2,3,4,5,6]
There is some disagreement between the industry and regulators about the credibility of PBPK modelling [10,11]
Summary
Over the past few decades, physiologically-based pharmacokinetic modelling (PBPK) has been anticipated to be a powerful tool to improve the productivity of drug discovery and development. Plenty of case study reports have been published in peer-reviewed journals, showing nearly perfect prediction, prediction error being much smaller than the variation in the clinical plasma concentration (Cp) - time profile. It seems that we already have achieved a “prediction paradise”[1]. Almost all case studies had to use parameter optimization on a drug-by-drug basis to fit the simulated plasma concentration (Cp) - time curve to clinical data (Part 3, section 3.4). The purpose of PBPK modelling should be explained in the introduction section. The reason for selecting a PBPK model should be explained
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