Physiological‐based pharmacokinetic modeling trends in pharmaceutical drug development over the last 20‐years; in‐depth analysis of applications, organizations, and platforms

Abstract

We assess the advancement of physiologically based pharmacokinetic (PBPK) modeling and simulation (M&S) over the last 20 years (start of 2000 to end of 2019) focusing on the trends in each decade with the relative contributions from different organizations, areas of applications, and software tools used. Unlike many of the previous publications which focused on regulatory applications, our analysis is based on PBPK publications in peer‐reviewed journals based on a large sample (>700 original articles). We estimated a rate of growth for PBPK (>40 fold/20 years) that was much steeper than the general pharmacokinetic modeling (<3 fold/20 years) or overall scientific publications (∼3 fold/20 years). The analyses demonstrated that contrary to commonly held belief, commercial specialized PBPK platforms with graphical‐user interface were a much more popular choice than open‐source alternatives even within academic organizations. These platforms constituted 81% of the whole set of the sample we assessed. The major PBPK applications (top 3) were associated with the study design, predicting formulation effects, and metabolic drug–drug interactions, while studying the fate of drugs in special populations, predicting kinetics in early drug development, and investigating transporter drug interactions have increased proportionally over the last decade. The proportions of application areas based on published research were distinctively different from those shown previously for the regulatory submissions and impact on labels. This may demonstrate the lag time between the research applications versus verified usage within the regulatory framework. The report showed the trend of overall PBPK publications in pharmacology drug development from the past 2 decades stratified by the organizations involved, software used, and area of applications. The analysis showed a more rapid increase in PBPK than that of the pharmacokinetic space itself with an equal contribution from academia and industry. By establishing and recording the journey of PBPK modeling in the past and looking at its current status, the analysis can be used for devising plans based on the anticipated trajectory of future regulatory applications.

Physiologically‐based pharmacokinetic modeling to evaluate in vitro‐to‐in vivo extrapolation for intestinal P‐glycoprotein inhibition

“…Model‐informed drug discovery and development (MID3) has become an important framework to quantitatively maximize the benefit‐risk profiles of new molecular entities during their development. One of the critical components in the MID3 strategy is physiologically‐based pharmacokinetic (PBPK) modeling, which is a mechanistic framework to quantitatively describe in vivo drug disposition profiles based on drug‐ and system‐dependent parameters 1–3 . By integrating in vitro‐to‐in vivo extrapolation (IVIVE) with PBPK modeling, PBPK‐IVIVE is widely applied to predict in vivo disposition profiles of drugs in various clinical studies, such as drug‐drug, drug‐disease, and drug‐gene interactions, that have not been tested yet.…”

A latent variable approach to account for correlated inputs in global sensitivity analysis

“…Further, modelling activities are an important tool for supporting a wide variety of decisions in R&D and regulatory submissions. For this reason, dedicated user-friendly software platforms are widely used [ 13 ], facilitating standardisation and easy access for non-expert users. We suspect that this is likely to hold true across many different domains, and therefore relevant across areas of application.…”

Translational aspects of cytochrome P450‐mediated drug–drug interactions: A case study with clopidogrel

“…Thus, they allow for simultaneous modelling of multiple drug disposition processes, providing a range of opportunities, including simulation of CYP-mediated DDIs. 27,28 From a translational perspective, PBPK modelling can be seen as a sophisticated tool to bridge in vitro and in vivo DDI studies. It may also serve as a starting point to investigate novel DDI signals (Figure 1).…”

“…27 Modelling of CYP-mediated DDIs is most easily carried out using commercially available or freeware PBPK software, which provide the computational and physiological frameworks of the PBPK platform (Figure 3). 28 Accordingly, only building of the drug-dependent component of the model relies on the user. However, PBPK models require considerably more input data than static prediction approaches, and familiarity with the applied equations and assumptions is crucial.…”

“…However, PBPK models require considerably more input data than static prediction approaches, and familiarity with the applied equations and assumptions is crucial. 27,28 Ideally, separate sets of clinical data for model building and refinement (training set) and model verification are used, and acceptance criteria and purpose of the modelling are predefined. 25,27 In the ideal case, the models can be cross-verified using data from multiple clinical studies concerning both the perpetrator and the victim drug.…”