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.

Liver cirrhosis is a chronic disease that affects the liver structure, protein expression, and overall metabolic function. Abundance data for drug-metabolizing enzymes and transporters (DMET) across all stages of disease severity are scarce. Levels of these proteins are crucial for the accurate prediction of drug clearance in hepatically impaired patients using physiologically based pharmacokinetic (PBPK) models, which can be used to guide the selection of more precise dosing. This study aimed to experimentally quantify these proteins in human liver samples and assess how they can impact the predictive performance of the PBPK models. We determined the absolute abundance of 51 DMET proteins in human liver microsomes across the three degrees of cirrhosis severity (n = 32; 6 mild, 13 moderate, and 13 severe), compared to histologically normal controls (n = 14), using QconCAT-based targeted proteomics. The results revealed a significant but non-uniform reduction in the abundance of enzymes and transporters, from control, by 30–50% in mild, 40–70% in moderate, and 50–90% in severe cirrhosis groups. Cancer and/or non-alcoholic fatty liver disease-related cirrhosis showed larger deterioration in levels of CYP3A4, 2C8, 2E1, 1A6, UGT2B4/7, CES1, FMO3/5, EPHX1, MGST1/3, BSEP, and OATP2B1 than the cholestasis set. Drug-specific pathways together with non-uniform changes of abundance across the enzymes and transporters under various degrees of cirrhosis necessitate the use of PBPK models. As case examples, such models for repaglinide, dabigatran, and zidovudine were successful in recovering disease-related alterations in drug exposure. In conclusion, the current study provides the biological rationale behind the absence of a single dose adjustment formula for all drugs in cirrhosis and demonstrates the utility of proteomics-informed PBPK modeling for drug-specific dose adjustment in liver cirrhosis.

Summary: Background: Prescription information for many drugs entering the market lacks dosage guidance for hepatic impairment. Dedicated studies for assessing the fate of drugs in hepatic impairment commonly stratify patients using Child‐Pugh score. Child‐Pugh is a prognostic clinical score with limitations in reflecting the liver's metabolic capacity.Aims: To demonstrate the need for better drug dosing approaches in hepatic impairment, summarise the current status, identify knowledge gaps related to drug kinetic parameters in hepatic impairment, propose solutions for predicting the liver disease impact on drug exposure and discuss barriers to dosing guidance in those patients.Methods: Relevant reports on dosage adjustment in hepatic impairment were analysed concerning the prediction of the impairment impact on drug kinetics using physiologically‐based pharmacokinetic (PBPK) modelling.Results: PBPK models are suggested as a potential framework to understand drug clearance changes in hepatic impairment. Quantifying changes in abundance and activity of drug‐metabolising enzymes and transporters, understanding the impact of shunting, and accounting for interindividual variations in drug absorption could help in extending the success of these models in hepatically‐impaired populations. These variables might not correlate with Child‐Pugh score as a whole. Therefore, new metabolic activity markers, imaging techniques and other scoring systems are proposed to either support or substitute Child‐Pugh score.Conclusions: Many physiological changes in hepatic impairment determining the fate of drugs do not necessarily correlate with Child‐Pugh score. Quantifying these changes in individual patients is essential in future hepatic impairment studies. Further studies assessing Child‐Pugh alternatives are recommended to allow better prediction of drug exposure.

ABC transporters (ATP‐binding cassette transporter) traffic drugs and their metabolites across membranes, making ABC transporter expression levels a key factor regulating local drug concentrations in different tissues and individuals. Yet, quantification of ABC transporters remains challenging because they are large and low‐abundance transmembrane proteins. Here, we analysed 200 samples of crude and membrane‐enriched fractions from human liver, kidney, intestine, brain microvessels and skin, by label‐free quantitative mass spectrometry. We identified 32 (out of 48) ABC transporters: ABCD3 was the most abundant in liver, whereas ABCA8, ABCB2/TAP1 and ABCE1 were detected in all tissues. Interestingly, this atlas unveiled that ABCB2/TAP1 may have TAP2‐independent functions in the brain and that biliary atresia (BA) and control livers have quite different ABC transporter profiles. We propose that meaningful biological information can be derived from a direct comparison of these data sets.

In-vitro in-vivo extrapolation (IVIVE) enables prediction of in vivo clinical outcomes related to drug exposure in various populations from in vitro data. Prudent IVIVE requires scalars specific to the biological characteristics of the system in each population. This study determined experimentally, for the first time, scalars in liver samples from patients with varying degrees of cirrhosis. Microsomal and cytosolic fractions were extracted from 13 non-cirrhotic and 32 cirrhotic livers (6 mild, 13 moderate, and 13 severe, based on Child-Pugh Score). Fractional protein content was determined and cytochrome P450 reductase activity was used to correct for microsomal protein loss. Although the median microsomal protein per gram liver (MPPGL) in mild, moderate, and severe cirrhosis (26.2, 32.4, and 30.8 mg.g^-1, respectively) seemed lower than control livers (36.6 mg.g^-1), differences were not statistically significant (Kruskal-Wallis test, p>0.05). Corresponding values for cytosolic protein per gram liver (CPPGL) were 88.2, 67.9, 62.2 and 75.4 (mg.g^-1) for mild, moderate, sever cirrhosis and control livers, respectively, with statistically lower values for server vs controls (Mann-Whitney p=0.006). Cirrhosis associated with cancer showed lower MPPGL (24.8 mg.g^-1) than cirrhosis associated with cholestasis (38.3 mg.g^-1, p=0.003). Physiologically-based pharmacokinetic simulations with disease-specific scalars captured cirrhosis impact on exposure to afentanil, metoprolol, midazolam, and ethinylestradiol. These experimentally-determined scalars should alleviate the need for indirect scaling using functional liver volume. Scaling factors in cirrhosis might be a reflection of the etiology rather than the disease severity. Hence, bundling various cirrhotic conditions under the same umbrella when predicting hepatic impairment impact should be revisited. Significance Statement Cirrhosis-specific scalars required for extrapolation from microsomal or cytosolic in vitro systems to liver tissue are lacking. These scalars can help in predicting drug clearane and selection of dosage regimens for cirrhosis populations. Attempts to consider potential changes have been empirical and ignored the potential impact of the cause of cirrhosis. We obtained experimental values for these scalars, for the first time, and assessed their impact on predicted exposure to various substrate drugs using PBPK simulations.