Current Practices, Gap Analysis, and Proposed Workflows for PBPK Modeling of Cytochrome P450 Induction: An Industry Perspective

Assessment of the CYP3A4 Induction Potential by Carbamazepine: Insights from Two Clinical DDI Studies and PBPK Modeling

In the past, rifampicin was well-established as strong index CYP3A inducer in clinical drug-drug interaction (DDI) studies. However, due to identified potentially genotoxic nitrosamine impurities, it should not any longer be used in healthy volunteer studies. Available clinical data suggest carbamazepine as an alternative to rifampicin as strong index CYP3A4 inducer in clinical DDI studies. Further, physiologically-based pharmacokinetic (PBPK) modeling is a tool with increasing importance to support the DDI risk assessment of drugs during drug development. CYP3A4 induction properties and the safety profile of carbamazepine were investigated in two open-label, fixed sequence, crossover clinical pharmacology studies in healthy volunteers using midazolam as a sensitive index CYP3A4 substrate. Carbamazepine was up-titrated from 100 mg twice daily (b.i.d.) to 200 mg b.i.d., and to a final dose of 300 mg b.i.d. for 10 consecutive days. Mean area under plasma concentration-time curve from zero to infinity (AUC(0-∞)) of midazolam consistently decreased by 71.8% (ratio: 0.282, 90% confidence interval (CI): 0.235-0.340) and 67.7% (ratio: 0.323, 90% CI: 0.256-0.407) in study 1 and study 2, respectively. The effect was adequately described by an internally developed PBPK model for carbamazepine which has been made freely available to the scientific community. Further, carbamazepine was safe and well-tolerated in the investigated dosing regimen in healthy participants. The results demonstrated that the presented design is appropriate for the use of carbamazepine as alternative inducer to rifampicin in DDI studies acknowledging its CYP3A4 inductive potency and safety profile.

Dose Optimization Informed by PBPK Modeling: State-of-the Art and Future

Model-informed drug development (MIDD) is a powerful quantitative approach that plays an integral role in drug development and regulatory review. While applied throughout the life cycle of the development of new drugs, a key application of MIDD is to inform clinical trial design including dose selection and optimization. To date, physiologically-based pharmacokinetic (PBPK) modeling, an established component of the MIDD toolkit, has mainly been used for assessment of drug-drug interactions (DDIs) and consequential dose adjustments in regulatory submissions. As a result of recent scientific advances and growing confidence in the utility of the approach, PBPK models are being increasingly applied to provide dose recommendations for subjects with differing ages, genetics, and disease states. In this review, we present our perspective on the current landscape of regulatory acceptance of PBPK applications supported by relevant case studies. We also discuss the recent progress and future challenges associated with expanding the utility of PBPK models into emerging areas for regulatory decision making, especially dose optimization in highly vulnerable and understudied populations and facilitating diversity in clinical trials.

Understanding CYP3A4 and P-gp mediated drug-drug interactions through PBPK modeling - Case example of pralsetinib

Pralsetinib, a potent and selective inhibitor of oncogenic RET fusion and RET mutant proteins, is a substrate of the drug metabolizing enzyme CYP3A4 and a substrate of the efflux transporter P-gp based on in vitro data. Therefore, its pharmacokinetics (PKs) may be affected by co-administration of potent CYP3A4 inhibitors and inducers, P-gp inhibitors, and combined CYP3A4 and P-gp inhibitors. With the frequent overlap between CYP3A4 and P-gp substrates/inhibitors, pralsetinib is a challenging and representative example of the need to more quantitatively characterize transporter-enzyme interplay. A physiologically-based PK (PBPK) model for pralsetinib was developed to understand the victim drug-drug interaction (DDI) risk for pralsetinib. The key parameters driving the magnitude of pralsetinib DDIs, the P-gp intrinsic clearance and the fraction metabolized by CYP3A4, were determined from PBPK simulations that best captured observed DDIs from three clinical studies. Sensitivity analyses and scenario simulations were also conducted to ensure these key parameters were determined with sound mechanistic rationale based on current knowledge, including the worst-case scenarios. The verified pralsetinib PBPK model was then applied to predict the effect of other inhibitors and inducers on the PKs of pralsetinib. This work highlights the challenges in understanding DDIs when enzyme-transporter interplay occurs, and demonstrates an important strategy for differentiating enzyme/transporter contributions to enable PBPK predictions for untested scenarios and to inform labeling.

Study of the ketohexokinase inhibitor PF-06835919 as a clinical cytochrome P450 3A inducer: Integrated use of oral midazolam and liquid biopsy

PF-06835919, a ketohexokinase inhibitor, presented as an inducer of cytochrome P450 3A4 (CYP3A4) in vitro (human primary hepatocytes), and static mechanistic modeling exercises predicted significant induction in vivo (oral midazolam area under the plasma concentration-time curve [AUC] ratio [AUCR] = 0.23-0.79). Therefore, a drug-drug interaction study was conducted to evaluate the effect of multiple doses of PF-06835919 (300 mg once daily × 10 days; N = 10 healthy participants) on the pharmacokinetics of a single oral midazolam 7.5 mg dose. The adjusted geometric means for midazolam AUC and its maximal plasma concentration were similar following co-administration with PF-06835919 (vs. midazolam administration alone), with ratios of the adjusted geometric means (90% confidence interval [CI]) of 97.6% (90% CI: 79.9%-119%) and 98.9% (90% CI: 76.4%-128%), respectively, suggesting there was minimal effect of PF-06835919 on midazolam pharmacokinetics. Lack of CYP3A4 induction was confirmed after the preparation of subject plasma-derived small extracellular vesicles (sEVs) and conducting proteomic and activity (midazolam 1'-hydroxylase) analysis. Consistent with the midazolam AUCR observed, the CYP3A4 protein expression fold-induction (geometric mean, 90% CI) was low in liver (0.9, 90% CI: 0.7-1.2) and non-liver (0.9, 90% CI: 0.7-1.2) sEVs (predicted AUCR = 1.0, 90% CI: 0.9-1.2). Likewise, minimal induction of CYP3A4 activity (geometric mean, 90% CI) in both liver (1.1, 90% CI: 0.9-1.3) and non-liver (0.9, 90% CI: 0.5-1.5) sEVs was evident (predicted AUCR = 0.9, 90% CI: 0.6-1.4). The results showcase the integrated use of an oral CYP3A probe (midazolam) and plasma-derived sEVs to assess a drug candidate as inducer.

Physiologically Based Pharmacokinetic Modeling of Extracellular Vesicles

Extracellular vesicles (EVs) are lipid membrane bound-cell-derived structures that are a key player in intercellular communication and facilitate numerous cellular functions such as tumor growth, metastasis, immunosuppression, and angiogenesis. They can be used as a drug delivery platform because they can protect drugs from degradation and target specific cells or tissues. With the advancement in the technologies and methods in EV research, EV-therapeutics are one of the fast-growing domains in the human health sector. Therapeutic translation of EVs in clinics requires assessing the quality, safety, and efficacy of the EVs, in which pharmacokinetics is very crucial. We report here the application of physiologically based pharmacokinetic (PBPK) modeling as a principal tool for the prediction of absorption, distribution, metabolism, and excretion of EVs. To create a PBPK model of EVs, researchers would need to gather data on the size, shape, and composition of the EVs, as well as the physiological processes that affect their behavior in the body. The PBPK model would then be used to predict the pharmacokinetics of drugs delivered via EVs, such as the rate at which the drug is absorbed and distributed throughout the body, the rate at which it is metabolized and eliminated, and the maximum concentration of the drug in the body. This information can be used to optimize the design of EV-based drug delivery systems, including the size and composition of the EVs, the route of administration, and the dose of the drug. There has not been any dedicated review article that describes the PBPK modeling of EV. This review provides an overview of the absorption, distribution, metabolism, and excretion (ADME) phenomena of EVs. In addition, we will briefly describe the different computer-based modeling approaches that may help in the future of EV-based therapeutic research.

Drug-drug interactions that alter the exposure of glucuronidated drugs: Scope, UDP-glucuronosyltransferase (UGT) enzyme selectivity, mechanisms (inhibition and induction), and clinical significance

Drug-drug interactions (DDIs) arising from the perturbation of drug metabolising enzyme activities represent both a clinical problem and a potential economic loss for the pharmaceutical industry. DDIs involving glucuronidated drugs have historically attracted little attention and there is a perception that interactions are of minor clinical relevance. This review critically examines the scope and aetiology of DDIs that result in altered exposure of glucuronidated drugs. Interaction mechanisms, namely inhibition and induction of UDP-glucuronosyltransferase (UGT) enzymes and the potential interplay with drug transporters, are reviewed in detail, as is the clinical significance of known DDIs. Altered victim drug exposure arising from modulation of UGT enzyme activities is relatively common and, notably, the incidence and importance of UGT induction as a DDI mechanism is greater than generally believed. Numerous DDIs are clinically relevant, resulting in either loss of efficacy or an increased risk of adverse effects, necessitating dose individualisation. Several generalisations relating to the likelihood of DDIs can be drawn from the known substrate and inhibitor selectivities of UGT enzymes, highlighting the importance of comprehensive reaction phenotyping studies at an early stage of drug development. Further, rigorous assessment of the DDI liability of new chemical entities that undergo glucuronidation to a significant extent has been recommended recently by regulatory guidance. Although evidence-based approaches exist for the in vitro characterisation of UGT enzyme inhibition and induction, the availability of drugs considered appropriate for use as 'probe' substrates in clinical DDI studies is limited and this should be research priority.

Quantitative Cytochrome P450 3A4 Induction Risk Assessment Using Human Hepatocytes Complemented with Pregnane X Receptor-Activating Profiles

Reliable in vitro to in vivo translation of cytochrome P450 (CYP) 3A4 induction potential is essential to support risk mitigation for compounds during pharmaceutical discovery and development. In this study, a linear correlation of CYP3A4 mRNA induction potential in human hepatocytes with the respective pregnane-X receptor (PXR) activation in a reporter gene assay using DPX2 cells was successfully demonstrated for 13 clinically used drugs. Based on this correlation, using rifampicin as a positive control, the magnitude of CYP3A4 mRNA induction for 71 internal compounds at several concentrations up to 10 µM (n = 90) was predicted within 2-fold error for 64% of cases with only a few false positives (19%). Furthermore, the in vivo area under the curve reduction of probe CYP substrates was reasonably predicted for eight marketed drugs (carbamazepine, dexamethasone, enzalutamide, nevirapine, phenobarbital, phenytoin, rifampicin, and rufinamide) using the static net effect model using both the PXR activation and CYP3A4 mRNA induction data. The liver exit concentrations were used for the model in place of the inlet concentrations to avoid false positive predictions and the concentration achieving twofold induction (F2) was used to compensate for the lack of full induction kinetics due to cytotoxicity and solubility limitations in vitro. These findings can complement the currently available induction risk mitigation strategy and potentially influence the drug interaction modeling work conducted at clinical stages. SIGNIFICANCE STATEMENT: The established correlation of CYP3A4 mRNA in human hepatocytes to PXR activation provides a clear cut-off to identify a compound showing an in vitro induction risk, complementing current regulatory guidance. Also, the demonstrated in vitro-in vivo translation of induction data strongly supports a clinical development program although limitations remain for drug candidates showing complex disposition pathways, such as involvement of auto-inhibition/induction, active transport and high protein binding.

Involvement of Transporters in Intestinal Drug-Drug Interactions of Oral Targeted Anticancer Drugs Assessed by Changes in Drug Absorption Time

(1) Background: Oral targeted anticancer drugs are victims of presystemic pharmacokinetic drug−drug interactions (DDI). Identification of the nature of these DDIs, i.e., enzyme-based or/and transporter-based, is challenging, since most of these drugs are substrates of intestinal and/or hepatic cytochrome P-450 enzymes and of intestinal membrane transporters. (2) Methods: Variations in mean absorption time (MAT) between DDIs and control period (MAT ratios < 0.77 or >1.30) have been proposed to implicate transporters in DDIs at the intestinal level. This methodology has been applied to a large set of oral targeted anticancer drugs (n = 54, involved in 77 DDI studies), from DDI studies available either in the international literature and/or in publicly accessible FDA files. (3) Results: Significant variations in MAT were evidenced in 33 DDI studies, 12 of which could be explained by modulation of an efflux transporter. In 21 DDI studies, modulation of efflux transporters could not explain the MAT variation, suggesting a possible relevant role of influx transporters in the intestinal absorption. (4) Conclusions: This methodology allows one to suggest the involvement of intestinal transporters in DDIs, and should be used in conjunction with in vitro methodologies to help understanding the origin of DDIs.

Alternatives to rifampicin: A review and perspectives on the choice of strong CYP3A inducers for clinical drug-drug interaction studies

N-Nitrosamine (NA) impurities are considered genotoxic and have gained attention due to the recall of several marketed drug products associated with higher-than-permitted limits of these impurities. Rifampicin is an index inducer of multiple cytochrome P450s (CYPs) including CYP2B6, 2C8, 2C9, 2C19, and 3A4/5 and an inhibitor of OATP1B transporters (single dose). Hence, rifampicin is used extensively in clinical studies to assess drug-drug interactions (DDIs). Despite NA impurities being reported in rifampicin and rifapentine above the acceptable limits, these critical anti-infective drugs are available for therapeutic use considering their benefit-risk profile. Reports of NA impurities in rifampicin products have created uncertainty around using rifampicin in clinical DDI studies, especially in healthy volunteers. Hence, a systematic investigation through a literature search was performed to determine possible alternative index inducer(s) to rifampicin. The available strong CYP3A inducers were selected from the University of Washington DDI Database and their in vivo DDI potential assessed using the data from clinical DDI studies with sensitive CYP3A substrates. To propose potential alternative CYP3A inducers, factors including lack of genotoxic potential, adequate safety, feasibility of multiple dose administration to healthy volunteers, and robust in vivo evidence of induction of CYP3A were considered. Based on the qualifying criteria, carbamazepine, phenytoin, and lumacaftor were identified to be the most promising alternatives to rifampicin for conducting CYP3A induction DDI studies. Strengths and limitations of the proposed alternative CYP3A inducers, the magnitude of in vivo CYP3A induction, appropriate study designs for each alternative inducer, and future perspectives are presented in this paper.

Atypical kinetics of cytochrome P450 enzymes in pharmacology and toxicology

Atypical kinetics are observed in metabolic reactions catalyzed by cytochrome P450 enzymes (P450). Yet, this phenomenon is regarded as experimental artifacts in some instances despite increasing evidence challenging the assumptions of typical Michaelis-Menten kinetics. As P450 play a major role in the metabolism of a wide range of substrates including drugs and endogenous compounds, it becomes critical to consider the impact of atypical kinetics on the accuracy of estimated kinetic and inhibitory parameters which could affect extrapolation of pharmacological and toxicological implications. The first half of this book chapter will focus on atypical non-Michaelis-Menten kinetics (e.g. substrate inhibition, biphasic and sigmoidal kinetics) as well as proposed underlying mechanisms supported by recent insights in mechanistic enzymology. In particular, substrate inhibition kinetics in P450 as well as concurrent drug inhibition of P450 in the presence of substrate inhibition will be further discussed. Moreover, mounting evidence has revealed that despite the high degree of sequence homology between CYP3A isoforms (i.e. CYP3A4 and CYP3A5), they have the propensities to exhibit vastly different susceptibilities and potencies of mechanism-based inactivation (MBI) with a common drug inhibitor. These experimental observations pertaining to the presence of these atypical isoform- and probe substrate-specific complexities in CYP3A isoforms by several clinically-relevant drugs will therefore be expounded and elaborated upon in the second half of this book chapter.

Novel Insights in Drug Transporter Sciences: the Year 2021 in Review

On behalf of the team I am pleased to present the second annual 'novel insights into drug transporter sciences review' focused on peer-reviewed articles that were published in the year 2021. In compiling the articles for inclusion, preprints available in 2021 but officially published in 2022 were considered to be in scope. To support this review the contributing authors independently selected one or two articles that were thought to be impactful and of interest to the broader research community. A similar approach as published last year was adopted whereby key observations, methods and analysis of each paper is concisely summarized in the synopsis followed by a commentary highlighting the impact of the paper in understanding of drug transporters' role in drug disposition.As the goal of this review is not to provide a comprehensive overview of each paper but rather highlight important findings that are well supported by the data, the reader is encouraged to consult the original articles for additional information. Further, and keeping in line with the goals of this review, it should be noted that all authors actively contributed by writing synopsis and commentary for individual papers and no attempt was made to standardize language or writing styles. In this way, the review article is reflective of not only the diversity of the articles but also that of the contributors. I extend my thanks to the authors for their continued support and also welcome Diane Ramsden and Pallabi Mitra as contributing authors for this issue.

Quantitative Proteomics of Hepatic Drug-Metabolizing Enzymes and Transporters in Patients with Colorectal Cancer Metastasis

The impact of liver cancer metastasis on protein abundance of 22 drug‐metabolizing enzymes (DMEs) and 25 transporters was investigated using liquid chromatography‐tandem accurate mass spectrometry targeted proteomics. Microsomes were prepared from liver tissue taken from 15 healthy individuals and 18 patients with cancer (2 primary and 16 metastatic). Patient samples included tumors and matching histologically normal tissue. The levels of cytochrome P450 (CYPs 2B6, 2D6, 2E1, 3A4, and 3A5) and uridine 5′‐diphospho‐glucuronosyltransferases (UGTs 1A1, 1A6, 1A9, 2B15, 2B4, and 2B7) were lower in histologically normal tissue from patients relative to healthy controls (up to 6.6‐fold) and decreased further in tumors (up to 21‐fold for CYPs and 58‐fold for UGTs). BSEP and MRPs were also suppressed in histologically normal (up to 3.1‐fold) and tumorous tissue (up to 6.3‐fold) relative to healthy individuals. Abundance of OCT3, OAT2, OAT7, and OATPs followed similar trends (up to 2.9‐fold lower in histologically normal tissue and up to 16‐fold lower in tumors). Abundance of NTCP and OCT1 was also lower (up to 9‐fold). Interestingly, monocarboxylate transporter MCT1 was more abundant (3.3‐fold) in tumors, the only protein target to show this pattern. These perturbations could be attributed to inflammation. Interindividual variability was substantially higher in patients with cancer. Proteomics‐informed physiologically‐based pharmacokinetic (PBPK) models of 50 drugs with different attributes and hepatic extraction ratios (Simcyp) showed substantially lower drug clearance with cancer‐specific parameters compared with default parameters. In conclusion, this study provides values for decreased abundance of DMEs and transporters in liver cancer, which enables using population‐specific abundance for these patients in PBPK modeling.