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

Abstract

The International Consortium for Innovation and Quality (IQ) Physiologically Based Pharmacokinetic (PBPK) Modeling Induction Working Group (IWG) conducted a survey across participating companies around general strategies for PBPK modeling of induction, including experience with its utility to address various questions, regulatory interactions, and regulatory acceptance. The results highlight areas where PBPK modeling is used with high confidence and identifies opportunities where confidence is lower and further evaluation is needed. To enhance the survey results, the PBPK‐IWG also collected case studies and analyzed recent literature examples where PBPK models were applied to predict CYP3A induction‐mediated drug‐drug interactions. PBPK modeling of induction has evolved and progressed significantly, proving to have great potential to accelerate drug discovery and development. With the aim of enabling optimal use for new molecular entities that are either substrates and/or inducers of CYP3A, the PBPK‐IWG proposes initial workflows for PBPK application, discusses future trends, and identifies gaps that need to be addressed.

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

“…Nevertheless, it is important to note that the field of PBPK modeling of induction DDIs continues to advance, with notable recent progress made in the development and qualification of a model of rifampicin-mediated induction, also incorporating P-gp induction. 89,90 As the fidelity of PBPK models continues to grow, we trust that confidence in their application in lieu of clinical DDI studies should increase for suitable contexts of use.…”

“…Underprediction of DDIs with the rifampicin model along with lack of confidence in the predictability and reliable validation of the models were cited as reasons for not acceptability of modeling results. Nevertheless, it is important to note that the field of PBPK modeling of induction DDIs continues to advance, with notable recent progress made in the development and qualification of a model of rifampicin‐mediated induction, also incorporating P‐gp induction 89,90 . As the fidelity of PBPK models continues to grow, we trust that confidence in their application in lieu of clinical DDI studies should increase for suitable contexts of use.…”

Quantitative Proteomics of Hepatic Drug‐Metabolizing Enzymes and Transporters in Patients With Colorectal Cancer Metastasis

“…23 Understanding the range of values in individual patients is necessary for projecting potential clinical consequences of the changes in a probabilistic rather than deterministic PBPK predictions. 24 In this study, we quantified DMEs and transporters in healthy livers from healthy donors and compared with matched histologically normal and cancerous livers from patients with cancer. To our knowledge, this is the most comprehensive report of absolute quantitative measurements of DMEs and transporters using LC-MS proteomics in CRLM to date.…”

“…A preliminary experiment measured the abundance of DMEs and transporters in CRLM pooled samples 23 . Understanding the range of values in individual patients is necessary for projecting potential clinical consequences of the changes in a probabilistic rather than deterministic PBPK predictions 24 …”

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

“…Guidelines for investigation of induction DDI risk with both static and dynamic modeling have been provided by regulators (EMA 2012;FDA, 2020) (Huang et al, 2013) (Luzon et al, 2017) (Sato et al, 2017) and international harmonization efforts are in progress (ICH M12). Recently, the International Consortium for Innovation and Quality PBPK induction Working Group proposed initial roadmaps for PBPK application for induction DDI risk assessment and discussed future trends based on a survey across participating pharmaceutical industries (Hariparsad et al, 2021).…”