Translational modeling and simulation approaches for molecularly targeted small molecule anticancer agents from bench to bedside

ABSTRACT

Introduction: Recent advances in molecular biology have enabled personalized cancer therapies with molecularly targeted agents (MTAs), which offer a promising future for cancer therapy. Dynamic modeling and simulation (M&S) is a powerful mathematical approach linking drug exposures to pharmacological responses, providing a quantitative assessment of in vivo drug potency. Accordingly, a growing emphasis is being placed upon M&S to quantitatively understand therapeutic exposure-response relationships of MTAs in nonclinical models.

Areas covered: An overview of M&S approaches for MTAs in nonclinical models is presented with discussion about mechanistic extrapolation of antitumor efficacy from bench to bedside. Emphasis is placed upon recent advances in M&S approaches linking drug exposures, biomarker responses (e.g. target modulation) and pharmacological outcomes (e.g. antitumor efficacy).

Expert opinion: For successful personalized cancer therapies with MTAs, it is critical to mechanistically and quantitatively understand their exposure-response relationships in nonclinical models, and to logically and properly apply such knowledge to the clinic. Particularly, M&S approaches to predict pharmacologically active concentrations of MTAs in patients based upon nonclinical data would be highly valuable in guiding the design and execution of clinical trials. Proactive approaches to understand their exposure-response relationships could substantially increase probability of achieving a positive proof-of-concept in the clinic.

KEYWORDS:

• Cancer
• drug-disease modeling
• mathematical modeling
• modeling and simulation
• molecularly targeted agents
• oncology
• targeted cancer therapies
• pharmacokinetic-pharmacodynamic modeling
• pharmacokinetic-disease modeling
• translational pharmacology
• tyrosine kinase inhibitor

Article highlights

• Recent advances in mathematical dynamic modeling & simulation (M&S) approaches to quantitatively estimate exposure–response relationships of molecularly targeted agents (MTAs) linking systemic exposures, pharmacodynamic biomarker responses (e.g. target modulation), and subsequent pharmacological outcomes (e.g. antitumor efficacy) in nonclinical tumor models.

• Key features of each mathematical model, such as pharmacokinetic-pharmacodynamic (PKPD) models for biomarker responses, pharmacokinetic-disease (PKDZ) models for antitumor efficacy, and integrated pharmacokinetic-pharmacodynamic-disease (PK-PDDZ) models, to establish exposure–response relationships of MTAs in a quantitative manner.

• Importance of projecting pharmacologically active concentrations in the clinic based upon nonclinical understandings of drug exposure–response relationships; this is particularly important in Phase I clinical trials for guiding dose escalation/de-escalation to maintain therapeutic plasma concentrations of MTAs and in contributing to go/no-go decisions through clinical drug development.

• Quantitatively understanding exposure–response relationships of MTAs in nonclinical models could be among the key drivers for successful translational pharmacology in personalized, targeted cancer therapies.

This box summarizes key points contained in the article.

Acknowledgment

The authors would like to thank Dr Bhasker Shetty, Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development (San Diego, CA) for helpful discussion and comments on this manuscript.

Declaration of interest

S Yamazaki is an employee of Pfizer, Inc.; ME Spilker is an employee of Pfizer, Inc.; P Vicini was an employee of Pfizer, Inc. and is currently employed by MedImmune. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.