Physiologically Based Pharmacokinetic Modeling to Identify Physiological and Molecular Characteristics Driving Variability in Drug Exposure

Abstract

Prospectively defining the physiological and molecular characteristics most likely driving between-subject variability (BSV) in drug exposure provides the opportunity to inform the assessment of biomarkers to account for this variability. A physiologically based pharmacokinetic (PBPK) model was constructed and verified for dabrafenib. This model was then used to evaluate the physiological and molecular characteristics driving BSV in dabrafenib exposure. The capacity to discriminate a steady-state dabrafenib trough concentration >48 ng/mL was also evaluated. The mean simulated/observed ratios for the parameters describing dabrafenib exposure in single-dose, multiple-dose, and drug-drug interaction studies were between 0.78 and 1.23. Multivariable analysis indicated that consideration of baseline weight, body mass index, and CYP2C8, CYP3A4, and P-gp abundance strongly predicts steady-state dabrafenib trough concentration above 48 ng/mL (ROC AUC = 0.94; accuracy = 86%). This is the first study to use a verified PBPK model to identify baseline physiological and molecular characteristics driving BSV in drug exposure.

Use of Physiologically Based Pharmacokinetic Modeling to Identify Physiological and Molecular Characteristics Driving Variability in Axitinib Exposure: A Fresh Approach to Precision Dosing in Oncology

“…Furthermore, we and others have recently reported on the broader potential for predictive analytics with PBPK modeling as a novel strategy to optimize dosing for targeted anticancer medicines . PBPK models combine characteristics of the patient (“population variables”) with drug physiochemical and in vitro kinetic data (“drug variables”) to predict mechanistically drug exposure .…”

“…26 Furthermore, we and others have recently reported on the broader potential for predictive analytics with PBPK modeling as a novel strategy to optimize dosing for targeted anticancer medicines. [27][28][29][30] PBPK models combine characteristics of the patient ("population variables") with drug physiochemical and in vitro kinetic data ("drug variables") to predict mechanistically drug exposure. 31,32 This approach allows for interrogation of outputs at a physiological and molecular level to efficiently identify the key characteristics driving variability in drug exposure.…”

Toward Dynamic Prescribing Information: Codevelopment of Companion Model‐Informed Precision Dosing Tools in Drug Development

“…Guidelines for PBPK models are now available to improve the quality and consistency of applications by pharmaceutical companies to regulators . These guidelines are also being applied in academic‐initiated research . Modeling with PBPK is typically used to mitigate the requirement for PK drug‐drug interaction studies and dedicated PK studies in the “special populations,” such as pediatrics …”

“…When dose adjustment occurs, it is usually based on a single covariate such as body weight (eg, low‐molecular‐weight heparins) or renal function (eg, oseltamivir) . However, our understanding of PK/PD now goes beyond these simple covariates in the PI to include the “unseen” physiological and molecular determinants of drug disposition and response—DMET activities, organ sizes and blood flows, inflammatory status, gut microbiome, genetics of molecular targets, and so forth . The word unseen is used here because such covariates are either not currently tested for in clinical practice, or if they are tested for, most doctors are unclear about how to action the result, such as pharmacogenomic test results for DMETs, that is, the prescriber is literally blind to their importance.…”

“…In particular, the ability to determine accurately DMET activities in a given patient is urgently required. So are studies that investigate the value and practicality of implementing MIPD clinically, such as the repurposing of currently available PBPK platforms . Commercial incentives that encourage precision dosing in drug development may change the business environment if payers for drugs start to command value‐based or outcome‐based pricing.…”