Role of pharmacokinetic modeling and simulation in precision dosing of anticancer drugs

In drug development, late phase clinical trials often aim to establish uniform dosing, balancing efficacy and toxicity, across the patient population from a limited set of proposed dosage schemes (1). Dosing of anticancer drugs has traditionally been based on body surface area (BSA) under the assumption that there is a relationship between BSA and clearance (CL) or volume of distribution (Vd). However, this relationship is in many instances poor and may therefore not accurately reflect the change in drug exposure seen across the population (2-5), meaning variability in drug exposure may remain high at the established dosage regimen (5). This is particularly true when the drug is dosed in a more diverse patient population in clinical practice, such as: complex drug-drug interactions (DDIs), pediatric patients, and renally/hepatically impaired or other special populations (6). Explicit dosage recommendations are often absent from the drug label for most special populations at the time of approval (7). These factors contribute to variable clinical practices, where clinicians are challenged to make decisions based on experience and the many times limited literature. Patients with multiple comorbidities/co-medication are therefore at risk of suboptimal pharmacotherapy that may lead to unacceptable levels of toxicity or reduced efficacy (6,8,9). Model-informed precision dosing (MIPD) provides a quantitative framework for achieving the accurate dose for the individual patient through statistical and/or mathematical modeling, such as pharmacokinetic (PK) modeling, by accounting for inter-individual variability (IIV), and other factors that lead to variable drug exposure and/or pharmacodynamic (PD) response (10)