The quest to define cancer-specific systems parameters for personalized dosing in oncology.

Abstract

Introduction: Clinical trials in oncology initially recruit heterogeneous populations, without catering for all types of variability. The target cohort is often not representative, leading to variability in pharmacokinetics (PK). To address enrollment challenges in clinical trials, physiologically based pharmacokinetic models (PBPK) models can be used as a guide in the absence of large clinical studies. These models require patient-specific systems data relevant to the handling of drugs in the body for each type of cancer, which are scarce.

Areas covered: This review explores system parameters affecting PK in cancer and highlights important gaps in data. Changes in drug-metabolizing enzymes (DMEs) and transporters have not been fully investigated in cancer. Their impaired expression can significantly affect capacity for drug elimination. Finally, the use of PBPK modeling for precision dosing in oncology is highlighted. Google Scholar and PubMed were mainly used for literature search, without date restriction.

Expert opinion: Model-informed precision dosing is useful for dosing in sub-groups of cancer patients, which might not have been included in clinical trials. Systems parameters are not fully characterized in cancer cohorts, which are required in PBPK models. Generation of such data and application of cancer models in clinical practice should be encouraged.