Pharmacodynamic biomarkers in model-based drug development in oncology

Introduction: Model-based drug development (MBDD) is recognized as an initiative able to improve success rates in the development of new anti-cancer agents. The use of pharmacodynamic (PD) biomarkers may be valuable in this context. The implementation of biomarkers in MBDD in oncology is the subject of this review. Methods: Literature was searched for articles and relevant conference abstracts concerning application of biomarkers in MBDD in oncology. First, papers are discussed concerning the use of biomarkers in modeling and simulation analyses in preclinical and early clinical phases of drug development. Subsequently, articles concerning late-stage clinical drug development are discussed. Results: Only a limited set of articles and conference presentations were identified. As expected, the majority of publications are concerned with targeted anti-cancer drugs. In the early development of novel anti-cancer agents, most publications concerned to the evaluation of dosing regimens for further clinical evaluation, or the identification of the required levels of target modulation. In general, combined analysis of clinical and preclinical data provide the most informative analyses. The use of biomarkers in late-stage drug development has mainly been confined to the prediction of phase III outcome on the basis of tumor growth data obtained from phase II trials, with tumor growth as biomarker for outcome. Conclusion: The use of suitable biomarkers in MBDD, has shown its merits in oncology, especially in early clinical development. Considering the low number of reports in literature, we would propose a more active use of presented techniques during all developmental phases of new anticancer agents.