Mathematical modeling of tumor growth and tumor growth inhibition in oncology drug development.
BACKGROUND
Approaches aiming to model the time course of tumor growth and tumor growth inhibition following a therapeutic intervention have recently been proposed for supporting decision making in oncology drug development. When considered in a comprehensive model-based approach, tumor growth can be included in the cascade of quantitative and causally related markers that lead to the prediction of survival, the final clinical response.


METHODS
The authors examine articles dealing with the modeling of tumor growth and tumor growth inhibition in both preclinical and clinical settings. In addition, the authors review models describing how pharmacological markers can be used to predict tumor growth and models describing how tumor growth can be linked to survival endpoints.


CONCLUSIONS
Approaches and success stories of application of model-based drug development centered on tumor growth modeling are growing. It is also apparent that these approaches can answer practical questions on drug development more effectively than that in the past. For modeling purposes, some improvements are still needed related to study design and data quality. Further efforts are needed to encourage the mind shift from a simple description of data to the prediction of untested conditions that modeling approaches allow.
Clinical Pharmacology, Janssen Research and Development, LLC, Raritan, NJ, USA. abernar8@its.jnj.com
Apexa
A
Bernard
Holly
H
Kimko
Dinesh
D
Mital
Italo
I
Poggesi
D000818:Animals; D000970:Antineoplastic Agents / Q000493:pharmacokinetics / Q000494:pharmacology; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D036262:Empirical Research; D023381:Endpoint Determination; D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000188:drug therapy*; D012107:Research Design
D000970:Antineoplastic Agents