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Publication in JPKPD supported by DDMoRe

Biomarker- versus drug-driven tumor growth inhibition models: an equivalence analysis. Maria Luisa Sardu , Italo Poggesi, Giuseppe De Nicolao Journal of Pharmacokinetics and Pharmacodynamics 2015 p 1- 16

Abstract
The mathematical modeling of tumor xenograft experiments following the dosing of antitumor drugs has received much attention in the last decade. Biomarker data can further provide useful insights on the pathological processes and be used for translational purposes in the early clinical development. Therefore, it is of particular interest the development of integrated pharmacokinetic–pharmacodynamic (PK–PD) models encompassing drug, biomarker and tumor-size data. This paper investigates the reciprocal consistency of three types of models: drug-to-tumor, such as established drug-driven tumor growth inhibition (TGI) models, drug-to-biomarker, e.g. indirect response models, and biomarker-to-tumor, e.g. the more recent biomarker-driven TGI models. In particular, this paper derives a mathematical relationship that guarantees the steady-state equivalence of the cascade of drug-to-biomarker and biomarker-to-tumor models with a drug-to-tumor TGI model. Using the Simeoni TGI model as a reference, conditions for steady-state equivalence are worked out and used to derive a new biomarker-driven model. Simulated and real data are used to show that in realistic cases the steady-state equivalence extends also to transient responses. The possibility of predicting the drug-to-tumor potency of a new candidate drug based only on biomarker response is discussed.

Work package: 

Associated members

Academia
Giuseppe De Nicolao's picture
Giuseppe De Nicolao
Universita' degli Studi di Pavia
Paolo Magni's picture
Paolo Magni
Universita' degli Studi di Pavia
Maria Luisa Sardu's picture
Maria Luisa Sardu
ME