title: Biomarker- versus drug-driven tumor growth inhibition models: an equivalence analysis.
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.
authors.affiliation: Dipartimento di Ingegneria Industriale e dell'Informazione, Università di Pavia, Via Ferrata 1, 27100, Pavia, Italy. marialuisa.sardu@unipv.it.
authors.forename: Maria Luisa
authors.initials: ML
authors.lastname: Sardu
authors.affiliation: Clinical Pharmacology & Pharmacometrics, Janssen Research & Development, 2340, Beerse, Belgium.
authors.forename: Italo
authors.initials: I
authors.lastname: Poggesi
authors.affiliation: Dipartimento di Ingegneria Industriale e dell'Informazione, Università di Pavia, Via Ferrata 1, 27100, Pavia, Italy.
authors.forename: Giuseppe
authors.initials: G
authors.lastname: De Nicolao
mesh_terms: D000818:Animals; D000970:Antineoplastic Agents / Q000494:pharmacology*; D014408:Biomarkers, Tumor / Q000378:metabolism*; D045744:Cell Line, Tumor; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D006801:Humans; D051379:Mice; D008954:Models, Biological; D015233:Models, Statistical; D009369:Neoplasms / Q000188:drug therapy* / Q000378:metabolism / Q000473:pathology; D013997:Time Factors; D047368:Tumor Burden / Q000187:drug effects; D023041:Xenograft Model Antitumor Assays
chemical_list: D000970:Antineoplastic Agents; D014408:Biomarkers, Tumor
keywords: Biomarkers; Causal pathways; PK–PD models; Simeoni model; Tumor growth inhibition; Xenograft experiments