Multi-scale Systems Pharmacology to Personalize Anticancer Drug Combination and Schedule
The quest for personalized cancer management has fostered the development of new technologies enabling the longitudinal assessment of patient- and tumor-specific features at the molecular, tissue and whole organism scales. To ensure the translation of these multi-type datasets into individualized therapies and subsequent patient benefit, systems pharmacology approaches are required. I design mathematical models representing the intracellular networks of proteins involved in drug pharmacokinetics-pharmacodynamics (PK-PD), DNA damage response, cell proliferation and cell death, which constitute a reliable physiological basis for the prediction of drug cytotoxicity. Both cancer and normal tissues are represented as a collection of heterogenous cell subtypes of different maturity and drug sensitivity. The therapeutic optimization builds on the identification of molecular and dynamical differences between the tumor and healthy organs which are targets of treatment toxicities. Physiological rhythms over the 24h span are further included as a major domain of host-tumor differences since normal tissues usually display a robust circadian organization that may be disrupted in malignant tumors. Because this complex molecular physiology and its temporal organization are unlikely to be completely assessed directly in individual cancer patients, I develop multi-scale methodologies integrating in vitro, pre-clinical and clinical investigations towards the design of patient-specific models and multi-drug therapies. I am currently developping such approaches to personalize i) temozolomide-based combination therapies against glioblastoma and ii) irinotecan, oxaliplatin and 5-fluorouracil association to targeted molecules in the context of digestive cancers.
Chercheuse INSERM, Responsable d'équipe ATIP-Avenir
Domain 3 - U900 - CBIO - Bioinformatics, Biostatistics Epidemiology and Computational Systems