R. El Cheikh (1), DC. Imbs (1), C. Faivre (1), J. ciccolini (1), A. Illiadis (1) and D. Barbolosi (1)
(1) Department of Pharmacokinetics, Inserm S_911 CRO2, Faculty of Pharmacy, University of Aix-Marseille, Marseille, France
Objectives: : To find new optimized temporal protocols for the combined administration of etoposide/cisplatin for small cell lung cancer (SCLC) treatment.
Methods: A PK/PD mathematical model that describes the effects of etoposide and cisplatin combination for SCLC treatment was developed. The model takes into consideration both the efficacy of drugs and their hematologic toxicity. It includes three components: the first one describes drug concentrations using compartment models, the second one is a delay differential equation system describing the hematopoietic chain and the last one describes tumor growth following a Gompertzian law. An interface model, that proved to link accurately the drugs concentrations to the perturbation of the hematopoietic chain and tumor regression, was used [1]. Model parameters were adjusted so that our simulations agree with experimental data. Through optimization techniques, the model was capable of proposing new temporal protocols that respect toxicity constraints and achieve acceptable tumor regression.
Results: Three new temporal protocols are proposed. All of them respect toxicity constraints and achieve better or similar tumor regression compared to standard protocols.
Protocol OP1 (4 cycles of 21 days): etoposide 3×80mg/m2 0h-1h, 14h-46h, 48h-72h; cisplatin 1×80mg/m2 1h-2h.
Protocol OP2 (4 cycles of 21 days): 1×72mg/m2 0h-1h, 1×96mg/m2 12h-33h, 1×68mg/m2 40h-69h, 1×52mg/m2 72h-93h, 1×112mg/m2 96h-119h; cisplatin 1×105mg/m2 1h-2h.
Protocol OP3 (intensified 6 cycles of 14 days): etoposide 1×42mg/m2 0h-1h, 1×50mg/m2 6h-30h, 1×67mg/m2 32h-72h; cisplatin 1×54mg/m2 3h-4h
Conclusions: Standard empirical approaches for optimizing drug dosing and scheduling in patients are now of limited utility as a result of the ever-growing numbers of druggable molecular targets and possible drug combinations. Consequently, mathematical modeling can play a substantial role in improving cancer treatments [2]. Mathematical models, as the one we propose here, are capable of testing in silico a huge number of protocols (different doses and schedules) and extract the optimized ones that meet the required toxicity-efficacy balance.
References:
[1] Meille C., Iliadis A., Barbolosi D., Frances N., and Freyer G. An interface
model for dosage adjustment connects hematotoxicity to pharmacokinzetcs. J. Pharmacokinet Pharmacodyn. DOI 10.1007/s10928-008-9106-4
[2] Barbolosi D., Ciccolini J., Lacarelle B., Barlési F. and André N. Computational oncology – mathematical modelling of drug regimens for precision medicine. Nat Rev Clin Oncol. 2015 Nov 24. doi: 10.1038/nrclinonc.2015.204
Reference: PAGE 25 (2016) Abstr 5938 [www.page-meeting.org/?abstract=5938]
Poster: Drug/Disease modeling - Oncology