Abstract A36: An anticancer drug combination and regimen database for research and clinical optimization.

Abstract

Physiomics and pharmacometrics have collaborated to design a new database of anti-cancer drugs and therapeutic treatment information aimed at researchers in oncology and clinicians. This database, accessible through the web, offers data on more than 130 anti-cancer drugs (small molecules and biologics) used in research and in the clinic. It contains information on drug combination as well as a several hundreds of cancer chemotherapy regimens routinely used in the clinic. These data are classified according to tumor type, species, or source (in vitro, in vivo or simulated). It will be constantly expanded and curated with the most recent information. Furthermore, it provides ways to standardize the expression and nomenclature of chemotherapy regimens unambiguously and uniformly is of paramount importance to improve efficacy, as well as to reduce medication errors. Individual drug information covers pharmacokinetic profiles, mechanism of action and of resistance, dose-response effect, dosing limits, therapeutic index, and immunosuppression data. Drug combinations are also referenced. The database covers synergy or antagonism, as well as a combination therapeutic index and cross-resistance information. Some drug combination having level of synergy depending on the drug schedule, drug sequence and administration timings are also referenced and thoroughly discussed. The user can also browse and compare chemotherapeutic regimens, analyze the overall drug dose over a course of treatment, by tumor type, in animal and clinical models. Advanced functions include the ability to do statistical analysis on drug usage and dosing in various contexts. It can also help determine which drug candidates are likely to be used in combination with a new chemical or biological entity, given the mechanism of action and other PK/PD data. Also, it will allow users to design new combinations and regimens, which obey dosing constraints, such as MLD and MTD. Finally, data can be exported and used in spread sheets, modeling software or simulation packages. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr A36.