Eric Fernandez, Jianxiong Pang, Chris Snell, Cheryl Turner, Cathy Derow, Frances Brightman, Christophe Chassagnole and Robert Jackson
Physiomics plc, The Oxford Science Park, Oxford OX4 4GA and Pharmacometrics Ltd, Southend-on-Sea SS2 6HZ
Objectives: Physiomics and Pharmacometrics have collaborated to design a new database of anti-cancer drugs and therapeutic treatment information. The objective is to provide PKPD data, regimens and combinations for use by clinicians and researchers in oncology.
Methods: The drugCARD 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 combinations as well as several hundreds of cancer chemotherapy regimens used routinely in the clinic. The data are classified according to tumour type, species and experimental system (in vitro or in vivo). A new search engine, based on Apache Solr™ [1], has been integrated, allowing users to perform powerful reliable and faceted search on any term and fields of the database.
Results: Individual drug information contained within the database comprises PK profiles, mechanisms of action and resistance, dose-response effect, dosing limits, therapeutic index and immunosuppression data. Drug combinations where the level of synergy is dependent upon the drug schedule, drug sequence or administration timing are also referenced and thoroughly discussed. The database covers synergy or antagonism, and includes the combination therapeutic index and cross-resistance information. The user can browse and compare chemotherapeutic regimens, and analyse the overall drug dose over a course of treatment, by tumour type, in animal and clinical models. Data can be exported for analysis in spreadsheets, modelling software or simulation packages.
Conclusions: The database enables users to design new combinations and regimens that obey dosing constraints (such as MLD and MTD), and can be used to determine drug candidates that could be combined with a new chemical or biological entity, given the respective mechanisms of action and other PK/PD data. Also, the database allows the expression and nomenclature of chemotherapy regimens to be standardized, which is of paramount importance in improving efficacy, as well as reducing medication errors [2].
References:
[1] The Apache Software Fundation. Apache Solr™. http://lucene.apache.org/solr/
[2] Kohler et al. (1998) Standardizing the expression and nomenclature of cancer treatment regimens. J Oncol Pharm Pract, 4(1), 23-31.
Reference: PAGE 22 (2013) Abstr 2838 [www.page-meeting.org/?abstract=2838]
Poster: Oncology