The Society of Toxicology (SOT) Medical Device Specialty Section (MDSS) is hosting a lunchtime webinar presentation by Ron Brown on the topic “Use of Computational Toxicology for the Biological Evaluation of Medical Devices.” Dr. Brown is a toxicologist at the US Food and Drug Administration, Center for Devices and Radiological Health (CDRH), where he coordinates CDRH efforts in toxicological risk assessment and computational toxicology. Dr. Brown is a founding member and former President (2012–2013) of the MDSS and recently served as author of the chapter on toxicological risk assessment in, Biocompatibility and Performance of Medical Devices (J-P Boutrand, ed., Woodhead Publishing).
Please save the date for this informative event on June 23, 2014, 12:00 noon–1:00 pm EDT. Registration and other details are provided on the MDSS Event website.
Abstract:
The biological safety of medical devices is typically assessed by conducting biocompatibility testing of an extract of the device or the device itself; however, there is growing interest in an alternate approach that involves characterizing the chemical composition of the device extract and conducting a risk assessment on the compounds identified in the extract. One limitation to the practical implementation of this chemical characterization/risk assessment approach is the lack of toxicity data for many compounds released from device materials. To address this need, computational toxicology models, such as Quantitative Structure-Activity Relationship (QSAR) models, are being increasingly used to predict the toxicity or carcinogenicity of compounds based on their chemical structure. Efforts are underway to validate the predictive ability of QSAR models for compounds that are known to be released from device materials. This webinar will describe the computational modeling approaches available to predict the toxicity, mutagenicity, and carcinogenicity of compounds released from device materials and will explore ways to use model-derived predictions as part of the biological evaluation of a device, notably, to determine when certain types of testing may not be necessary.