Firm will use its COSS platform to identify treatments based on specific patient pathophysiologies.
Drug repositioning specialist Biovista’s European affiliate has been awarded a $0.5 million grant to fund its participation in the European Commission’s €13.3 million (roughly $19.7 million), four-year p-medicine project focused on developing new tools and virtual physiological human (VPH) models to speed the development of personalized medicine. Biovista’s involvement in the 7th Framework program will hinge on use of its Clinical Outcome Search Space (COSS) platform and profiling capabilities to identify therapeutics suitable for patients based on their pathophysiological characteristics.
Biovista is exploiting its technologies to reposition existing drugs for new therapeutic applications. The firm’s programs are focused on multiple disease areas including eye disorders, diabetes/obesity, CNS disorders, and cancer. Its pipeline also includes work on 28 drugs that have recently, or will over the next year, come off patent.
Award of the European Commission Grant follows just a month after Biovista established a research collaboration agreement with Novartis focused on using the COSS platform to identify new indications for a number of Novartis compounds.
Biovista also offers pharma services that combine predictive modelling capabilities for adverse event profiling and drug repositioning. The firm claims its technologies can be applied to a range of areas including: benefit/risk assessment and evaluation, establishing risk evaluation and mitigation strategies, pinpointing the causes of adverse events leading to clinical hold or drug development withdrawal, and identifying potentially new indications for off-patent of failed drugs.
The p-medicine project aims to exploit data emerging from postgenomic research combined with genetic and clinical trials, and informatics initiatives to drive the development of individualized therapeutics. A major focus will be on formulating an open, modular framework of tools and services for running VPH simulations for clinical decision support, and building a p-medicine workbench as a central access point for tools, models, services workflows, and data resources.
The initiative will facilitiate the secure sharing and handling of large personalized datasets, as well as develop VPH multiscale simulations that build on standards-compliant tools and models for VPH research, and build tools for large-scale, privacy-preserving data and literature mining.
