Team Leader
Team Staff
Institute Presentation
In Silico Biosciences has a proven track record of developing validated mechanistic mathematical QSP models of the pathophysiology of CNS diseases such as schizophrenia, Alzheimer’s, and Parkinson’s disease. The integration of current knowledge from many sources is applied to better understand the systemic physiological disease processes at the neuronal circuit level. Our purpose is to significantly aid in the discovery, development, and clinical delivery of medications by creating and using the latest tools available for quantitative systems pharmacology.
For the QSPainRelief initiative, In Silico Biosciences contributed to the development of a validated QSPainRelief modelling platform that is able to adequately predict analgesic efficacy and side effect potential for new combinations of existing CNS drugs to treat chronic pain. The QSPainRelief model platform is based on the integration of CNS drug distribution (ULEI), target site interaction (ULEI), and subsequent neuronal circuit activations for pain relief. Our overall aim was to systematically optimise analgesic efficacy over side-effects by modelling biophysically realistic neuronal circuits to determine poly-pharmaceutical dose-response profiles in diverse patient populations.
Beyond the QSPainRelief project runtime, the model platform will be validated using preclinical and clinical data to enable greater generalizability and quantitative predictability for actual outcomes in clinical pain patient populations. The platform will be utilised for high-throughput systematic in silico screening of combinations of opioids with other CNS-active medications that are approved by the European Union to identify promising combinatorial pharmacotherapies for better treatment of chronic pain.