Development of Predictive Algorithms for In Silico Drug Toxicity and Efficacy Assessment

The aim and purpose of this proposal is to research and build a Quantum Intelligence System (QIS) and demonstrate its technical innovation and commercial feasibility for predicting in silico drug toxicity and efficacy. QIS integrates a collection of state-of-the-art data mining and optimization technologies. QIS first employs the best practices in database and data warehousing area to integrate the important information from diversified databases, then employs innovative data mining techniques which can are specially designed to handle large dimensional numeric and text data jointly to analyze, classify and predict the potential toxicity and efficacy of drug candidates. The effort is critical and significant because QIS technology make it possible to look at heterogeneous databases as a whole and study all the aspects of a drug discovery process jointly. So it is very likely that some previously unknown insight that could come out and lead to significant breakthrough. If successful, the resultant QIS can be applied to military defense interest of chemical and biological agents and pathogens. QIS should be also readily applicable to civil efforts of drug discovery. QIS would help drug candidates to "fail fast" before expensive later-phase trials, thus saving time and money.