Modern drug discovery is an inefficient, expensive and risky process. The average cost of a successful drug introduction now exceeds $3bn, with a time to market in excess of 10 years. The consumption of patent life during R&D has a profound financial impact with the decreasing economic life of an approved drug leading to increased market costs. The key bottleneck and attrition point in drug discovery is the hit to lead transition from early hits identified by multiple approaches (including genomics, proteomics, high throughput screening, AI) and in vivo proof of target.
The inefficiencies in drug discovery and validation do not only impact the bottom line of Pharmaceutical and Biotechnological Companies but also translate into higher prices of medicines for patients and outstanding unmet need in many disease areas. Last but not least, the preclinical research imposes high ethical burden on animals as many need to be sacrificed in the process of drug validation.
Our AI-driven Drug-Disease matching platform works in concert with the patented multi-disease modeling technology facilitating more efficient and ethical drug development and positioning. The toolkit reduces the time to prepare animal models, and the cost of drug discovery and pre-clinical trials, by an order of magnitude. The impact of this is cheaper, more rapidly developed drugs, with a greater target to market success rate.
With this in mind, the overall SME Instrument Phase 2 project objectives are as follows:
1) Enhance the prototype platform technology by refining methodology and target drug/disease roadmap
2) Validate technology through commercial trials with key industry partners
3) Develop commercialization and marketing strategy and prepare for the next scale-up phase
