The right target, the right exposure, the right drug
Predictive science is the collective name for a network of scientific disciplines. It focuses on indicating the most likely effects and outcomes. By combining all the knowledge available to us and applying specialised technology, equipment and methods, such as modelling and simulation, we can better answer critical questions in the drug discovery and development process.
Predictive Science is mostly concerned with helping to provide critical insights about whether we have the right target, the right exposure, the right drug. The information obtained can help shape the design of experiments to follow in the next stage or inform an early decision not to proceed.
AZD8329 is an oral, once daily inhibitor of the 11βHSD1 enzyme with best-in-class potential for the treatment of Type 2 diabetes. Using all available information, a preclinical in vitro model was developed to explore the mechanism of action. The results were used to predict what would happen in patients. This model was then used to design the dose-finding study. As a result of insight gained through modelling, the team was able to recommend reducing the proposed study size from 270 to 115 patients for the Phase IIb trial. This outcome resulted in lowering the cost of the study.
Professor Andrew Hughes gives a snapshot of predictive science
Andrew Hughes briefly explains what predictive science is about, and why we are making such a big investment to grow our predictive science capability at AstraZeneca.