AI drug development

Developing a new drug requires a tremendous investment in time, resources and expertise. Yet, 90% of drugs under clinical development fail to reach the market.

Unpredictable outcomes during human trials, complexity of disease processes, stringent regulatory requirements, and the inherent challenges of clinical trials all contribute to this concerning trend.

Mavatar’s strategy to optimize the success rate of drug development, is to compile large databases from clinical and biomedical studies, pertaining to relevant tissues, diseases and conditions.

With the aid of AI solutions, drug developers can then make significant progress in target selection, combination treatment and mechanism of action. In fact, these steps can be taken before development starts, and before any significant investment is even made.

Alternatively, the same AI-driven analysis can be applied to existing drugs on the market to discover indications.