Global Artificial Intelligence in Drug Discovery Market is estimated register 39% CAGR between 2017 and 2027. Much of the demand is expected to generate from leading companies spending high amount of net revenue on R&D process.

Artificial intelligence has the potential to offer over US$ 70 billion saving for drug discovery process by 2028. The potential to boost company’s ROI along with its time saving process has led big pharmaceutical and biotech companies to invest heavily on technologies. For instance, in 2017, Sanofi entered in strategic research collaboration with AI drug discovery firm Exscientia for US$ 250 million. In the same year, Exscientia entered in another major collaboration with GSK to apply its AI in drug discovery process for ten disease related targets. The deal will help company to carry out the AI enabled research on metabolic disease. Similar such developments took place in last two years.

Global Artificial Intelligence in Drug Discovery Market Drivers and Challenges

The growth will be further driven by increasing demand by companies to speed up the drug trial phase, reduce research spending and create effective medicines for wide range of therapeutic applications. AI has already penetrated in healthcare segment and its presence in drug discovery is tangible.

Companies are working to mordernize their research facilities and resource intensive clinical trial process. Currently, conventional drug discovery method along with its FDA approval could take around ten years, costing over US$ 1.5 billion on an average. Most of the drugs failed to even pass through FDA phase II process. This led to significant loss to company. The probability of getting FDA approval is getting more stringent with regulatory compliances. At this phase, AI has certainly seen as a game changer move.