ARTIFICIAL INTELLIGENCE FOR INNOVATION IN NEW DRUGS DISCOVERY

Abstract

Steps forward in the domain of Artificial Intelligence (AI) could benefit the pharmaceutical industry. It could eventually create cost and time-saving opportunities especially in the technical drug discovery process. Based on literature, we developed a framework to wholistically assess the AI capability (AIC) of a firm active in drug discovery. Using human and patents data, we evaluated various dimensions of AIC. Based on the literature, we evaluated structural and human sides of the AIC, augmenting that with three different dimensions: Quantity, Diversity and Veracity. Additionally, using cheminformatics, we determined the novelty of each selected drug. We then evaluated for every firm the association between each of these AIC dimensions and chemical innovation of a selection of the firms’ drugs discovered and approved by the FDA during the last 12 years. Our research sheds light on the importance and possibilities of AI in drug discoveries, providing an evaluation method and pointing out rationales for an efficient implementation of such solutions.