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Case Study: Is it time for AI for drug discovery as a service?

Nardev Ramanathan, Ph.D., Senior Analyst
November 10, 2021

Despite the value of AI to the pharmaceutical industry in the drug discovery space, significant barriers to its adoption remain. One of the major barriers lies in developing the relevant AI capabilities to tackle questions around novel target identification, lead identification and optimization, safety, and bioavailability and metabolic stability, to name a few. Big pharma has, for the most part, looked at investing heavily in these capabilities internally, launching open innovation programs or acquiring promising drug discovery startups. However, smaller pharmaceuticals and clinical-stage biotechnology companies are more resource-scarce, especially if there is no internal AI expertise within the core team.

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USE CASE AND BUSINESS IMPACT

Chief.AI is a British startup that is looking to address this gap by helping to improve and expand the accessibility of AI to smaller, innovative players. In partnership with Medicines Discovery Catapult (MDC), it launched what it claims is the first "no-code, pay-as-you-go" service for its AI platform for drug discovery. It offers a cloud-based system with a series of what it claims are best-in-class AI models for clients through an AI marketplace. Clients can build applications quickly through a relatively simple interface without needing substantive IT capabilities. The company only announced its platform several months ago (July 2021), so it remains to be seen how much appeal the platform will have on the market.

#LUXTAKE

AI for drug discovery as a service is unlikely to appeal to big pharma, which have their own strategies in this area, as discussed above. Big pharma generally desire secrecy in the early stages of their therapeutic programs for competitive reasons. However, this could be an option for smaller clinical-stage biotechnology companies with fewer financial resources, which could seek external help to fast track their drug discovery program and move potential targets quickly through the preclinical and clinical pipelines. Clients should keep an eye out for similar developers looking to offer a SaaS-type model for drug discovery for potential investment or partnership opportunities but should note the limited appeal it will have with big pharma.

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