Naming a Chief Artificial Intelligence (AI) officer may not be an industry first, but Lilly’s recent creation of the role with the appointment of Thomas Fuchs confirms the solid commitment pharma has already made to introducing AI in processes that range from drug discovery to marketing.
AI Leaders
Eli Lilly announced this month the appointment of its first chief AI officer, dean and department chair for AI and human health at Mount Sinai Thomas Fuchs. Fuchs, who has worked to develop AI tools aimed at improving patient outcomes and administrative efficiency in his current role, will be charged with creating a strategic direction for all of the US-based firm’s AI initiatives, and identifying, building, and managing Lilly’s AI and machine learning projects.
Pharma companies have long been convinced of AI’s potential and have increasingly tasked dedicated leaders to steer their AI initiatives. “The company has a longstanding commitment to AI, evident in our substantial investments in this area,” Saskia Steinacker, who has been leading the digital transformation at Bayer for over three years told Pharmaboardroom earlier this year.
While drugmakers’ AI efforts have typically been led by chief digital officers, a role which has come to prominence over the past decade, Lilly is not the only company to appoint an AI lead. In August, Pfizer named Berta Rodriguez-Hervas as its chief AI and analytics officer, whereas Merck appointed Chief Data & AI Officer Walid Mehanna almost three years ago.
AI in Drug Discovery
The new Lilly appointment coincides with the announcement of the Nobel Prize winners that seem to fully confirm the relevance of AI and machine learning in science, and potentially in drug discovery. Chemistry laureates Demis Hassabis and John Jumper of Google DeepMind have developed an AI model for predicting proteins’ structures and their AlphaFold Protein Structure Database is being used by over 2 million scientists and researchers in 190 countries.
AI has been praised for its potential to streamline drug discovery, a traditionally long and laborious process, by enabling the reduction of target identification times, molecular simulations and the prediction of drug properties. According to Morgan Stanley, even “modest improvements in early-stage drug development success rates enabled by the use of artificial intelligence and machine learning could lead to an additional 50 novel therapies over a 10-year period, which could translate to a more than USD 50 billion opportunity.”
AI has been especially driving biotech discovery with AI-fueled pipelines expanding at an annual rate of almost 40%. The world’s largest pharma players have all entered the AI drug discovery game, mainly through partnerships with biotechs or other suppliers specializing in AI, like the accord between AstraZeneca/BenevolentAI. This approach was validated by Bayer’s Steinacker. “Instead of attempting to tackle every aspect independently, we actively seek partnerships and collaborations within the AI ecosystem.”
There have been advances and breakthroughs, like for GlaxoSmithKline partner Insilico Medicine who garnered the FDA’s first Orphan Drug designation for a drug discovered and designed using AI. However, with most of the recent AI-discovered molecules still in Phase I trials, questions remain about the quality of AI-driven discoveries and their ability to progress through the pipeline.
Beyond R&D
The potential of AI in other business areas has also become apparent for drugmakers. In this vein, Lilly’s newly appointed AI officer will handle all of the company’s AI initiatives spanning from “drug discovery, clinical trials, manufacturing, commercial activities and internal functions.”
Moderna recently partnered with OpenAI to improve its internal workflows and employee productivity with bespoke chatbots while Bayer is using AI in marketing and forecast planning, leveraging historical sales data, marketing information, and various datasets.
