A Changing Landscape: AI In Biotechnology
The use of artificial intelligence (AI) in biotechnology offers companies a compelling opportunity to accelerate and optimize drug development, a process that is time consuming, costly and has a high risk of failure. Beyond improving drug discovery, there is enormous potential for AI in enabling personalized medicine, enhancing diagnostic accuracy, delivering analytics, and assisting with diagnosis, providing biotechnology companies with an exciting opportunity to transform the pharmaceutical research and development landscape.
AI has already had a significant impact on the industry and its role in biotechnology will only continue to grow. In January, Eli Lilly (LLY) and Novartis (NVS) signed independent contracts valued at $45 million and $37.5 million upfront respectively, with Alphabet’s (GOOG) digital biotech company Isomorphic Labs. The companies will leverage Isomorphic’s artificial intelligence platform to develop small molecule drugs for undisclosed targets.
PRISM MarketView investigates the current and potential future applications of AI in biotechnology, and the companies using it today:
Drug Discovery and Development
AI algorithms have already begun revolutionizing the drug discovery process by accelerating the identification of potential drug candidates. Machine learning models enable researchers to predict the efficacy and safety of compounds with unprecedented accuracy, expediting the discovery of new therapies and reducing the cost and failure rate associated with traditional methods.
Genomics and Precision Medicine
AI-driven analysis of genomic data is enabling personalized medicine approaches by predicting patient outcomes, and tailoring treatments to the individual. This level of precision allows for targeted therapies that maximize efficacy and minimize adverse effects, ushering in a new era of customized healthcare.
Biomarker Discovery
Identifying reliable biomarkers for diagnosis, prognosis, and treatment response is crucial for advancing healthcare. AI algorithms can analyze complex biological data to pinpoint biomarkers indicative of specific diseases or physiological states, improving diagnostic accuracy and allowing for early intervention and monitoring of treatment efficacy.
Protein Engineering and Design
Researchers at MIT have begun using AI to generate proteins with specific structural features, using algorithms that have the potential to disrupt protein engineering by predicting the structure, function, and interactions of biomolecules with unprecedented precision. By simulating protein folding and dynamics, researchers can design enzymes, antibodies, and therapeutics tailored to specific targets or pathways, which has potential applications in the development of biologic drugs.
We took a closer look at some of the companies that are already leveraging the power of AI to develop innovative therapies:
Recursion Pharmaceuticals (RXRX)
Recursion is using AI to enhance its speed and efficacy as it develops therapeutics in a number of indications. The company has partnered with Nvidia (NVDA) to build BioHive-2, a next generation supercomputer that the company believes will be one of the most powerful supercomputers in the world across any industry. Recursion’s proprietary AI platform, the Recursion Operating System (ROS), analyzes biological images to identify disease pathways, screen potential drug candidates, and optimize drug discovery processes. The company recently reported that it is on track to read out multiple Phase 2 trial results, beginning in Q3 2024.
Amgen Inc. (AMGN)
Amgen, which has a market cap of more than $167 billion, has embraced AI to enhance its R&D capabilities. The company is leveraging advanced machine learning algorithms and computational modeling to accelerate the discovery of novel therapies for indications including cancer, cardiovascular disorders, and autoimmune conditions. In January, Amgen announced it had entered a partnership with Nvidia to develop an AI model-building platform, named Freyja, which will be installed in Reykjavik, Iceland.
Lantern Pharma (LTRN)
Lantern Pharma focuses on AI, machine learning, and genomic data to streamline its drug development process. The company is developing treatments for non-small cell lung cancer, bladder cancer, glioblastoma and other central nervous system cancers, and is conducting active clinical trials across three AI-guided drug candidates, using its proprietary AI platform, RADR®. This week, the company announced it had completed dosing of patients in two cohorts, and no dose-limiting toxicities have been observed in its AI-guided Phase 1a clinical trial evaluating LP-284 in patients with hematologic cancers as well as other select solid tumors and sarcomas. Lantern has a market cap of $66.27 million.
Privately-held BenevolentAI is also leveraging AI for drug discovery and development through a platform that integrates machine learning, natural language processing, and knowledge graphs to analyze biomedical data. BenevolentAI is developing drug candidates for ulcerative colitis, glioblastoma, ALS, Parkinson’s disease and fibrosis.
