Barry Bunin, PhD
Founder & CEO
Collaborative Drug Discovery
As 2026 Begins, It Looks Like Another Big Year for GLP-1. Nature carries the headline “The Expanding Landscape of GLP -1 Medicines” for an article reviewing current uses worldwide, including “for type 2 diabetes, obesity and associated comorbidities, including cardiovascular disease, peripheral artery disease and obstructive sleep apnea,” noting GLP-1s are “revolutionizing public health strategies for these conditions.” The article also looks at potential new applications, including: “neurodegenerative and substance use disorders, metabolic liver disease, arthritis, type 1 diabetes and inflammatory bowel disease.” Meanwhile, the Wall Street Journal reporting on Novo Nordisk’s gaining U.S. approval for the pill form of its Wegovy, quotes David Moore, Executive Vice President of Novo Nordisk’s U.S. operations as saying: “We now have injectable-like efficacy in a once-daily pill. And that’s a change from where we’ve been in terms of treating obesity.”
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NVIDIA Continues to Open New Collaborations in Drug Discovery—Announcing Projects with Merck and Genentech This comes after the company’s October announcement (which we covered in our previous Industry Roundup) of working with Eli Lilly to create an “AI Factory for Drug Discovery.” Recently, an article headlined “Merck and NVIDIA Team Up on New Drug Discovery Model” in Healthcare Brew, describes a small-molecule drug model called KERMT rolled out by NVIDIA and Merck. The model is pretrained on more than 11 million molecules, then fine-tuned for various tasks specific to industrial drug discovery workflows. Alan Cheng, Merck’s senior director of data science, said the model could help scientists better predict how a given molecule will behave in the body, potentially catching problems before researchers invest in months of testing. HPC Wire carries an article headlined “Genentech and NVIDIA Enter Into Strategic AI Research Collaboration to Accelerate Drug Discovery and Development.” The article quotes Jensen Huang, Founder and CEO of NVIDIA, as saying: “The greatest impact of generative AI is to revolutionize the life science and healthcare industry. Our collaboration to create Genentech’s next-generation AI platform will dramatically accelerate the pace of drug discovery and development.”
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"Large Quantitative Models: How AI is Accelerating Drug Discovery." That’s the headline for a World Economic Forum article on how the technology could save billions in R&D. The article says, in part: “Training language-based AI models on existing literature, historical data, and failed experiments is unlikely to help us discover novel molecules and unknown compounds that will unlock breakthroughs in new treatments for the most challenging and complex diseases. To achieve this, we need new AI models that can go beyond our existing pre-clinical data and literature, enabling deeper exploration of chemical space to uncover new candidates. They need to understand the nature and behavior of molecules and proteins so they can simulate their interactions and predict potential outcomes without lengthy and costly physical experimentation.” The article also points to the value of in-silico screening and optimization, saying this “could save billions of dollars in inefficient, risk-based R&D spending annually, leading to greater investment in therapies for challenging or rare diseases, including those affecting small or underserved populations.”
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“Why Big Pharma is Teaming Up with AI Giants to Speed Up Drug Discovery and Make Work Easier for Health Care Workers.” Fortune carries that headline for an article that appears to have been inspired by NVIDIA’s recently announced drug discovery collaborations. The article begins: “AI chip maker NVIDIA’s fresh partnerships with Eli Lilly and Johnson & Johnson point to a broader trend in the pharmaceutical industry, where tie-ups with AI giants are intended to speed up drug discovery and make work easier for health care workers.” While much has been written about AI-powered drug discovery, the work with Johnson & Johnson is interesting as it involves AI-powered robotic surgery. Kimberly Powell, a VP of Healthcare at NVIDA, who worked on the J&J surgical AI project, points to data from the World Health Organization that projects a shortfall of 11 million health workers globally by 2030. She predicts that a new operating room—a hybrid mix of human surgeons working alongside physical robots and digital agents—could result in breakthroughs in new procedure techniques. “There is a future goal of how we go from robotic-assisted surgery to robotic surgery, where the robot is actually taking some action on its own,” says Powell. “We’re laying all the groundwork to do that.”
Barry A. Bunin, PhD, is the Founder & CEO of Collaborative Drug Discovery, which provides a modern approach to drug discovery research informatics trusted globally by thousands of leading researchers. The CDD Vault is a hosted biological and chemical database that securely manages your private and external data.