Tech giants race in AI4S: Microsoft Corporation (MSFT.US) launches a biological world model, with Anthropic, OpenAI, and others also entering the fray.

AI4S is becoming a new battleground that tech giants are racing to bet on. Recently, Microsoft Corporation (MSFT.US) Research launched an experimental AI research system called Quine, aiming to build a multimodal world model for biology and establish an interactive harness framework connecting models, scientific tools, literature, and researchers, pushing AI from assisted analysis further toward scientific discovery. According to the introduction, Quine is not trained on a single type of biological data, but simultaneously covers multiple modalities including genomics, proteins, chemistry, RNA, cell states, and biological imaging, enabling information across different modalities to assist each other in prediction. In the specific scientific research workflow, after researchers pose a question, Quine can combine scientific literature and research tools for computational analysis, generate research plans and experimental designs, and hand prediction results over to real experiments for validation. The new data generated by experiments is then returned to the model and researchers for model training and to drive the next round of question analysis, forming a cycle of "question posingmodel reasoningexperimental validationresult feedback." Microsoft Corporation has partnered with the Broad Institute, jointly established with MIT and Harvard University, to apply Quine to cancer biology and other research. A case disclosed by Microsoft Corporation shows that Quine predicted and ranked the potential of thousands of compounds to alter the state of pancreatic cancer cells, after which the top-ranked candidate compounds entered wet-lab validation, with the highest-ranked compound producing the largest expected change. Microsoft Corporation stated that from narrowing the compound search scope to identifying candidates for laboratory validation, the entire process took only one weekend, saving months of experimental work and substantial research costs. However, Quine is still in an early research stage, and its results remain far from actual clinical application. In fact, Microsoft Corporation is not the only tech giant to ramp up AI4S recently. On September 23, Anthropic announced the establishment of a life sciences research team and laboratory, and disclosed early results from Claude's participation in biological research. After analyzing more than 200,000 reverse transcriptase (RT) sequences, Claude selected 3,500 candidate systems and further narrowed them down to 20, ultimately discovering a novel enzyme system called ART that has been preliminarily validated through wet-lab experiments. In addition, on September 16, Novo Nordisk A/S Sponsored ADR Class B announced a collaboration with Anthropic to use Anthropic models and Claude Science for scientific reasoning and related workflows in drug R&D, in order to solve specific drug discovery problems. OpenAI launched GPT-Rosalind for life sciences research in April this year. The model is specifically oriented toward biology, drug R&D, and translational medicine, covering tasks such as medicinal chemistry, genomics, and quantitative biology, and emphasizes tool calling and real-world scientific research workflows. On September 11, OpenAI announced that GPT-Rosalind had ended its research preview and opened access to eligible institutions. NVIDIA Corporation chose to enter from the angles of computing power, models, and experimental infrastructure. In January this year, NVIDIA Corporation (NVDA.US) and Eli Lilly (LLY.US) announced the joint establishment of an AI innovation laboratory, with the two sides planning to jointly invest up to US$1 billion over five years for infrastructure and research, focusing on solving complex problems in drug discovery and exploring the application of Siasun Robot&Automation and physical AI in drug discovery and production. On September 9, Eli Lilly announced that it would launch the artificial intelligence and machine learning platform TuneLab, which will open AI drug discovery models trained on its years of research data to biotechnology companies. Alphabet Inc. Class C's Isomorphic Labs continues to bet on AI-driven drug design. Relying on technological accumulations such as AlphaFold, the company applies AI models to the design of small molecules and other types of drugs, and collaborates with pharmaceutical companies such as Novartis AG Sponsored ADR, Eli Lilly, and Johnson & Johnson. Huafu Securities pointed out that on the industry side, AI healthcare is evolving from a single algorithmic tool to systematic applications covering diagnosis and treatment, health management, hospital operations, and drug R&D. As of June 2026, China had 134 approved Class III AI medical imaging-assisted diagnosis software products, and medical imaging has formed a certain foundation for product approvals. It is recommended to pay attention to relevant companies that can combine real clinical needs, possess comprehensive capabilities in data governance, model iteration, clinical validation, system integration, and compliant operations, and have already entered hospitals' actual workflows. Founder believes that large models have already landed in pharmaceutical companies, and the business models of computational R&D platforms such as CADD have also been proven, but the scale of publicly disclosed recurring revenue and the final number of marketed drugs remain relatively limited. Key indicators worth tracking going forward include whether cooperation between large models and pharmaceutical companies moves from the testing stage to actual use and fee disclosure, whether the contract value of professional R&D platforms continues to grow, and whether projects involving AI in R&D can further enter clinical trials and form commercialized assets. This article is reprinted from "Cailian Press"; GMTEight editor: Yan Wencai.