Amazon Bio Discovery enables scientists to run complex computational workflows through more than 40 AI-specialized foundational models, trained on a wide range of biological datasets. These models generate and evaluate potential drug molecules, alongside AI agents that help scientists to select models, optimize inputs and evaluate candidates according to their research.
DeepSeek V4 Pro has a total of 1.6 trillion parameters, making it the biggest open-weight model available, outstripping competitors like Moonshot AI's Kimi K 2.6 and MiniMax's M1.
The iShares Biotechnology ETF is the default large-cap vehicle for the sector. It is market-cap weighted, which concentrates the fund in cash-generative incumbents rather than spreading capital across clinical-stage names.
Helical's thesis is that bio foundation models, AI systems trained on vast genomic, transcriptomic, and proteomic datasets, have already crossed a quality threshold that makes computational hypothesis-testing meaningful in pharma research.
Incyte tops this list due to its rare combination of commercial scale, cash generation, and pipeline depth. The company posted FY2025 revenue of $5.14 billion, up 21.2% YoY, anchored by Jakafi generating $828.2 million in Q4 2025 alone (+7% YoY) and Opzelura delivering $207.3 million (+28% YoY). With $3.58 billion in cash and 14 pivotal clinical trials underway, Incyte offers an acquirer immediate revenue, margin expansion potential, and a deep oncology pipeline spanning KRASG12D, CDK2 inhibition, and mutCALR.
GPT-Rosalind is designed to support evidence synthesis, hypothesis generation, experimental planning, and multi-step scientific workflows across biochemistry, genomics, and protein engineering.
Novo Nordisk plans to deploy advanced artificial intelligence capabilities to analyze complex datasets, identify promising drug candidates, and reduce the time required to move from research to patient.
Meta's new Model Capability Initiative will track the mouse movements, clicks, and keystrokes of its US employees to generate high-quality training data for future AI agents. This software will operate on specific work-related apps and websites, and will also utilize periodic screenshots to provide context for the AI training.
We provide thought partnership. When a company is developing a drug, there's a lot of work involved, such as understanding the science, designing a study and generating good data. We come in and explain what the standard of care looks like today for their patient population, and what we think it will look like in five to eight years or whenever they plan to launch their therapy.
Now, researchers have created an artificial-intelligence system that vastly simplifies and accelerates the process of chemical synthesis. The system, which is called MOSAIC and is described in a study published in Nature on 19 January, recommended conditions that researchers were able to use to generate 35 compounds with the potential to become products like pharmaceuticals, agrochemicals or cosmetics without needing to do any further trawling or tweaking.
