Noor’s Newsletter — Issue #15
This isn’t a recap of the weeks—it’s an attempt to understand the forces reshaping how we live, govern, and evolve.
The first weeks of 2026 are already revealing how quickly AI is reshaping not just discovery, but also deployment, regulation, and integration across healthcare. Where 2025 closed with cautious optimism around protein design and platform validation, the new year opens with a series of moves that hint at both acceleration and consolidation.
AI in Clinical and Research Workflows
Anthropic continued to expand Claude into healthcare and life sciences, offering HIPAA-ready infrastructure for research collaboration, clinical workflow augmentation, and decision support. In parallel, OpenAI introduced ChatGPT health builds on the strong privacy, security, and data controls. Healthcare has historically been one of the most difficult sectors to penetrate due to regulation, ethics, and risk sensitivity. The entry of major AI players into clinical environments is therefore likely to have a catalytic effect—particularly on regulators—potentially accelerating pathways that allow more innovation to reach patients, which I think is generally a good move for the sector.
On the diagnostics side, two major announcements from two of the largest players in the field stood out. Illumina, increasingly moving into spatial multiomics, introduced the Billion Cell Atlas to accelerate AI-driven drug discovery. Built under an alliance framework with AstraZeneca, Merck, and Eli Lilly as founding participants, the Atlas is already being constructed using curated cell lines designed to support drug target validation, and potentially biomarker discovery. A dataset at this scale will be an interesting playfield for training AI models and advance research into disease mechanisms that have previously been out of reach.
Meanwhile, 10x Genomics—long the leader in spatial transcriptomics—announced its move into the diagnostics space, including the establishment of a CLIA lab. This signals 10x’s intent to move its research platforms closer to patients and regulated clinical and diagnostic workflows across multiple disease areas.
AI-Driven Discovery and Techbio Consolidation
The strategic logic of AI-native biotech continues to clarify. AstraZeneca announced its acquisition of Modella AI, a pathology chatbot company, likely motivated by the opportunity to absorb the underlying talent and foundational pathology model capabilities. These assets can be integrated into biomarker discovery, target identification, and improved clinical trial design. This is one of the relatively few AI-centric acquisitions by big pharma and may point to a growing appetite for acquiring specialized AI platforms rather than building them entirely in-house.
Similarly—though via a different commercial structure—GSK signed a five-year, $50 million agreement to access Noetik’s foundation AI models for biomarker discovery. The subscription-based nature of this deal is notable, and it will be interesting to observe how this model evolves as AI capabilities mature and pricing power shifts. At the same time, Isomorphic’s collaboration with J&J highlights the value of integrating AI models across both early discovery and translational validation.
It is encouraging to see more pharma–techbio collaborations centered on technology and talent, rather than exclusively on molecules or therapeutic assets. Historically, such deals have been relatively rare. However, given the pace of innovation over the past few years, I suspect it has become increasingly difficult for large organizations to build and experiment across the full breadth of emerging technologies internally. On the startup side, this signals interest beyond pilots and individual therapeutics (usually capital intensive) and should ultimately drive greater investment and momentum. On the pharma side, it reflects a more open-minded approach to collaboration and data sharing—an area where the industry has not traditionally excelled.
Along similar lines, Eli Lilly—one of the most active players in this space over the past year—and Nvidia announced a $1 billion co-innovation lab focused on AI-powered drug discovery. The money will support an autonomous lab facility that is aimed to optimise the design-make-test-analyse cycle with the integration of robotics and AI.
For anyone tracking the intersection of AI, healthcare, and life sciences, these first weeks of the year are undoubtedly an exciting start. They serve as a reminder that the field is accelerating on multiple fronts—from data and technology to talent and business models.
—Noor
P.S. I recently wrote a short book on my perspective on some of the most exciting innovations of the past few years. It spans AI, healthcare, energy, space, autonomous vehicles, and other transformative technologies we are fortunate to witness—and help build. You can download individual chapters here or find the full book on Amazon here.