AI in Healthcare

Today's Stories

1. 1

   Thermo Fisher Scientific is presenting new tools for drug manufacturing, clinical testing, and AI-powered research at BIO International 2026, expanding its portfolio across the biotech development pipeline.

   Thermo Fisher Scientific is showcasing new capabilities across manufacturing, clinical development, and AI-enabled research at the BIO International 2026 conference. The company is demonstrating how it supports biotech companies across multiple stages—from early research through manufacturing and clinical trials—positioning itself as a comprehensive partner in the drug development process.

   The specific innovations and tools being unveiled at BIO International 2026 will indicate where Thermo Fisher is investing to help accelerate biotech development.

2. 2

   Thermo Fisher Scientific is expanding AI-enabled research tools, advanced manufacturing capacity, and clinical development capabilities to help pharma and biotech customers accelerate drug development and bring therapies to market faster.

   Thermo Fisher announced new investments across three areas at BIO International 2026. On manufacturing, the company is expanding sterile fill-finish and device assembly capacity (including a collaboration with SHL Medical at its Ridgefield, New Jersey site), launching new GMP monoclonal antibody manufacturing capabilities in Plainville, Massachusetts in the second half of 2026, and adding biologics drug substance capacity in the U.S. and Switzerland. On research, Thermo Fisher is introducing AI-enabled analytics and clinical research capabilities through Clario and forming strategic partnerships with NVIDIA, OpenAI, TetraScience, and BenchSci to help customers automate laboratory workflows and unify scientific data. Pharma and biotech companies are under pressure to reduce development timelines and are increasingly seeking data-driven, connected approaches across research, clinical testing, and manufacturing. Thermo Fisher positions itself as a single integrated provider that can help customers simplify complex workflows across the entire drug development lifecycle—from discovery through commercialization.

   The company is launching new GMP monoclonal antibody manufacturing in Plainville, Massachusetts in the second half of 2026, and expanding its Bioprocess Design Center network with new facilities in the U.S. and India to provide local expertise and collaborative environments for customers scaling up manufacturing.

3. 3

   Jacobi–IDE, a development tool for Abaqus subroutines, now runs analytical physics tests automatically and can send failed diagnostics to Claude for AI-powered debugging.

   Jacobi–IDE compiles and runs a suite of 12 physics tests on Abaqus subroutines (specialist engineering simulation code), flagging errors in material properties, yield behavior, and numerical stability. When tests fail, the tool sends diagnostic data to Claude, an AI assistant, which suggests the likely cause—such as a volumetric component in plastic flow that needs correction. Writing and validating Abaqus subroutines is error-prone and time-consuming; engineers typically must debug by hand. Automated analytical tests catch physical inconsistencies early, and AI diagnosis narrows the search space for fixes, reducing iteration cycles and the expertise barrier for less experienced developers.

   The tool is demonstrated passing 10 of 12 tests on an elastic–plastic material model, with Claude correctly identifying a suspected issue in the failed cases. Availability, pricing, and compatibility with different Abaqus versions are not stated in the announcement.

4. 4

   Eli Lilly and Twist Bioscience are pursuing different strategies to industrialize AI-driven drug discovery, signaling how biotech companies are translating AI advances into actual medicines.

   Eli Lilly and Twist Bioscience have announced distinct approaches to scaling AI in drug discovery. Eli Lilly is integrating AI into its internal R&D operations, while Twist Bioscience is positioning itself as a technology and services partner to enable other companies to leverage AI in their own drug development programs. Drug discovery has historically been slow and expensive, making AI's potential to accelerate candidate identification and reduce costs highly valuable to the industry. These two companies represent contrasting industrialization models—one focused on internal competitive advantage, the other on providing the infrastructure others need—which will shape how AI translates from research promise into commercial drug pipelines.

   The outcomes of both approaches will determine whether AI's drug-discovery gains flow primarily to large integrated pharma companies or become accessible to smaller biotech firms and research organizations. How quickly each model produces validated drug candidates will be a key measure of which path proves more effective.

5. 5

   AI drug discovery is shifting focus from tool-makers to real-world users—two healthcare stocks show how companies are turning algorithms into actual medicines.

   Eli Lilly and Twist Bioscience are using AI in drug development in different ways. Lilly partners with OpenAI on drug discovery and has built an AI co-innovation lab with Nvidia to find molecules faster; Twist makes synthetic DNA that drugmakers test, and is now integrated into Amazon's new Bio Discovery platform for AI-driven drug design. The first wave of AI rewarded companies that sold the tools. The next wave appears to reward companies that apply those tools in clinics, labs, and pharmacies to produce new medicines. Both firms show how AI adoption is moving into real-world use rather than staying at the software level.

   Eli Lilly's recently approved weight-loss pill Foundayo is a near-term growth driver because a pill format (replacing injections) could reach a much larger patient population. Twist reported revenue rising 19% to $110.7 million（約180億円） in fiscal Q2 2026 and has posted 13 straight quarters of rising revenue, though it currently operates at a net loss.

6. 6

   Merck and Protillion have launched a collaboration to use AI for drug discovery, with Merck able to earn up to $510 million（約820億円） in milestone payments as the partnership progresses.

   Merck and Protillion announced a collaboration focused on AI-driven drug discovery. Merck can receive up to $510 million（約820億円） in milestone payments tied to the partnership's advancement and achievements. Large pharmaceutical companies like Merck are betting on AI to accelerate the drug discovery process, which is traditionally slow and expensive. This deal signals that established players view AI as a necessary tool to compete in modern drug development.

   The structure ties Merck's financial upside to concrete milestones, meaning the partnership's progress and whether it delivers tangible results in drug candidates will determine how much of the $510 million（約820億円） payment potential is realized.