AI in Healthcare

Today's Stories

1. 1

   Bristol Myers Squibb stock may trade 48% below fair value on AI drug discovery push

   Bristol-Myers Squibb has expanded its AI collaboration with Nvidia and opened a new San Diego R&D hub. A Discounted Cash Flow analysis estimates the company's intrinsic value at about $123 per share, implying the stock trades at roughly a 48.1% discount to that level. The stock has delivered a 42.2% return over the past year, signaling growing market optimism. The DCF model, which projects future cash flows from a latest twelve month free cash flow of about $12b, suggests meaningful upside if the valuation estimate holds — though regulatory uncertainty around partnered drugs and pipeline outcomes could affect how durable those cash flows prove to be.

   The stock's next move depends on whether the current price already reflects the intrinsic value from the DCF model or still leaves a margin of safety for investors. Bristol-Myers Squibb scores 4 out of 6 on overall valuation checks, pointing to a mixed picture rather than a clear bargain or overvaluation.

2. 2

   Merck KGaA adopts Evinova's full AI clinical trial suite

   Merck KGaA has signed up to use Evinova's complete AI-powered clinical trial platform. Evinova provides AI tools designed to support the full lifecycle of clinical trials for pharmaceutical development. Clinical trials are a lengthy and costly phase of drug development. AI-driven solutions that streamline trial management could reduce timelines and expenses, making it valuable for large pharma companies like Merck KGaA to adopt such platforms.

   The deal signals industry momentum toward AI adoption in regulated pharmaceutical workflows. How successfully Merck KGaA deploys Evinova's tools across its trial portfolio will serve as a reference case for other companies evaluating similar AI platforms.

3. 3

   Medical AI study finds critical flaw across OpenAI, Anthropic, OpenEvidence, Doximity

   A new independent benchmark called NOHARM, built by researchers at Stanford, Harvard, and the ARISE network, tested AI tools from OpenEvidence, Doximity, OpenAI (GPT-5.6 Sol), and Anthropic (Claude Fable 5) on 1,100 real clinical cases with roughly 13,000 physician annotations. Doximity Ask ranked first, but the key finding was that across all systems, 76.6% of harmful errors were omissions—the AI left something out rather than stating something factually wrong. Omissions in medical AI are particularly dangerous because they deprive doctors of critical information at the point of care. Eric Topol, a cardiologist at Scripps Research, noted that errors of omission must be brought close to zero, and that today's models maintain an "illusion of readiness" despite improvement. The timing is significant: the FDA loosened AI oversight in January, but states have passed more than a dozen new laws in 2026 requiring human sign-off before AI-assisted decisions reach patients, and malpractice liability remains legally unclear.

   OpenEvidence's CEO Daniel Nadler disputed NOHARM's methodology, saying the study is not peer-reviewed and questioned whether Doximity's perfect-memory approach should qualify for re-testing. The unresolved liability question—whether doctors, hospitals, or AI vendors bear responsibility when a model's suggestion is wrong—will likely shape how regulators, hospital systems, and investors approach medical AI next.

4. 4

   AI medical coding market to hit $10.6B by 2035

   The global AI in medical coding market was valued at approximately USD 3 Billion in 2025, is expected to reach USD 3.4 Billion in 2026, and is projected to grow to around USD 10.6 Billion by 2035, at a CAGR of 13.5% during the forecast period from 2026 to 2035. AI-powered medical coding automates code assignment, fraud detection, compliance monitoring, and risk adjustment — functions that healthcare providers and payers rely on for billing accuracy and regulatory compliance. The market expansion reflects growing adoption of automation in healthcare administrative workflows.

   Key players in the market include 3M Company, Optum Inc. (UnitedHealth Group), Nuance Communications Inc. (Microsoft), Oracle Health (Cerner), Dolbey Systems Inc., Aviacode (GeBBS Healthcare Solutions), Iodine Software, CodaMetrix Inc., AGS Health LLC, and R1 RCM Inc.

5. 5

   Israel's medical data becomes prize for Pfizer, OpenAI, tech giants

   Multinational pharmaceutical and AI companies including Pfizer and OpenAI are pursuing access to Israeli medical data to train AI models and develop new drugs. Israel's centralized health system and digitized patient records—held by health funds and government institutions—have made the country an attractive source for this sensitive data. Medical data is critical for training AI systems that can improve drug discovery, disease diagnosis, and personalized treatment. For Israel's tech sector, this positions the country as a supplier of high-value health information to global leaders, though the arrangement raises questions about data privacy and sovereignty over sensitive citizen health records.

   The terms and safeguards under which Israeli health data is shared—including whether individuals consent, how identifiable data is protected, and which institutions control access—will shape both the pace of AI-driven medical breakthroughs and the precedent for other countries with digitized health systems.

6. 6

   Bristol Myers Squibb Expands Nvidia AI Partnership for Drug Discovery

   Bristol Myers Squibb announced it will deploy Nvidia's next-generation DGX SuperPOD AI supercomputer to build what it calls the most powerful AI factory in life sciences, expanding its existing collaboration with Nvidia to accelerate drug discovery and development. Drug development is typically slow and expensive; if Bristol Myers' AI efforts succeed in cutting development time and costs even by 1%, the impact could be meaningful across its dozens of active pipeline programs. The company already faces major patent cliffs ahead for key drugs like Eliquis and Opdivo, so faster, cheaper drug discovery could help offset revenue pressure from generic and biosimilar competition.

   Bristol Myers has said it is already seeing benefits from its long-standing AI-related efforts, and this new supercomputer investment could help further boost efficiency. The company is also advancing newer medicines including milvexian (a next-gen anticoagulant) and pumitamig (a cancer drug in multi-indication testing) that could help mitigate patent cliff impact.