AI in Healthcare: FDA, Hospitals, and Drug Discovery in 2026

Isomorphic Labs raised $2.1 billion on May 13, 2026, in the second-largest biotech fundraise ever, while hospitals across the U.S. are deploying AI agents for medical transcription and records management — and struggling to secure them. These parallel developments mark a defining moment for AI’s role across the full clinical and pharmaceutical pipeline.

Isomorphic Labs’ $2.1B Bet on AI Drug Discovery

Isomorphic Labs, the Alphabet-founded AI drug development firm, closed a $2.1 billion funding round led by Thrive Capital, according to Forbes Tech. The raise follows a $600 million first outside round from the previous year and places Isomorphic behind only Altos Labs in total single-round biotech fundraising history, per trade publication Endpoints News.

The London-based company is best known for AlphaFold, the AI model that predicts protein structures — work for which CEO Demis Hassabis (who also leads Google DeepMind) won the 2024 Nobel Prize in Chemistry. AlphaFold 3, released in May 2024, extended the model’s capabilities to small molecules, peptides, antibodies, and proteins — the core building blocks of modern drug design.

Building on AlphaFold, Isomorphic has developed what it calls the Isomorphic Labs Drug Design Engine (IsoDDE). Isomorphic President Max Jaderberg described IsoDDE to Forbes as “like half a dozen AlphaFold breakthroughs” combined into a single platform. The company has not disclosed which specific drug candidates it plans to advance to clinical trials.

“We’re aiming to redefine the way we create new medicines,” Jaderberg told Forbes, calling the new funding “a lot of validation of what we’ve been building out the past four-and-a-half, almost five, years.”

The investment comes at an undisclosed valuation. The scale of the round reflects sustained investor confidence that AI can compress the drug development timeline — a process that traditionally takes over a decade and costs billions per approved therapy.

AI Agents Are Already Inside Hospitals — and Security Teams Are Scrambling

While drug discovery AI operates largely in research environments, a different class of AI is already embedded in day-to-day clinical operations. VentureBeat reported that AI agents are now handling medical transcription, updating electronic health records, surfacing patient history in real time, and prompting prescription options — all inside live hospital exam rooms.

The problem is that these agents generate non-human digital identities that most enterprise IT systems cannot inventory, scope, or revoke at machine speed. Cisco President Jeetu Patel told VentureBeat at RSAC 2026 that 85% of enterprises are running AI agent pilots, but only 5% have reached production deployment — an 80-point gap he attributed directly to trust and identity governance failures.

IANS Research found that most organizations still lack role-based access control mature enough for their existing human identities — and that AI agents will make this problem significantly harder to manage. The 2026 IBM X-Force Threat Intelligence Index reported a 44% increase in attacks exploiting public-facing applications, driven by missing authentication controls and AI-enabled vulnerability discovery.

Michael Dickman, SVP and GM of Cisco’s Campus Networking business, told VentureBeat that the trust gap is architectural, not a tooling problem — meaning hospitals cannot solve it by simply purchasing a new security product.

Hospital Cyber Resilience: A New Minimum Standard

Separate from AI agent security, hospitals face a broader cyber resilience mandate. According to Forbes Tech, The Joint Commission and the American Hospital Association launched the Cyber Resilience Readiness (CRR) program to help health systems assess and sustain clinical operations during extended technology outages.

The program sets a concrete benchmark: hospitals must be able to deliver safe patient care for 30 days or longer without core technology systems. This is described not as a regulatory aspiration but as the current operational minimum.

The average healthcare data breach costs $7.42 million, according to the Forbes report, with additional losses from daily downtime, manual billing processes, and disrupted patient access. The CRR program begins with a free self-assessment tool covering four priority areas:

• Clinical-IT integration: Ensuring clinical, IT, emergency management, and disaster recovery teams collaborate before a crisis, not during one.
• Board-level involvement: Regular cybersecurity briefings to hospital boards, not just IT leadership.
• Downtime procedure readiness: Verified, practiced manual workflows for when digital systems fail.
• Supply chain and vendor risk: Assessing third-party dependencies that could fail during an incident.

Forbes contributor David Chou, a healthcare technology executive, noted that most health system CIOs have not yet planned for 30-day outage scenarios — a gap the CRR program is designed to close.

GE HealthCare Advances MRI Technology for Clinical Research

On the imaging side, GE HealthCare announced updates to its SIGNA MR platform, positioning next-generation MRI technology as a bridge between research discovery and clinical deployment, according to a Business Wire announcement. Specific technical specifications and FDA clearance details were not included in the available source material.

The SIGNA MR announcement reflects a broader trend of established medical device manufacturers investing in AI-assisted imaging to improve diagnostic speed and precision — complementing the software-layer AI deployments happening simultaneously in hospital workflows.

AI-Assisted Cardiac Risk: Longevity Medicine’s Diagnostic Push

At the patient-care level, AI-informed diagnostics are beginning to surface in preventive cardiology. A Forbes Tech piece co-authored by physician Hansa Bhargava and Dr. Jeffrey Chen — a Harvard-trained emergency medicine physician and Founding Medical Director of Peak Health — described how traditional cardiac risk calculators are missing high-risk patients.

The article detailed a patient case in which a 42-year-old woman with normal blood pressure and cholesterol was cleared by standard risk models, despite a family history of fatal heart attack at age 52. Dr. Chen ordered a coronary artery calcium (CAC) scan — a low-radiation CT that directly images arterial calcium deposits — which revealed significant subclinical disease invisible to standard blood panels.

CAC scans and similar advanced diagnostics are increasingly being paired with AI interpretation layers to flag risk patterns that population-level statistical models underweight. The case illustrates a structural limitation in current clinical practice: risk calculators optimized for average populations can systematically miss outliers, particularly those with strong family histories.

What This Means

The week’s AI healthcare news points to a sector moving on multiple fronts simultaneously — and encountering friction at each one.

Isomorphic Labs’ $2.1 billion raise is the largest single signal yet that institutional capital believes AI can materially shorten drug development timelines. But Isomorphic has disclosed no clinical pipeline, meaning the capital is funding platform infrastructure, not near-term drug approvals. The gap between AI drug design capability and FDA-approved therapies remains wide.

In hospitals, the deployment reality is messier. AI agents are already running live clinical workflows, but the identity and access management infrastructure to govern them doesn’t exist at scale. Cisco’s data point — 85% in pilots, 5% in production — suggests the bottleneck is not model performance but institutional trust, security architecture, and regulatory clarity. Until hospitals can answer basic questions about which agents have access to what data and who is accountable when an agent errs, broad production deployment will remain stalled.

The cyber resilience standard from The Joint Commission adds another layer: hospitals are being asked to operate without technology for a month while simultaneously being pushed to adopt more of it. CIOs are caught between two mandates that require fundamentally different planning horizons.

For patients, the near-term benefit may come not from drug discovery AI but from diagnostic AI — tools like AI-assisted CAC scan interpretation that can catch high-risk individuals before a cardiac event, in the exam room, today.

FAQ

What did Isomorphic Labs raise $2.1 billion to do?

Isomorphic Labs raised $2.1 billion, led by Thrive Capital, to fund its AI-driven drug development platform, including its IsoDDE drug design engine built on the AlphaFold protein structure prediction model. The company has not disclosed specific drug candidates it plans to bring to clinical trials.

What is the Cyber Resilience Readiness program for hospitals?

The Cyber Resilience Readiness (CRR) program, launched by The Joint Commission and the American Hospital Association, helps hospitals assess their ability to sustain clinical operations during extended technology outages — with a benchmark of 30 days without core systems. It begins with a free self-assessment tool covering clinical-IT integration, board involvement, downtime procedures, and vendor risk.

Why are AI agents in hospitals a security risk?

AI agents running hospital workflows generate non-human digital identities that most enterprise identity and access management systems cannot track, scope, or revoke in real time. According to Cisco’s Jeetu Patel, only 5% of enterprises running AI agent pilots have reached full production, largely because security teams cannot yet answer who is accountable when an agent acts outside its intended scope.