🦠 AI Engineers the World’s First Custom Viruses

ALSO: AI Maps 1,000+ Diseases Before They Strike

September 22, 2025

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AIHealthTech Insider: Issue #67

September 22, 2025

This week’s issue captures AI’s expanding footprint in healthcare — from lab breakthroughs that design viruses and predict diseases decades ahead, to regulatory wins and hospital strategies transforming patient care. Add in startups pitching at Charmalot 2025, and the picture is clear: AI is no longer experimental — it’s becoming the backbone of discovery, diagnosis, and delivery.

Summaries for education, not medical advice. Verify locally before clinical use.

Image created with AI

Researchers have used AI to design viral genomes from scratch, creating bacteriophages capable of infecting and killing drug-resistant E. coli.

  • AI models Evo 1 & Evo 2 generated 302 candidate genomes based on the ΦX174 virus

  • Lab synthesis produced 16 viable phages that targeted resistant E. coli

  • Some designs carried entirely new coding sequences

  • Marks the first time AI has produced coherent, genome-scale sequences

Scientists say this could unlock therapies against superbugs but raises biosafety questions.

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Researchers unveiled Delphi-2M, an AI model forecasting risk for more than 1,000 diseases up to 20 years in advance.

  • Trained on 400,000 UK Biobank participants + 1.9M Danish records

  • Strong accuracy for cardiovascular disease, diabetes, cancers

  • Uses lifestyle, medical & demographic data

  • Raises questions on privacy, fairness & clinical integration

A potential shift toward predictive prevention — if responsibly deployed.

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Harvard Medical School released PDGrapher, a free AI model to speed drug discovery for complex conditions.

  • Maps gene–protein–pathway networks to restore diseased cells

  • Tested on 11 cancer types, ranking targets 35% higher & 25x faster

  • Identifies both known therapies & novel targets with clinical evidence

Already applied to Parkinson’s, Alzheimer’s & cancer, PDGrapher could reshape precision medicine.

Source: Jefferson Health

Jefferson Health launched a system-wide AI strategy to reclaim 10M+ clinician hours and cut paperwork burden for 23,000+ staff.

  • Focus on augmentation, not automation

  • Pillars: human-centered care, faster insight-to-action, transparency

  • Builds on 120+ AI use cases + AI Center of Excellence (2022)

  • Ambient listening for doctors → expansion to nursing underway

A bold push to turn AI into time, trust, and better outcomes.

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Source: Tempus

Tempus AI gained FDA 510(k) clearance for its updated Pixel platform in cardiac MR imaging.

  • Generates T1 & T2 maps even when scanners can’t

  • Improves diagnosis of fibrosis, inflammation & edema

  • Provides a comprehensive tissue view for personalized care

  • Builds on Tempus’s portfolio, including its $81M Paige acquisition

A milestone for AI-powered cardiac imaging.

Source: Mount Sinai

Mount Sinai Fuster Heart Hospital opened the Samuel Fineman AI Research Lab to advance interventional cardiology.

  • Led by Dr. Annapoorna Kini

  • Focus: risk stratification, case planning, workflow efficiency, patient engagement

  • Backed by a gift from Samuel Fineman, honoring care by Dr. Samin Sharma

  • Inaugural AI Symposium hosted Sept 15

Ranked #2 in the U.S. and #6 globally, Mount Sinai aims to lead in AI-driven cardiac care.

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🌟 Charmalot 2025: AI Meets Healthcare Innovation

Source; CharmHealth

CharmHealth’s annual user conference (Sept 19–21, Berkeley, CA) united clinicians, entrepreneurs & startups at the scenic Berkeley Marina.

  • Hands-on EHR training & workflow customization

  • Networking with startups, sponsors & digital health leaders

  • Keynotes: Dr. Ranya Habash (AI & ophthalmology), Sally Ann Frank (Microsoft, Health & Life Sciences)

  • Innovation Challenge 2025 spotlighted AI solutions in patient engagement, decision support, and workflow automation. Finalists pitched for $10K + CharmHealthHub integration.

Charmalot showcased CharmHealth’s role in blending EHR customization with AI integration to build scalable healthcare ecosystems.

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