The Next Trillion-Dollar Wave Isn’t in Semiconductors. It’s in Your Bloodstream.
Everyone’s watching chips, NeoCloud, and power. Meanwhile, AI is quietly rewiring healthcare from reactive to predictive — and almost nobody is positioned for it.
Healthcare is moving through the same kind of capital cycle we’ve mapped in AI infrastructure: a foundational layer (genomics) enabling a diagnostic layer (AI-read data) enabling a delivery layer (personalized treatment) enabling a behavioral layer (digital therapeutics that keep patients engaged). Four layers, four sets of plays.
1. Gene Therapies — The Foundational Layer
This is the “silicon” of biotech: rewrite the underlying code, fix the disease at the source. 2026 has been a genuine inflection point — the FDA has leaned into faster, more flexible review pathways for cell and gene therapies, and the pipeline is converting.
•$QURE (uniQure) — surged sharply this month on a major gene therapy advancement; a name riding the regulatory tailwind directly
•$RGNX (REGENXBIO) — AAV gene therapy platform with a PDUFA decision already through in February and multiple late-stage pivotal readouts through 2026; partnered with AbbVie on what could be the first gene therapy for a non-rare disease (wet AMD)
•$NTLA (Intellia) / $CRSP (CRISPR Therapeutics) / $BEAM (Beam Therapeutics) — the core gene-editing complex; CRSP remains range-bound despite holding the world’s first approved CRISPR therapy, which is exactly the kind of “stuck but structurally important” setup worth tracking
2. AI-Assisted Diagnostics — The Inference Layer
This is where AI infrastructure spend actually shows up as patient outcomes. The model: ingest multimodal data (genomic, imaging, clinical), run inference, return an actionable diagnosis faster than a human panel.
•$TEM (Tempus AI) — the clearest pure-play. Q1 2026 revenue +36% YoY to $348M, diagnostics revenue +35%, MRD test volume up ~500% YoY, full-year guidance raised to $1.59–1.60B. This is the diagnostics version of a NeoCloud growth curve
•$PACB (Pacific Biosciences) — sequencing infrastructure, the “memory layer” underneath every genomic diagnostic
•$BFLY (Butterfly Network) — point-of-care imaging, AI-assisted ultrasound, democratizing diagnostic access
3. Precision Medicine — The Targeting Layer
Where genomics and diagnostics converge into “right drug, right patient, right time.”
•$PRAX (Praxis Precision Medicines) — CNS precision neuroscience, translating genetic epilepsy insights into targeted therapies, multiple readouts ahead in 2026
•$RGNX again earns a mention here — its retinal and Duchenne programs are precision-targeted by genetic subtype, not blanket indications
•Watch the AbbVie/Gilead-style partnership pattern — Big Pharma is increasingly outsourcing precision targeting to smaller platform companies rather than building in-house, which is where the asymmetric upside sits
4. Digital Therapeutics — The Engagement Layer
The layer that keeps patients adherent and reduces cost-of-care between clinical touchpoints — software as the prescription.
•$HIMS (Hims & Hers) — already a long-term holding in the core portfolio; consumer-facing digital health at scale
•$GDRX (GoodRx) — Pharma Direct revenue +82% YoY in Q1 2026, a real signal that the direct-to-consumer medication/therapeutics rail is accelerating
•$TDOC (Teladoc) — legacy name still worth tracking as the digital-care distribution layer consolidates
The framework, simply:
Genomics writes the code → AI reads the code → precision medicine targets the code → digital therapeutics keeps you compliant with the fix. Same wave structure as chips → memory → photonics → energy, just running through biology instead of silicon.
This sector moves on binary catalysts (PDUFA dates, trial readouts) rather than smooth growth curves like NeoCloud — size positions accordingly and expect volatility around data releases.
Not financial advice.
