Tempus AI ($57.39, +9.5% today on Pan-Cancer HRD-RNA algorithm launch) is the most financially successful AI-medicine company by revenue. At ~$1.27B FY2025 revenue growing 83% YoY, it dwarfs every company in our Phase 3 Discovery portfolio combined. But revenue scale ≠ Phase 3 classification within Apex's cyclical framework.
This report establishes why TEM is a Phase 2 Deployment name, provides full v2 Alpha Scores for TEM against our Phase 3 Discovery names (SDGR, RXRX, DNA, RLAY), and identifies whether the broader AI medicine narrative creates actionable opportunities for Apex Capital.
Key finding: RLAY has been fundamentally repriced since our original assessment — FDA Breakthrough Therapy designation for zovegalisib (Feb 3) and $596M cash runway into 2029 transforms it from a "cash runway risk / EXIT" call to the most de-risked AI-discovery clinical asset in our universe. This report includes a revised RLAY alpha score.
What it does: Uses AI to analyze existing data (genomics, pathology, clinical records) to match patients with existing treatments more precisely.
Compute profile: Classification algorithms on structured data. Computationally modest — a 1,660-gene logistic regression model runs in minutes.
Revenue mechanism: Diagnostic testing fees + data licensing to pharma. Recurring, scalable, and already proven at $1.27B/yr (TEM).
Capex feedback: Minimal. Does not generate new demand for GPU clusters. Pharma pays for data access, not compute infrastructure.
TEMPUS AI sits here.
What it does: Uses AI to simulate molecular physics, fold proteins, and design molecules that don't yet exist. Creates new treatments, not just better use of existing ones.
Compute profile: Molecular dynamics across 1012 timesteps. Protein conformational landscapes with 10300 states. GPU-hours per candidate in the thousands. Exact or worthless — you cannot distill physics.
Revenue mechanism: Software licensing + milestone payments + clinical-stage therapeutics. Pre-revenue at scale, but monetization creates step-function compute demand.
Capex feedback: Massive. Clinical validation → every pharma needs dedicated GPU clusters → Phase 1 infrastructure demand restarts at higher intensity.
SDGR · RXRX · DNA sit here.
The RLAY Question: Relay Therapeutics occupies a hybrid position. Its Dynamo® platform uses molecular dynamics simulation (Phase 3 methodology) but applies it to a focused clinical pipeline (more traditional biotech execution). With zovegalisib now carrying FDA BTD and a Phase 3 trial underway, RLAY is the closest to proving that AI-guided drug design produces clinically superior outcomes. If ReDiscover-2 reads out positive in mid-2026, it becomes the single most important proof-of-concept for the entire AI-discovery sector.
| Metric | FY2024 | FY2025 (prelim) | Growth |
|---|---|---|---|
| Total Revenue | ~$693M | ~$1,270M | +83% |
| Diagnostics Revenue | ~$452M | ~$955M | +111% |
| Data & Applications | ~$241M | ~$316M | +31% |
| Insights (Data Licensing) | — | ~$316M | +38% |
| Adj. EBITDA | ~($105M) | ~$5M (est.) | +$110M |
| Net Revenue Retention | — | ~126% | — |
| Cash & Securities | — | ~$764M | — |
| Market Cap | — | $9.92B | — |
| P/S (TTM) | — | ~7.8x | — |
The HRD-RNA algorithm uses RNA gene expression (1,660 genes) to dynamically assess Homologous Recombination Deficiency — a key predictor of response to platinum-based chemotherapy and PARP inhibitors. Unlike static DNA-based "genomic scar" tests, this RNA approach captures real-time tumor functional status, detecting HRD even in cancer types where genomic scarring is difficult to identify.
Significance: Incrementally positive — adds to TEM's algorithmic test suite (PurIST, IPS, Paige Predict), demonstrates continued product innovation ahead of Feb 24 earnings. Currently research-use only; clinical availability expected later in 2026. The +9.5% move is pre-earnings positioning on an oversold name (down 45% from 52-week high), not a thesis inflection.
Moat (72): Largest multimodal clinical-genomic dataset is structural. Paige acquisition added digital pathology moat. But diagnostic testing is increasingly competitive (Foundation Medicine/Roche, Guardant, Grail). Data licensing moat is durable — pharma switching costs are high once integrated into R&D workflows.
Catalyst Runway (70): Feb 24 earnings (confirmation + 2026 guidance), HRD-RNA clinical availability H2 2026, Paige Predict expansion, AstraZeneca/Pathos foundation model milestones. Mostly confirmation catalysts — market expects the beat.
S/D Trajectory (68): Precision diagnostics demand growing but pricing pressure emerging. Data licensing demand expanding as pharma AI adoption accelerates. Diagnostics supply response from competitors narrows moat over 12-18 months.
Edge Decay (55): "AI + precision medicine" is broadly consensus. 19 analysts covering. 15 Buy ratings. The growth story is well-known. Remaining edge is in execution speed and dataset scale, not in the thesis being non-consensus.
Regime (72): FDA increasingly supportive of AI-enabled diagnostics. Precision medicine adoption accelerating. Rate environment neutral. AI sentiment tailwind. No significant headwinds.
Moat (72): Physics-based FEP+ platform is structurally differentiated — competitors (Isomorphic Labs, etc.) are ML-only. All top 20 pharma as software customers. Novartis $2.5B deal. Lilly TuneLab integration. Software licensing is recurring floor under the stock. Neptune ammonia catalyst validates platform beyond pharma.
Catalyst Runway (68): Feb 25 earnings, SGR-1505 Phase 1 data completion 2026, SGR-3515 data H1 2026, Copernic catalyst pilot demos, potential new pharma collaborations. Mix of confirmation and new information events.
S/D (58): Software demand stable but drug discovery revenue lumpy. Competition from Isomorphic Labs and large pharma in-house teams could compress licensing pricing over time.
Edge (55): "Physics + AI" platform thesis is increasingly known. Stock down 58% from 52-week high — bad sentiment, but the thesis hasn't been disproven. Remaining edge is in clinical data readouts that haven't yet arrived.
Regime (60): FDA end-of-animal-testing policy (Apr 2025) is structural tailwind. But biotech funding environment remains tight. Rate sensitivity moderate.
Moat (58): 65PB multimodal imaging dataset + OS 2.0 + Exscientia merger is differentiated. NVIDIA partnership. But platform validation remains clinical — until pipeline drugs work in humans, the "AI discovers better" claim is unproven at scale. REC-1245 DAHLIA H1 2026 readout is make-or-break.
Catalyst Runway (65): DAHLIA Phase 1 data H1 2026 (new information), REC-617 ovarian cancer data ongoing, Sanofi/Roche/Bayer collaboration milestones. Front-loaded catalyst calendar.
S/D (52): Cash runway to mid-2027 ($509M). But at $3.41 (down 72% from 52wk high), the market is deeply skeptical. Revenue (~$100M est.) heavily collaboration-dependent. No product revenue in sight for 3+ years.
Edge (55): NVIDIA backing is known. AI-drug thesis is increasingly covered. But clinical data readouts will be genuinely new information — either validating or destroying the thesis.
Regime (55): FDA end-animal-testing policy helps. But biotech funding environment challenging for cash-burning pre-revenue companies. Dilution risk real.
Moat (60): OpenAI + Ginkgo autonomous lab experiments (Feb 5: 36,000 experiments, GPT-5 proposed novel reagents) positions DNA as the physical execution layer for AI biology. The "NVDA of Phase 3" thesis — but financials remain deeply distressed (Z-Score -7.01). Platform is unique; solvency is the question.
Catalyst Runway (65): Autonomous lab expansion with OpenAI, synthetic biology commercial deals, potential biosecurity contracts. Mostly new-information events — market hasn't modeled autonomous lab scale.
S/D (50): Revenue declining, margin negative, cash burn significant. Customer demand for cell programming exists but hasn't scaled to profitability. Supply of competing bio-foundry capacity is limited (moat), but demand hasn't arrived at price.
Edge (65): Autonomous AI biology is genuinely non-consensus. Most investors view DNA as a failed SPAC, not the physical execution layer for AI-driven biological discovery. If OpenAI partnership produces validated results, massive re-rating potential.
Regime (58): Biosecurity policy tailwinds. FDA animal testing reform helps. But financial distress and dilution risk weigh heavily.
Moat (75): Dynamo® platform uses molecular dynamics simulation (D.E. Shaw Research heritage) to capture protein motion — a structural differentiation no competitor has replicated. Zovegalisib is the first pan-mutant selective PI3Kα inhibitor ever developed — discovered through computational protein dynamics. FDA BTD validates the approach. Phase 3 trial (ReDiscover-2) underway. This is no longer speculative — it's clinically validated and regulatory-endorsed.
Catalyst Runway (85): This is the highest catalyst density in our AI-medicine universe. March 16: ESMO data (400mg BID fed Phase 3 dose — first public disclosure). Mid-2026: ReDiscover-2 topline Phase 3 data. NRAS program advancing. Fabry disease clinical initiation. Vascular malformations expansion. 5+ distinct catalysts, majority are new-information events that the market has not modeled.
S/D (62): PIK3CA-mutant HR+/HER2- breast cancer = ~140K patients/yr in US alone. Plus 170K vascular malformation patients. Addressable market is massive if zovegalisib delivers. Competitive threat from Celcuity's gedatolisib (broader PI3K inhibitor) — but RLAY's mutant-selectivity may offer superior tolerability.
Edge (60): BTD announcement moved the stock but it's still 91% below 52-week high of $9.54. Wait — actually RLAY is at $9.18 vs 52-week high of $9.54, meaning it's near highs now after massive recovery from $1.77 lows. The BTD and Oppenheimer upgrade are becoming known. But Phase 3 topline data is genuinely unmodeled — new information.
Regime (72): FDA extremely supportive — BTD granted. Precision oncology regulatory pathway is well-established. $596M cash runway into 2029 eliminates the funding risk that killed RLAY's thesis previously. This is the most de-risked AI-discovery asset in the universe.
Prior Assessment (Feb 4): Alpha 50 · EXIT · "Down 47%. Low alpha. Cash runway risk."
Revised Assessment (Feb 18): Alpha 72 · HOLD / ADD · FDA BTD transforms risk profile. $596M cash runway eliminates funding concern. Stock has re-rated from $1.77 to $9.18 (+419%). Phase 3 data mid-2026 = highest-conviction near-term catalyst in AI discovery.
What changed: Everything. BTD is the FDA explicitly endorsing Dynamo-discovered molecules as clinically meaningful. This is the proof-of-concept we said Phase 3 names needed to validate the capex feedback thesis. RLAY is delivering it.
| Attribute | TEM | RLAY | SDGR | DNA | RXRX |
|---|---|---|---|---|---|
| Phase | PH.2 | PH.3 | PH.3 | PH.3 | PH.3 |
| Price | $57.39 | $9.18 | $11.87 | $9.12 | $3.41 |
| Market Cap | $9.92B | $1.59B | $874M | $518M | $1.37B |
| 52w High / Low | $104 / $36 | $9.54 / $1.78 | $28.47 / $11.15 | $17.58 / $5.00 | $12.36 / $2.98 |
| % from 52w High | -45% | -4% | -58% | -48% | -72% |
| vs 50D MA | -12% below | +13% above | -28% below | ~flat | -22% below |
| vs 200D MA | -18% below | +71% above | -40% below | -12% below | -31% below |
| Revenue (TTM) | ~$1.27B | ~$8.4M | ~$225M | ~$75M* | ~$100M* |
| Revenue Growth | +83% | N/M | +21% | declining | +22% |
| Profitable? | Near breakeven | No | No | No | No |
| Cash Runway | $764M | $596M → 2029 | Funded by SW rev | At risk | $509M → mid-27 |
| v2 Alpha | 68 | 72 | 63 | 59 | 57 |
| Signal | WATCH | HOLD / ADD | HOLD | SPEC HOLD | SPEC HOLD |
| AI Methodology | Classification / pattern matching on clinical data | Molecular dynamics simulation (protein motion) | Physics-based FEP+ molecular simulation | Autonomous AI-driven biological experiments | High-dimensional imaging + ML drug discovery |
| Compute Intensity | LOW | HIGH | VERY HIGH | HIGH | HIGH |
| Capex Feedback | Minimal — data licensing, not compute demand | Moderate — validates AI drug design | Strong — pharma buys compute for FEP+ | Strong — autonomous labs need GPU clusters | Moderate — imaging pipeline is GPU-intensive |
| Next Catalyst | Feb 24 earnings | Mar 16 ESMO data | Feb 25 earnings | OpenAI lab updates | DAHLIA H1 2026 |
*Revenue estimates based on available data. Confirm via earnings releases. All prices intraday Feb 18, 2026.
TEM's success → pharma buys data licenses → $ flows to TEM, not to GPU manufacturers. The capital stays within the Phase 2 deployment layer. More patients sequenced, more data collected, more algorithms trained — but on existing clinical infrastructure, not new GPU clusters.
Infrastructure demand impact: Incremental.
SDGR/RXRX/DNA/RLAY success → pharma buys compute infrastructure → $ flows to NVDA, hyperscalers, power providers, memory manufacturers. The capital propagates from discovery through the entire Phase 1 supply chain. One successful AI-discovered drug validates the entire computational approach for an industry.
Infrastructure demand impact: Exponential.
The RLAY inflection: If zovegalisib's Phase 3 data reads out positive in mid-2026, it will be the first drug designed through AI-powered molecular dynamics simulation to demonstrate Phase 3 clinical efficacy. That single data point re-rates the entire AI-drug discovery sector — SDGR, RXRX, DNA, and potentially TEM's pharma partnerships — while simultaneously triggering the compute demand cycle that validates Phase 1 infrastructure investments. This is why RLAY's alpha score just jumped from 50 to 72.
Do not initiate a position ahead of Feb 24 earnings. The stock is +9.5% today on a product announcement, entering a binary earnings catalyst in 6 days. At $57.39 with the stock 45% off highs and 12% below its 50-day MA, this is a name in downtrend recovery, not breakout territory. The risk/reward for a new position is unfavorable.
Post-earnings evaluation criteria: If TEM guides FY2026 revenue above $1.8B with Adj. EBITDA profitability and data licensing growth sustaining 35%+, consider a 1-2% Phase 2 watchlist position with entry below $55. If guidance disappoints or growth decelerates, pass entirely.
TEM does not belong in Phase 3. It is the best AI-applied medicine company in the world. But "best in Phase 2" is not the same as "qualifies for Phase 3."
Prior: EXIT at $4.50, Alpha 50. Revised: Alpha 72, highest in AI-medicine universe.
The FDA BTD, $596M cash runway into 2029, and Phase 3 trial in a massive indication (PIK3CA-mutant breast cancer, ~140K US patients/yr) fundamentally changed this name. At $9.18, the stock has already re-rated +419% from $1.77 lows — but the Phase 3 topline data hasn't arrived yet. That's the highest-conviction catalyst in AI discovery for 2026.
Risk: Phase 3 failure is binary. Celcuity's gedatolisib is a competitive threat. At $1.59B market cap, RLAY is pricing in some success. The stock is near 52-week highs — chasing is suboptimal.
Sizing: Treat as an option — 0.5-1% portfolio weight. If adding, wait for pullback toward $8 support (near 50-day MA of $8.12). Stop below $6.50.
No changes to Phase 3 Discovery option book. SDGR (Feb 25 earnings) is the most important near-term catalyst for the computational engine thesis. RXRX's DAHLIA data in H1 2026 is the highest-risk/highest-reward readout. DNA remains the speculative long-shot on autonomous AI biology.
All three names are significantly below their 52-week highs (58%, 72%, 48% respectively). The market is deeply skeptical of AI-drug discovery. If any of the three catalysts validates the thesis, the sector re-rates violently. This is why we hold them as options, not as core positions.
| Ticker | Phase | v2 Alpha | Signal | Position | Rationale |
|---|---|---|---|---|---|
| TEM | PH.2 | 68 | WATCH | 0% | Evaluate post-Feb 24 earnings. Best AI-applied medicine. Not Phase 3. |
| RLAY | PH.3 | 72 | ADD | 0.5-1% | Highest alpha in AI-medicine. BTD validates. Phase 3 data mid-2026. |
| SDGR | PH.3 | 63 | HOLD | 1% | Computational engine. Feb 25 earnings. Software floor supports. |
| DNA | PH.3 | 59 | SPEC HOLD | 0.5% | Autonomous AI lab thesis. Financial distress risk. High edge. |
| RXRX | PH.3 | 57 | SPEC HOLD | 1% | DAHLIA H1 2026. Binary. NVIDIA-backed. 65PB dataset. |
The AI-medicine landscape bifurcates into two fundamentally different value chains. TEM dominates the data-and-diagnostics layer with $1.27B in revenue, 126% net retention, and a dataset moat no competitor can replicate at scale. It is the best Phase 2 AI-medicine play in public markets. But its success generates data licensing revenue, not compute demand — and it's the compute demand channel that creates the Phase 1 infrastructure feedback loop at the core of our cyclical thesis.
The surprise finding of this analysis is RLAY's transformation. A name we flagged for exit at $4.50 with alpha 50 has received FDA Breakthrough Therapy designation, secured cash runway into 2029, and sits at $9.18 with Phase 3 topline data arriving mid-2026. If zovegalisib works, it validates computationally-guided drug design as a clinical paradigm — repricing every Phase 3 name in our book and triggering the pharma compute demand cycle we've been positioning for.
Phase 3 is where the AI medicine thesis either proves itself or dies. The next 6 months will tell us.