Emerging Target Radar

Emerging Target Radar — The Pre-Consensus Watchlist Integrator

The single most valuable thing a frontier investor or a clinical scientist entering a new field can know is what is inflecting before everyone agrees it is. Scientific mindshare accreting to an emerging target or modality is measurable, with lead times running from ~5-7 years (NIH grant flows) down to near-real-time (conference share-of-voice). The radar's job is to fuse those signals into one ranked, defensible watchlist instead of chasing whatever was loudest at the last JPM.

This skill is the integrator. It does not generate raw velocity, attention, or convergence signals itself — three upstream skills do that (signal-scanner, mindshare-tracker, data-generation-monitor). The radar consumes their outputs and produces a single ranked list of {target × modality} candidates, each carrying its lead-time estimate (the literature-inflection-to-first-in-human gap, typically 3-7 years for a novel target), its NewCo-creation events (the sharpest venture signal there is), and its historical-pattern tag (genetics-first like PCSK9/GPR75, modality-unlock like KRAS/VAV1, or resistance-ladder like BTK). These candidate objects are the input contract for the downstream analog engine (moa-analog-engine, modality-lifecycle, frontier-conviction-scorer).

The core discipline is anti-hype. Mindshare is reflexive — capital manufactures the attention it claims to detect — so a candidate's rank is a positioning/timing instrument, never a measure of biological merit. Every velocity signal must be gated by an evidence-maturity check and normalized against the financing regime (Q1 2025 was the lowest US biotech startup formation in a decade, ~70% off the 2021 peak, so a single NewCo means more in 2025 than it did in 2021).

Watchlist: the dated target×modality candidate roster is versioned separately in references/watchlist.md (a point-in-time snapshot to refresh on cadence); the scoring method stays here.

How to Run

Input

If the three upstream signal streams are unavailable, reconstruct them inline: query PubMed E-utilities for total_count velocity, bioRxiv/medRxiv for preprint lead, conference abstract databases for share-of-voice, and EDGAR/press/Crunchbase for NewCo events. The skill degrades gracefully but is strongest when fed clean upstream objects.

Steps

Step 1 — Assemble the Candidate Universe

Pull every {target × modality} pair surfacing in the three signal streams within scope. Do not pre-filter on merit — the universe is deliberately broad; ranking happens later.

Seed sources to query directly when upstream streams are thin:

• PubMed E-utilities — total_count per target[tiab] AND modality[tiab] per year; compute YoY velocity and the second derivative (acceleration). Strip review/perspective publication types before counting.
• bioRxiv / medRxiv — preprint volume per entity (leads peer-reviewed by 6-18 months); the earliest formal-literature signal.
• Open Targets — genetics-to-target associations; flags genetics-first candidates.
• ClinicalTrials.gov v2 — first IND/Phase-1 entry is the translation-event ground truth that closes the lead-time measurement.
• ChEMBL — is there tractable chemical matter yet (IC50/EC50/Ki), or is this still a tool-compound gap?

Step 2 — Fuse the Three Signal Streams per Candidate

For each candidate, combine the upstream signals into a fused signal profile. The streams are deliberately orthogonal — they catch different false positives:

FUSED SIGNAL PROFILE — {target × modality}

  Velocity  (signal-scanner):   accel of PubMed total_count + bioRxiv preprint vol; author-affiliation
                                 breadth (Herfindahl — high concentration = single-lab artifact, discount)
  Attention (mindshare-tracker): 0-100 momentum from conference share-of-voice (AACR/ASCO/ASH/ESMO/JPM);
                                 GATED by Consensus evidence-maturity (volume high + quality low = HYPE flag)
  Convergence (data-gen-monitor): count of net-new ORTHOGONAL data-engine convergences
                                 (cis-pQTL+MR AND selective DepMap dependency AND clean Perturb-seq AND
                                  druggable ChEMBL matter AND cell-type-restricted expression)

A candidate with high velocity but a HYPE flag and zero orthogonal convergences is froth. A candidate with moderate velocity, multi-lab breadth, and 3+ convergences is a durable inflection. Rank rewards the second, not the first.

Step 3 — Estimate Lead Time (Literature-Inflection → First-in-Human)

For each candidate, locate the literature-velocity inflection year and the first-in-human (FIH) entry, or project the FIH if not yet reached.

LEAD-TIME ESTIMATE

  Inflection year   = year the second derivative of publication/preprint volume turned sharply positive
  FIH year          = first Phase-1 entry on ClinicalTrials.gov v2 (REALIZED) — or projected from arc position
  Realized lead     = FIH year − Inflection year         (only if FIH has occurred)
  Expected lead     = 3-7 yr from inflection for a novel target (use 3 yr if tool compound + chemical matter
                      already exist; 7 yr if still target-ID/biology stage with no tractable handle)

The realized/expected lead time is what tells an investor how much runway remains before consensus prices it and tells a scientist how mature the field is. A candidate already past FIH with a short realized lead (PCSK9 ~12 yr target-to-approval) is late-stage radar; a candidate at tool-compound stage with a 5-7 yr expected lead is the earliest actionable read.

Step 4 — Capture NewCo-Creation Events (the Sharpest Venture Signal)

A venture builder spinning out a NewCo around a specific target/modality front-runs consensus by 1-2 years — far more informative than aggregate sector financing. Record each event and normalize against the financing regime:

NEWCO SIGNAL

  Events: [company, round/$ , date, builder (Flagship/ARCH/etc.), specific target×modality]
  Big-pharma deal proxy: large licensing/M&A on the exact mechanism counts as a confirmation NewCo-equivalent
    (e.g. Novartis × Monte Rosa VAV1 degrader up to $2.1B; Sanofi × Vigil TREM2 $470M+; AbbVie × Capstan ~$2.1B)
  Regime normalization: weight each event UP in a contractionary year. Q1 2025 = decade-low US startup
    formation (~70% off 2021 peak), so a 2025 NewCo carries more conviction than a 2021 one.

Step 5 — Tag the Historical Pattern

Assign each candidate exactly one of three named patterns (the analog engine keys off this tag). The pattern predicts how the class will explode and what the ignition event will be:

PATTERN TAG

  genetics-first    — human-genetics (esp. LoF-protective) validation came BEFORE the drug.
                      Ignition = CV/hard-outcome trial. Analogs: PCSK9, GPR75, INHBE/ALK7, TL1A.
  modality-unlock   — a flat/disordered/pocketless target made tractable by a CHEMISTRY/PLATFORM fix,
                      not new biology. Analogs: KRAS (covalent switch-II), VAV1 (molecular glue),
                      in vivo CAR (tLNP), siRNA targets (GalNAc). Ignition = first-in-class pivotal readout.
  resistance-ladder — each new sub-class triggered by a defined resistance mutation. Analogs: BTK
                      (ibrutinib → acalabrutinib → pirtobrutinib C481S → BTK degraders). Ignition =
                      the resistance mechanism itself is the leading indicator of the next rung.

Step 6 — Rank and Emit the Watchlist

Score each candidate and sort. The composite rank is a positioning score, not a PoS:

RADAR RANK (0-100) =
    0.35 × fused_signal_strength      (velocity accel + breadth + convergence count, gated by evidence-maturity)
  + 0.25 × newco_signal               (count × regime-normalization weight)
  + 0.25 × lead_time_actionability    (more remaining runway before consensus = higher; penalize already-crowded)
  + 0.15 × pattern_clarity            (clean genetics-first or post-ignition modality-unlock ranks above ambiguous)

  HARD GATES (apply before scoring):
    — HYPE flag (high volume, low Consensus evidence quality) → cap rank at 40, route to "watch, don't underwrite"
    — Single-lab artifact (Herfindahl breadth fail) → cap rank at 40
    — "AI-discovered target" claim with no independent wet-lab/clinical validation → discount; AI moving
      molecular DESIGN is credible, AI "finding a novel target" usually is not (targets were already implicated)

Output

EMERGING TARGET RADAR — {Scope}
Date: [assessment date]   |   Velocity window: [window]   |   Regime year: [year]

RANKED WATCHLIST

| Rank | Target × Modality | Pattern Tag | Arc Position | Lead Time (R/E) | NewCo / Deal Signal | Fused Signal | Evidence Gate |
|------|-------------------|-------------|--------------|-----------------|---------------------|--------------|---------------|
| 1    | RAS(ON) tri-cplx  | modality-unlock | FIH→1st-appr (Ph3) | realized ~8 yr | RevMed (public) | accel↑↑ / conv 4 | PASS |
| 2    | GPR75/INHBE × siRNA | genetics-first | tool→FIH | expected 4-6 yr | Arrowhead/Regeneron | accel↑ / conv 5 | PASS |
| ...  |                   |             |              |                 |                     |              |               |

CANDIDATE OBJECTS (handoff to analog engine) — one per row:
  { target, modality, indication, arc_position, pattern_tag, lead_time, newco_events,
    supporting_signals: {velocity, mindshare, convergence}, evidence_gate, radar_rank }

TOP-OF-RADAR NARRATIVE:
1. [Highest-conviction pre-consensus read and why now]
2. [Steepest adoption curve this cycle]
3. [The one to "watch, don't underwrite" — high mindshare, evidence gap]

DEPRIORITIZED (gated out):
  - [Candidate] — [HYPE flag / single-lab / AI-novelty discount]

Error Handling

Cross-Domain Connections

This skill is explicitly dual-use: a clinical-scientist entering a field reads the watchlist as a map of where the science is inflecting and how mature each frontier is; an investor reads the identical output as a screen of early opportunities with remaining runway before consensus pricing. Lead-time and pattern-tag serve both readers.

• frontier-intelligence/signal-scanner (depends_on): supplies the velocity/acceleration/breadth primitive the radar fuses — the literature inflection that starts the lead-time clock
• frontier-intelligence/mindshare-tracker (depends_on): supplies the 0-100 attention momentum and the Consensus evidence-maturity gate that powers the anti-hype hard gate
• frontier-intelligence/data-generation-monitor (depends_on): supplies the orthogonal-convergence count — the strongest durable-merit signal that separates inflection from froth
• frontier-intelligence/moa-analog-engine: primary consumer — takes each candidate object, finds its nearest validated analog, and names the still-pending ignition trial to watch
• frontier-intelligence/modality-lifecycle: consumes the modality half of each candidate to supply the P(modality deliverable) term and confirm the delivery unlock has landed
• frontier-intelligence/frontier-conviction-scorer: ultimate consumer — converts the ranked candidate into a decomposed conviction score, handing off to phase-weighted rNPV once a clinical asset exists
• competitive-intelligence/pipeline-mapper (depends_on): once a candidate crosses into the clinic, pipeline-mapper enumerates the competitive set and confirms the "pre-explosion crowding" signal (e.g. every major immunology pharma owning a TL1A asset)
• product/frontier-antenna (depends_on): shares the cross-domain frontier-scanning methodology; the radar is the biotech-specialized instance feeding product-level frontier signals
• neocortex/foresight (depends_on): the radar's lead-time + pattern-tag output is a structured foresight signal — second-derivative detection of an emerging trend before consensus