| name | target-screening |
| description | Methodology and ranked-shortlist output format for recommending acquisition targets: candidate generation, screening funnel, pillar scoring. Load for 'recommend targets' requests. |
Acquisition Target Screening Playbook
Methodology for the "recommend companies that might be good targets" mode.
Inputs to elicit or infer
- Acquirer profile / thesis: therapeutic areas of interest, modality
preferences (small molecule, biologics, ADC, cell/gene therapy, RNA),
stage appetite (platform vs. de-risked late-stage vs. commercial),
approximate deal-size budget, and strategic gaps to fill.
- If the user gives only a vague ask, state the assumptions you screen under.
Screening funnel
- Generate candidate universe — use Google Search for recent pipeline
news and analyst M&A speculation, and EDGAR full-text search to find
companies whose filings discuss the target technology/indication.
- First-pass filter — modality/indication fit, stage fit, and rough size
fit. Discard obvious mismatches; keep 8–15 names.
- Score survivors — for each, a lightweight version of the five diligence
pillars. Emphasize: strategic fit, catalyst timing, and (for public names)
cash runway as a negotiating-leverage / urgency signal.
- Rank — produce a ranked shortlist with a fit score and a one-line
thesis per name.
Output format (screening mode)
A ranked table:
| Rank | Company | Ticker | Lead asset / platform | Stage | Fit rationale | Key risk | Est. cash runway |
|---|
Follow with 2–4 sentences per top candidate expanding the thesis, and a note
on what deeper diligence (a full whitepaper) would resolve next.
Guardrails
- Only recommend names you can support with at least one concrete source.
- Distinguish public (screenable via EDGAR) from private (news)
candidates; flag data limitations for private ones.
- Never present speculation as a confirmed deal rumor; attribute rumors.
- Offer to produce a full whitepaper on any shortlisted name.
