target-screening

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

1. 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.
2. First-pass filter — modality/indication fit, stage fit, and rough size fit. Discard obvious mismatches; keep 8–15 names.
3. 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.
4. 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.