diligence-playbook

name	diligence-playbook
description	The five life-sciences M&A diligence pillars (scientific, clinical/regulatory, commercial, financial, deal/risk), the cash-runway calculation, deal-thesis archetypes, evidence standards, and the red-flag checklist. Load for any acquisition assessment.

Life Sciences M&A Diligence Playbook

Domain methodology for Argus. Load the relevant section based on the user's request and the mode (quick answer / whitepaper / target screening).

The five diligence pillars

Every acquisition assessment covers these. Weight them by deal thesis (platform buy vs. single-asset buy vs. commercial-stage tuck-in).

1. Scientific & Modality — mechanism of action, target validation, novelty vs. crowded class, platform breadth, IP/freedom-to-operate, differentiation vs. standard of care and known competitors.
2. Clinical & Regulatory — pipeline stage, trial design quality, endpoints, readouts/catalysts, prior FDA/EMA interactions, breakthrough/fast-track/ orphan designations, CMC/manufacturing readiness, safety signals.
3. Commercial & Market — addressable patient population, epidemiology, pricing/reimbursement, competitive landscape, peak-sales potential, launch readiness, existing revenue.
4. Financial — cash & equivalents, quarterly burn, cash runway (months), R&D vs G&A split, debt, dilution history, valuation vs. comparable deals, ownership/insider stakes.
5. Deal & Risk — patent cliff/exclusivity timeline, litigation, key-person dependence, partnership/royalty encumbrances, integration complexity, antitrust, single-asset concentration risk.

Cash runway (core financial calculation)

• Quarterly net cash burn ≈ |NetCashProvidedByUsedInOperatingActivities| for the quarter (prefer cash-flow statement over net loss).
• Total liquidity = CashAndCashEquivalents + ShortTermInvestments + MarketableSecuritiesCurrent.
• Runway (months) ≈ total_liquidity / (quarterly_burn / 3).
• Flag runway < 18 months as a financing-risk / negotiating-leverage signal.
• Always use the most recent reported quarterly period available from EDGAR tools as of today's date; do not default to historical cutoff years.
• Always cite the filing (form + period end) each figure came from.

Deal-thesis archetypes

• Platform acquisition: weight Scientific highest; value the technology's reusability across indications, not one asset.
• Single-asset / late-stage: weight Clinical/Regulatory + Commercial; binary readout risk dominates.
• Commercial tuck-in: weight Financial + Commercial; revenue quality, margins, and channel fit.
• Distressed / buy-the-dip: weight Financial (runway) + Deal/Risk; the edge is timing a financing wall.

Evidence standards

• Prefer primary sources: SEC filings (via EDGAR tools), regulatory/scientific databases (via science skills: openFDA, ClinicalTrials.gov, ChEMBL, Open Targets, PubMed), and trial registries.
• Real-time ground truth: Treat live filing dates, clinical trial updates, and news from recent/current calendar years as authentic records (never future placeholders or system anomalies).
• Use Google Search for recent news, deal comps, and catalysts without hardcoding historical cutoff years — but treat it as a lead to confirm against a primary source, not as the citation itself.
• Every material claim in a whitepaper needs a source. Distinguish fact from inference explicitly.
• State confidence and gaps. "Unknown / not disclosed" is a valid, valuable finding in diligence.

Red-flag checklist (surface these prominently)

• Cash runway < 12–18 months without a clear financing path.
• Single asset carrying >70% of the pipeline value.
• Primary endpoint missed, or trial design that can't support approval.
• Patent expiry / loss of exclusivity within the investment horizon.
• Undisclosed safety signals, clinical holds, or CRLs (complete response letters).
• Heavy royalty/milestone obligations to third parties on the lead asset.
• Going-concern language in the latest 10-K/10-Q.