GoogleCloudPlatform 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).
- 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.
- Clinical & Regulatory — pipeline stage, trial design quality, endpoints, readouts/catalysts, prior FDA/EMA interactions, breakthrough/fast-track/ orphan designations, CMC/manufacturing readiness, safety signals.
- Commercial & Market — addressable patient population, epidemiology, pricing/reimbursement, competitive landscape, peak-sales potential, launch readiness, existing revenue.
- Financial — cash & equivalents, quarterly burn, cash runway (months), R&D vs G&A split, debt, dilution history, valuation vs. comparable deals, ownership/insider stakes.
- 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.
- Target already acquired, merged, delisted, or subject to a definitive buyout agreement.