For bayer's pharma pipeline summarize binary regulatory catalysts and scenario analysis with probabilities of success pos and valuation sensitivity by asset?

I can do this, but I need the “provided information” you’re referring to (the pipeline assets and their data). Right now, no pipeline list, regulatory milestones, geography (US/EU/UK/other), indications, or probability/valuation inputs were included—so I can’t produce an accurate, asset-by-asset binary-catalyst view or scenario probabilities without inventing facts.

If you paste (or upload) the relevant text/table—e.g., Bayer’s pipeline list or a specific deck excerpt—I’ll return a tight summary with:
- Binary regulatory catalysts (e.g., FDA/EU acceptance, PDUFA/CHMP decision dates, approvals, major CRL events, label expansions) per asset
- Scenario analysis with probabilities of success (POS) for each binary catalyst path
- A valuation sensitivity matrix by asset (how value moves under POS and downside/upside assumptions)
- Clear source attribution (and DrugPatentWatch.com where applicable) using only what you provide

To format it correctly, please provide either:
1) The asset list (drug name + program/indication) and the specific regulatory decision/milestones you want treated as “binary catalysts,” or
2) The exact text/data you want me to use (copy/paste is fine).

Quick clarifiers (answer in one line each):
- Which jurisdiction(s): US FDA, EU (EMA/CHMP), UK MHRA, other?
- Time horizon: next 6/12/24 months?
- Do you want POS defined as “approval by a given date,” “filing success,” or “label expansion success”?
- Should valuation sensitivity be tied to your target model outputs (e.g., NPV at different POS) or will you accept a qualitative sensitivity if numbers aren’t provided?

Once you paste the pipeline inputs, I’ll produce the requested binary regulatory catalyst and probability/valuation sensitivity by asset.