npbuilds PoS Calculator — The Actuarial Engine
No open-source probability-of-success calculator exists for biotech venture diligence. Every VC firm does this on ad-hoc spreadsheets with inconsistent assumptions. This skill changes that. It produces a structured, auditable PoS estimate with explicit adjustment rationale at every step — so when you present an rNPV to an investment committee, every assumption behind the probability weighting can be traced.
How to Run
Input
Provide as much of the following as available. The calculator works with partial information but produces wider confidence ranges.
| Parameter | Required? | Example |
|---|---|---|
| Therapeutic area | Yes | Oncology (NSCLC) |
| Current development phase | Yes | Phase 2 |
| Mechanism of action | Yes | PD-1/VEGF bispecific antibody |
| Target | Recommended | PD-1 + VEGF-A |
| Modality | Recommended | Bispecific antibody |
| Biomarker selection | If applicable | PD-L1 CPS >= 1 |
| Regulatory designations | If applicable | Breakthrough Therapy, Orphan |
| Prior clinical data | If available | Phase 1 ORR = 42%, DCR = 78% |
| Competitive context | Recommended | 3 approved IO agents in 1L NSCLC |
| Company capitalization | Optional | $800M market cap, $400M cash |
Steps
Step 1 — Establish Base Rate
Load therapeutic-area-specific base rates from pos-base-rates:
Base PTRS = {P(current phase -> next), P(next -> next+1), ..., P(NDA -> Approval)}
Base LOA = Product of all remaining PTRS
Example for Phase 2 oncology (NSCLC):
- P2->P3: 24% | P3->NDA: 52% | NDA->Appr: 85%
- Base LOA from Phase 2 = 0.24 x 0.52 x 0.85 = 10.6%
Step 2 — Apply Modality Adjustment
Adjust base rate for drug modality using pos-base-rates modality table:
Modality-adjusted LOA = Base LOA x Modality Factor
Example: bispecific antibody = 0.9-1.0x → adjusted LOA = 10.6% x 0.95 = 10.1%
Step 3 — Apply Mechanism-Based Adjustments
Route to mechanism-risk-adjuster for target validation assessment. Key adjustment categories:
| Factor | Direction | Magnitude | Evidence Required |
|---|---|---|---|
| Genetic target validation (MR) | Upward | +20-30% relative | Published MR study with significant association |
| Validated target (approved drug in class) | Upward | +10-20% relative | Approved drug hitting same target |
| First-in-class (novel target) | Downward | -10-15% relative | No approved drug or advanced clinical data on target |
| Prior failure in same MOA | Downward | -15-25% relative | Phase 2/3 failure in same mechanism class |
| Strong preclinical-to-clinical translation | Upward | +5-10% relative | Species concordance, validated PK/PD model |
| Known mechanism toxicity | Downward | -5-15% relative | Class-effect safety signal documented |
Apply adjustments multiplicatively to the modality-adjusted LOA. Document each adjustment with evidence.
Mechanism-adjusted LOA = Modality-adjusted LOA x (1 + sum of adjustment factors)
Step 4 — Apply Program-Specific Modifiers
| Modifier | Direction | Magnitude | Rationale |
|---|---|---|---|
| Breakthrough Therapy Designation | Upward | +10-15% relative | 54% of granted BTDs approved; 30% time savings |
| Orphan Drug Designation | Upward | +10-15% relative | Smaller trials, regulatory flexibility, 7yr exclusivity |
| Biomarker-selected population | Upward | +15-25% relative | Higher effect size, enriched responder population |
| Large unmet need (no approved SOC) | Upward | +5-10% relative | FDA more willing to accept surrogate endpoints |
| Positive Phase 2 data (above expectations) | Upward | +10-20% relative | Data de-risks efficacy hypothesis |
| Crowded indication (5+ competitors) | Downward | -5-10% relative | Higher bar for differentiation, enrollment challenges |
| Small/undercapitalized sponsor | Downward | -5-10% relative | Execution risk, may not fund pivotal trial adequately |
Step 5 — Apply Reflexivity Adjustment (Innovation)
This step captures the insight from Soros's reflexivity theory applied to biotech:
PoS is path-dependent. A well-capitalized company with positive market sentiment has genuinely higher PoS than the base rate suggests — not because the drug is different, but because:
- Better-funded Phase 3 trials (more sites, faster enrollment, better CRO)
- Ability to run adaptive trials and add arms
- Stronger regulatory interactions (can afford experienced regulatory teams)
- Better manufacturing scale-up execution
| Capital Position | Reflexivity Adjustment |
|---|---|
| Well-capitalized (>3yr runway, >$500M cash) | +5-10% relative |
| Adequately capitalized (1-3yr runway) | 0% (neutral) |
| Under-capitalized (<1yr runway without raise) | -10-15% relative |
| Pre-data capital raise completed | +5% relative (runway secured) |
Reflexivity-adjusted LOA = Program-adjusted LOA x (1 + reflexivity factor)
Step 6 — Produce Output
Output
POS ESTIMATE — [Asset Name]
Indication: [therapeutic area + specific indication]
Current Phase: [phase]
Date: [date of assessment]
Phase-by-Phase PTRS:
P[current] -> P[next]: [%] (base: [%], adjusted: [%])
P[next] -> P[next+1]: [%] (base: [%], adjusted: [%])
...
NDA -> Approval: [%] (base: [%], adjusted: [%])
Cumulative LOA: [%]
Adjustment Audit Trail:
Base rate (TA): [%] Source: BIO/Informa 2024
+ Modality ([type]): [+/- x%] Reason: [rationale]
+ Target validation: [+/- x%] Evidence: [MR study / competitive validation / novel]
+ [Modifier 1]: [+/- x%] Reason: [rationale]
+ [Modifier 2]: [+/- x%] Reason: [rationale]
+ Reflexivity: [+/- x%] Capital position: [status]
─────────────────────────
Final LOA: [%]
Confidence Range: [low% - high%]
Low: Conservative (all adjustments at lower bound)
High: Optimistic (all adjustments at upper bound)
Key Assumptions:
1. [Most impactful assumption]
2. [Second most impactful]
3. [Third most impactful]
Key Risks to PoS:
1. [Risk that could materially lower PoS]
2. [Risk that could materially lower PoS]
Comparison to Naive Estimate:
Generic Phase 2 LOA: [%]
This program's LOA: [%]
Difference: [+/- x%] ([reason for divergence])
Error Handling
| Scenario | Response |
|---|---|
| Insufficient information for base rate | Use "All Indications" base rate with wider confidence range |
| No MR data available for target | Skip genetic validation adjustment; note as limitation |
| Conflicting adjustment factors | Apply both; net effect may partially cancel; document both |
| Ultra-rare disease (<200 patients) | Base rates unreliable; use rare disease rates with high uncertainty band |
| Platform technology (multiple indications) | Calculate PoS per indication; note that platform success in one indication may de-risk others |
Cross-Domain Connections
- Biotech-venture/pos-base-rates: Source of all base rate data
- Biotech-venture/mechanism-risk-adjuster: Provides mechanism-based adjustment factors
- Biotech-venture/rnpv-modeler: Primary consumer — PoS feeds into probability-weighted cash flows
- Biotech-venture/diligence-scorecard: PoS is the clinical strength pillar score
- Investing/reflexivity-theory: Source of the reflexivity adjustment concept
- Investing/risk-architecture: Structural parallel — both quantify multi-factor risk