Biotech Probability of Success: Risk-Adjusted Drug Valuation

Key Takeaways

• Biotech probability of success from Phase 1 is roughly 7.9 percent overall per BIO/Informa 2011-2020 data, but oncology runs at just 3.4 percent, making indication choice the biggest variable in PoS modeling.
• Risk-adjusted NPV is the product of PoS and the NPV of the approved drug minus remaining development cost; a Phase 1 oncology asset with a $5 billion peak sales profile often has negative rNPV because development cost exceeds probability-weighted revenue.
• A common mistake is using the blended all-indication rate for a specific disease, which can overstate oncology PoS by four times and dramatically inflate the risk-adjusted valuation.
• A successful Phase 2 readout typically lifts remaining PoS from roughly 15 to 52 percent, the jump from Phase 2 to Phase 3 probability, which is why Phase 2 results produce some of the largest stock moves in biotech.

What It Is

PoS is an empirical probability drawn from historical phase transition data. For a drug currently in Phase 2, PoS is the joint probability of clearing Phase 2, clearing Phase 3, filing an NDA or BLA, and receiving FDA approval. For a drug in Phase 1, you add the Phase 1 transition on top.

The two most cited datasets are Wong, Siah, and Lo (2019), which analyzed 21,143 compounds in 406,038 trial entries from 2000 to 2015, and the BIO/Informa 2011-2020 study, which tracked 9,704 drug programs across 12,728 phase transitions. Both reach similar conclusions. Around 10 to 14 percent of compounds entering Phase 1 are eventually approved, with wide variation by therapeutic area.

The Intuition

A biotech's market cap is not the NPV of its drug at peak sales. It is the probability-weighted NPV, net of remaining development cost. A drug in Phase 1 with a potential $5 billion annual franchise is not worth $5 billion discounted. It is worth that number times the probability it ever reaches market, which for most indications is a small single-digit to low-teens percentage.

This is why two biotechs with similar peak-sales profiles can trade at very different valuations. The one with a Phase 3 asset has cleared more filters. Its PoS is three to six times higher than the Phase 1 company's, and its market cap reflects that.

How It Works

PoS is computed by multiplying the conditional probabilities of clearing each remaining stage. Using BIO/Informa overall rates:

Phase 1 -> Phase 2:    52.0%
Phase 2 -> Phase 3:    28.9%
Phase 3 -> NDA/BLA:    57.8%
NDA/BLA -> Approval:   90.6%

PoS from Phase 1 = 52.0% x 28.9% x 57.8% x 90.6% = 7.9%
PoS from Phase 2 = 28.9% x 57.8% x 90.6% = 15.1%
PoS from Phase 3 = 57.8% x 90.6% = 52.4%
PoS from NDA/BLA = 90.6%

These are blended rates. Indication-specific PoS varies widely. Wong, Siah, and Lo report oncology PoS from Phase 1 at roughly 3.4 percent, compared to above 20 percent for some hematology programs. Rare disease generally runs higher than common disease, partly because of regulatory flexibility and smaller trial sizes.

Risk-adjusted NPV (rNPV) is the standard valuation output:

rNPV = (PoS x NPV of approved drug) - remaining development cost

The DiMasi et al. (2016) estimate of $2.6 billion per approved drug is a company-wide cost including failures. For a single asset in Phase 2, remaining out-of-pocket cost is typically $100 to $400 million depending on trial size.

Worked Example

A clinical-stage biotech has a single Phase 2 oncology asset. Analysts project peak sales of $3 billion, a 12-year commercial life after launch, and a 60 percent EBIT margin. At a 10 percent discount rate, the NPV of that cash flow stream is roughly $4 billion. Remaining development cost to approval is estimated at $350 million.

Using an oncology-specific PoS from Phase 2 of approximately 5 percent (compared to the 15 percent all-indication rate):

rNPV = (0.05 x $4B) - $0.35B
     = $0.20B - $0.35B
     = -$0.15B

The asset has negative rNPV at this PoS. This is common for early-stage oncology and explains why pre-commercial oncology biotechs often trade at cash value. A successful Phase 2 readout would lift PoS to roughly 50 percent (the Phase 3 rate), which would transform the rNPV to roughly $1.65 billion. The binary nature of the readout is why these stocks are so volatile.

Common Mistakes

1. Using an all-indication average for a specific disease. Oncology, neurology, and cardiovascular drugs have materially lower PoS than the 7.9 percent overall average. Using the blended rate for an Alzheimer's program dramatically overstates the value.

2. Double-counting expedited designations. Breakthrough Therapy and similar designations correlate with slightly higher approval rates, but the effect is modest. Treating a designated drug as if it had 2x the PoS of the base rate is aggressive and unsupported by most datasets.

3. Ignoring lead vs follow-on indication. Wong, Siah, and Lo found that success rates for the lead indication are higher than for all indications pooled together. A drug being tested across four cancers has different PoS per indication than the headline number suggests.

4. Treating PoS as constant through a trial. PoS should step up at each data readout. An interim Phase 2 analysis that clears a futility boundary raises the conditional probability of Phase 2 success. Static PoS ignores this.

5. Forgetting commercial risk after approval. PoS ends at FDA approval. Launch risk, reimbursement, and competitive entry still sit between approval and peak sales. A drug can be approved and still fail commercially, so the NPV inside the rNPV formula should itself carry commercial risk adjustments.

Frequently Asked Questions

Q: What is biotech probability of success in simple terms? Probability of success is the estimated likelihood that a drug currently in a given phase will ultimately receive FDA approval. For a Phase 2 drug, it is the joint probability of clearing Phase 2, passing Phase 3, and winning FDA review. Multiplying this probability by the drug's potential NPV gives the risk-adjusted valuation.

Q: How does biotech probability of success affect investment decisions? PoS is the discount applied to every projected cash flow in a biotech model. A Phase 3 drug with 52 percent PoS is priced very differently from a Phase 1 drug with 8 percent PoS, even if both have the same peak-sales potential. Investors who use the wrong PoS, too high or too low, will systematically misprice the stock.

Q: What is a real-world example of biotech probability of success? In the worked example, a Phase 2 oncology asset with a $4 billion NPV produces a negative rNPV of minus $150 million at a 5 percent oncology-specific PoS, meaning the stock should theoretically trade near cash value. A successful Phase 2 readout lifts PoS to roughly 50 percent, transforming rNPV to approximately $1.65 billion and resetting the market cap accordingly.

Q: How can investors use biotech probability of success analysis? Use indication-specific PoS from the Wong, Siah, and Lo or BIO/Informa datasets. Adjust upward for Breakthrough Therapy designation only modestly, consistent with the literature. Update PoS at each data readout, a clean interim analysis that clears a futility boundary raises conditional Phase 2 PoS above the base rate.

Q: How is biotech probability of success different from the commercial probability of success? PoS ends at FDA approval. After approval, a drug still faces launch risk, payer reimbursement negotiations, and competitive entry. A drug can achieve approval and still fail commercially if reimbursement is restricted or a competitor launches a superior product. The NPV inside the rNPV formula should carry its own commercial risk adjustments separate from the clinical PoS.

Sources

1. Wong, C.H., Siah, K.W., Lo, A.W. (2019). "Estimation of clinical trial success rates and related parameters." Biostatistics 20(2), 273-286. https://academic.oup.com/biostatistics/article/20/2/273/4817524
2. BIO, Informa Pharma Intelligence, QLS Advisors (2021). "Clinical Development Success Rates and Contributing Factors 2011-2020." https://go.bio.org/rs/490-EHZ-999/images/ClinicalDevelopmentSuccessRates2011_2020.pdf
3. DiMasi, J.A., Grabowski, H.G., Hansen, R.A. (2016). "Innovation in the pharmaceutical industry: New estimates of R&D costs." Journal of Health Economics 47, 20-33. https://www.sciencedirect.com/science/article/abs/pii/S0167629616000291
4. FDA. "Step 3: Clinical Research." https://www.fda.gov/patients/drug-development-process/step-3-clinical-research

Disclaimer

This article is educational content only and is not financial advice. Nothing here is a recommendation to buy, sell, or hold any security. Consult a licensed advisor before making investment decisions.