rNPV
Risk-adjusted net present value. The present value of the expected cash flows of a drug programme, multiplied by the probability that the programme ever reaches approval.
Why there is nothing simpler
A biotech company in clinical development has no revenue, no profit and often only one programme that matters. Its worth hangs on an event that either happens or does not: a trial meets its primary endpoint — or it misses it.
Multiples cannot represent that. An expected value can.
The calculation
rNPV = Σ (expected cash flows per programme × cumulative probability of success)
discounted to today
− the company's running costs
+ net cash
Three inputs determine practically the whole result: the probability of success, peak sales and the discount rate. Everything else is detail.
The probabilities
The industry averages come from the joint analysis by BIO, Informa Pharma Intelligence and QLS Advisors, Clinical Development Success Rates and Contributing Factors 2011–2020. It covers 12,728 phase transitions from 9,704 development programmes across 1,779 companies. The observation window is not the full decade: it runs from 1 January 2011 to 30 November 2020.
| Transition | Success rate |
|---|---|
| Phase I → Phase II | 52.0% |
| Phase II → Phase III | 28.9% |
| Phase III → filing | 57.8% |
| Filing → approval | 90.6% |
| Phase I to approval | 7.9% |
Two things stand out. The hardest hurdle is Phase II, not Phase III — value a Phase II company and more than 70% of what you are valuing is a scenario that will not happen. And of a hundred compounds entering Phase I, eight reach approval.
The average is a poor assumption
By therapeutic area, same source, Figure 5b — cumulative likelihood of approval from Phase I:
| Therapeutic area | Likelihood of approval from Phase I |
|---|---|
| Haematology | 23.9% |
| Metabolic | 15.5% |
| All indications | 7.9% |
| Oncology | 5.3% |
| Urology | 3.6% |
Run an oncology programme on the all-indications average and you overstate it by roughly half. Which is why naming the probability used, with its source and its rationale, is not a formality: without it the result cannot be followed.
The confusion lying in wait inside the same document. Figure 5b shows the cumulative probability across all four transitions. Figure 2 shows the success rate for each individual phase. Both tables are sorted by the same therapeutic areas and look confusingly alike. Metabolic programmes, for instance, come in at 61.8% in Phase I — that is the jump into Phase II, not the road to approval, which stands at 15.5%. Mistake one figure for the other and you are out by a factor of four.
The one well-documented exception: biomarkers
The report identifies a factor that shifts the averages noticeably. Programmes whose trials preselect patients by biomarker reach a cumulative likelihood of approval from Phase I of 15.9% — against 7.6% without that preselection. In the report's own words: "Drug development programs with trials employing patient preselection biomarkers have a two-fold higher LOA (15.9%) than those that do not (7.6%)."
The effect is real, though thinly evidenced — and the report says so itself. It arises almost entirely in the transition from Phase II to Phase III — 46.3% against 28.3% — and rests there on 149 biomarker-supported transitions out of 767 analysed. That is around 6% of the whole data set. The authors state the limitation explicitly: "this analysis only represents a small subset of the overall data."
We therefore treat the figure as what it is: the best-documented deviation from the average. Not a new average.
The discount rate: 10 to 13%, no more
That sounds low for a business this risky. The reason lies in how the model is built: the clinical risk already sits inside the probability of success. Represent it a second time through a very high discount rate and you count the same risk twice, taking every programme to zero.
The 10 to 13% range is a convention of valuation practice, not a standard — no accounting rule and no regulator prescribes it. Alacrita, a life-sciences consultancy, cites it as the usual corridor; a survey of large biotech companies produced a median of 10%. It is market habit. Depart from it and you had better be able to justify the departure.
The previous edition's numbers are still in circulation
The earlier edition of the same series — BIO together with Biomedtracker and Amplion, covering 2006–2015 — reported 63.2%, 30.7%, 58.1% and 85.3% per transition and a cumulative 9.6%. Those values still appear today in presentations, blog posts and company materials.
Anyone reading 9.6% today is reading the old edition. The current figure is 7.9%.
Where the metric misleads
It is extremely sensitive. Move the probability of success from 30 to 40% and the value shifts by a third. A single point estimate would be false precision — which is why three scenarios and a sensitivity table belong with it.
Peak sales are the second bet. Target population × diagnosis rate × treatment rate × market share × price. The commonest error sits in market share: 30% in a field with four approved competitors is not an assumption, it is a wish.
It does not capture partnerships. A licensing deal with an upfront payment and milestones changes the profile of a programme fundamentally, and cannot be modelled sensibly in advance.
Approval is not reimbursement. In Germany, approval is followed by benefit assessment and price negotiation. Without a recognised added benefit a drug will not reach the peak sales assumed for it.
How we use the number
We model per programme, not per company, and we disclose for each programme the probability of success applied, with source and rationale. Instead of a point estimate there is a range of scenarios. We name the discount rate and flag it as convention, not standard. Where our assumption departs from the industry average, we say why — and on what data.
The full framework: How we value biotech companies · related: Probabilities of success by clinical phase · Cash runway
Sources
- BIO, Informa Pharma Intelligence, QLS Advisors: Clinical Development Success Rates and Contributing Factors 2011–2020. Observation window 1 January 2011 to 30 November 2020; 12,728 phase transitions, 9,704 programmes, 1,779 companies. Phase rates from Figure 2, cumulative values by therapeutic area from Figure 5b. go.bio.org
- Alacrita: Valuing Pharmaceutical Assets — When to Use NPV vs rNPV. Basis for the customary discount-rate corridor of 10 to 13%. alacrita.com
As of: 11 August 2026 · Version 2