By Dr. Mugdha Sawant and Dr. Laura-Marie Zimmermann, Biorizon Consulting
In 2012, Glybera became the first gene therapy approved in Europe. Five years later, with only one patient ever treated commercially, uniQure let its marketing authorisation lapse [2]. The regulator said yes. The market did not.
Most life science exit models still treat regulatory approval as the finish line. It is not. It is the starting gun.
Approval confirms that a product is safe and effective. It does not tell us whether an insurer, a national health system or a hospital budget committee will pay for it, at what price, or how long that decision will take. That second gate, reimbursement, is one of the largest and least explicitly modelled variables in a life science exit case, particularly in Asia-Pacific, where the systems behind it differ fundamentally from one market to the next.
Our previous article on TAM, SAM and SOM looked at how large a market is. This one asks how much of it can be reached once payers have had their say, and what it costs an exit case when that question is left out.
In brief
Approval and reimbursement are two separate gates. Most exit models treat them as one.
Across APAC, the gap between them ranges from about two months in Japan to more than eighteen months for oncology in China.
On our numbers, a two-year lag and realistic odds of coverage can remove 40–52% of present value before price negotiations begin.
1. The Approval-to-Market Trap
What the model assumes: Phase 3 success, regulatory approval, peak market share by Year 3, exit.
What tends to happen: Phase 3 success, regulatory approval, a payer review that can take years, then a fraction of the projected sales.
The gap exists because regulators and payers are answering different questions:
| Regulatory bodies (FDA, EMA, PMDA) | Payers / health systems (CMS, NHSA, PBAC, ACE) | |
|---|---|---|
| Core question | Is it safe, and does it demonstrate efficacy? | Is it worth the money, and does it improve on the current standard of care? |
| Evidence required | Randomised controlled trials | Comparative effectiveness, real-world evidence, budget-impact and cost-effectiveness models |
| Primary focus | Efficacy and safety | Comparative value, budget predictability, system-wide savings |
| What “yes” means | The product may legally be marketed | The system will pay for it, at this price, for these patients |
Table 1. Regulatory approval vs. payer reimbursement: two gates, two different questions.
Three modelling habits keep this gap open:
The hockey-stick assumption. Models routinely project a steep revenue ramp 12–18 months after approval, while national coverage decisions and payer contracts commonly take two to five years.
One probability for two risks. An rNPV model may carry an 85–90% probability of approval at the filing stage and then treat approval as the end of risk. That is a regulatory probability; it says nothing about whether, when or on what terms reimbursement follows.
Underestimated cost-to-exit. Models often omit the cost of the health economics (HEOR) and market access work needed to convince sceptical payer committees, most of which falls after approval.
2. Why Approval Does Not Pay the Bills
Even when a product clears a payer’s initial review, the structure of its reimbursement can undermine the financial model:
The coding hurdle. A product reimbursed under temporary or generic codes may receive payment that does not cover the procedure. CVRx’s Barostim heart-failure device, FDA-approved in August 2019, relied on temporary Category III codes for more than six years; permanent Category I codes took effect only on 1 January 2026 [1].
The incremental-benefit penalty. A drug that is only marginally better than the standard of care is often placed on a restrictive formulary tier with high co-payments. Coverage is secured; the volume assumptions are not.
Value-based contracts. Risk-sharing arrangements, such as payment only if the patient remains well for two years, delay cash flow and create operational liabilities that few models capture.
Budget-impact rejection. Sometimes the answer is simply no. Glybera, priced at roughly €1.1 million per treatment for an ultra-rare indication, failed commercially because payers and hospitals would not absorb a one-off cost of that size [2].
3. APAC Reimbursement Is Not One System
A single “APAC market access” assumption does not survive contact with the region. The major markets move at different speeds and follow different logic.
| Market | System archetype | Pricing mechanism | Primary payer evidence focus |
|---|---|---|---|
| Japan | Universal, multi-payer social health insurance | Central price-setting at listing; regular price revisions, now annual | Comparator- or cost-based pricing; cost-effectiveness used to adjust price after listing (since 2019) |
| China | Single national basic medical insurance (NHSA) | NRDL negotiation: price reductions in exchange for volume | Budget impact and price benchmarking |
| Australia | Universal public (Medicare / PBS) plus private insurance | PBS listing at a price justified against the comparator | Comparative cost-effectiveness (PBAC; MSAC for devices and services) |
| Singapore | Mixed public-private, income-tiered subsidies and co-payment | Value-based pricing negotiated by ACE for SDL, MAF and Cancer Drug List | Clinical and cost-effectiveness, budget impact |
| South Korea | Single-payer National Health Insurance | Economic evaluation (HIRA) followed by price negotiation (NHIS) | Cost-effectiveness; risk-sharing for high-cost drugs |
| Taiwan | Single-payer National Health Insurance under a global budget | NHIA price-setting with reference to international prices | Clinical value, HTA and budget impact |
Table 2. Six APAC reimbursement archetypes compared.
Japan is the fastest gate by design: NHI price listing followed approval within roughly 66 days on average for drugs approved in 2004–2014 [3]. The trade-off comes later, as regular statutory price revisions erode terminal value.
China negotiates volume for price. Average negotiated price cuts in NRDL rounds have risen from 44% in 2017 to around 60% in 2022 [12], with per-dose treatment costs down by up to 78% for some drugs [4][5]. In oncology, the median approval-to-reimbursement lag is 579–637 days and only 55–65% of indications are reimbursed [6]. Models need a binary switch: without NRDL listing the market is marginal; with it, the case shifts to low margin and high volume.
Australia applies one of the most rigorous HTA frameworks globally. The PBAC publishes no fixed threshold, but without convincing evidence of superiority over the comparator a product is typically funded only at the comparator’s price, or not at all. Before parallel TGA–PBAC review, cancer medicines waited an average of 63 weeks (about 441 days) for a funding recommendation; the gap has narrowed considerably since [7].
Singapore ties reimbursement to tiered subsidy. ACE negotiates value-based prices for the Standard Drug List, Medication Assistance Fund and Cancer Drug List, typically within three to nine months [8][9]. Subsidy levels vary by patient means and by public or private setting, so models should stratify uptake rather than assume a flat rate.
South Korea and Taiwan sit between these poles. Korea’s timeline shortened from roughly 29 to 13 months after the post-2014 reforms [10]; Taiwan’s median lag is 378–458 days [11].
A note on medical devices. These archetypes describe pharmaceutical reimbursement. Devices pass through different gates, including MSAC and the Prescribed List in Australia, functional-category reimbursement in Japan, and volume-based procurement of high-value consumables in China. The modelling principle is the same; the evidence requirements and timelines differ.
4. What This Does to Exit Value
The revenue trigger is misplaced. Starting the ramp at approval assumes Japan-style, near-automatic access everywhere.
A probability term is missing. Regulatory success and reimbursement are separate probabilities. Models that carry only the first overstate the case.
Part of the market may not materialise. Where a meaningful share of approved indications is never reimbursed, as in Chinese oncology, the issue is not delay but lost market.
The financial effect is material even under simple assumptions. Table 3 applies a 12% discount rate, within the range commonly used for commercial-stage life science cash flows; earlier-stage assets are usually discounted at higher rates, which would widen the losses shown.
| Scenario | PV index | Change vs. base |
|---|---|---|
| Base case: revenue ramp starts at approval | 100 | – |
| 18-month reimbursement lag | 84 | –16% |
| 24-month reimbursement lag | 80 | –20% |
| 24-month lag and 75% probability of reimbursement | 60 | –40% |
| 24-month lag and 60% probability (cf. China oncology [6]) | 48 | –52% |
Table 3. Illustrative effect of reimbursement timing and probability on the present value of a post-approval revenue stream (Biorizon Consulting calculation). The figures are conservative: they exclude negotiated price reductions and the shorter period of market exclusivity that a delayed launch leaves.
How we recommend modelling it
Treat approval and reimbursement as two distinct events, each with its own timing and probability.
Build market-specific reimbursement assumptions rather than one regional average.
Stress-test the exit case against the specific markets the go-to-market plan depends on.
Model the structure of reimbursement, not only its existence: an inadequate code or restrictive formulary tier can be as damaging as a negative decision.
Conclusion
Regulatory approval establishes that a product may be sold, not whether anyone will pay for it, when, or on what terms. An exit model that merges “approved” and “reimbursed” into one event omits the variable that, in several APAC markets, determines whether the exit case holds.
If your model has one date for approval and reimbursement, it has one date too few.
At Biorizon Consulting, reimbursement pathways are part of our market-by-market assessment. Through Biorizon Insight, we review them in scientific and commercial due diligence for investors; through Biorizon Elevate, we help founders build them into their investment case before investors ask.
References
[1] CVRx, Inc. CVRx Announces New CPT® Category I Codes for Barostim. Investor news release. https://ir.cvrx.com/news-releases/news-release-details/cvrx-announces-new-cptr-category-i-codes-barostim. Accessed: 13.10.2026. See also: Cardiac Interventions Today (2024–2025). CVRx Reports Barostim CMS Reimbursement Updates. https://citoday.com/news/cvrx-reports-barostim-cms-reimbursement-updates. Accessed: 24.07.2026.
[2] Senior, M. (2017). After Glybera's Withdrawal, What's Next for Gene Therapy? Nature Biotechnology, 35(6), 491-492. https://doi.org/10.1038/nbt0617-491. Accessed: 24.07.2026.
[3] Takayama, A., & Narukawa, M. (2016). Pharmaceutical Pricing and Reimbursement in Japan: For Faster, More Complete Access to New Drugs. Therapeutic Innovation & Regulatory Science, 50(3), 361-367. https://doi.org/10.1177/2168479015619202. Accessed: 24.07.2026.
[4] Hu, Q., Kuai, L., Xu, D., et al. (2025). Impact of Six Rounds of National Drug Price Negotiation on Availability, Cost, Use, and Prices of Targeted Drugs in China. BMC Health Services Research, 25, 1421. https://doi.org/10.1186/s12913-025-13575-y. Accessed: 27.07.2026.
[5] Zhu, Z., Zhang, J., Xu, Z., et al. (2025). Impacts of National Reimbursement Drug Price Negotiation on Drug Accessibility, Utilization, and Cost in China: A Systematic Review. International Journal for Equity in Health, 24, 36. https://doi.org/10.1186/s12939-025-02390-w. Accessed: 27.07.2026.
[6] Zhou, J., Lu, H., & Pan, J. (2024). Association of Launch Price and Clinical Value With Reimbursement Decisions for Anticancer Drugs in China. International Journal of Health Policy and Management, 13(1), 1-10. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11270615/. Accessed: 21.07.2026.
[7] Gao, Y., Laka, M., & Merlin, T. (2025). Does Regulatory and Reimbursement Parallel Processing Provide Swifter Funded Access to Medicines for Patients? Evaluation of Cancer Medicines Using the Australian Parallel Process. Value in Health, 28(3), 431-440. https://doi.org/10.1016/j.jval.2024.11.008. Accessed: 27.07.2026.
[8] Pearce, F., Lin, L., Teo, E., Ng, K., & Khoo, D. (2019). Health Technology Assessment and Its Use in Drug Policies: Singapore. Value in Health Regional Issues, 18, 176-183. https://www.valuehealthregionalissues.com/article/S2212-1099(18)30056-6/fulltext. Accessed: 21.07.2026.
[9] Agency for Care Effectiveness (2023). Methods and Process. Ministry of Health, Singapore. https://www.ace-hta.gov.sg/resources/process-methods/. Accessed: 21.07.2026.
[10] Son, K.-B. (2018). Understanding the Adoption of New Drugs Decided by Several Stakeholders in the South Korean Market: A Nonparametric Event History Analysis. Health Economics Review, 8(1), 1-10. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6755591/. Accessed: 21.07.2026.
[11] Shih, Y.R., Liao, K.H., Chen, Y.H., Lin, F.J., & Hsiao, F.Y. (2020). Reimbursement Lag of New Drugs Under Taiwan's National Health Insurance System Compared With United Kingdom, Canada, Australia, Japan, and South Korea. Clinical and Translational Science, 13(5), 916-922. https://pmc.ncbi.nlm.nih.gov/articles/PMC7485943/. Accessed: 21.07.2026.
[12] ISPOR Europe 2023. Is NRDL Supporting Access or Hindering Access in China? A Time-Trend Analysis From 2017–2022. Conference abstract. https://www.ispor.org/heor-resources/presentations-database/presentation/euro2023-3784/132422. Accessed: 09.11.2026.
This article is provided for informational purposes only and does not constitute investment advice or an offer to buy or sell any security.