Recalibrating the Race: A Policy Solution to the Social Cost of First-Mover Advantage in Drug Development

By: Elias Sikavitsas

Edited By: Nikki Stancik

Photo by Matt Chinworth

In the pharmaceutical industry, speed to market is often equated with success. Companies race to advance therapies into human testing to capture the enormous commercial advantages of being first. Analysts estimate that every six-month delay in launch costs a drug about 1.8 percent of its market share, and second entrants achieve only one-third of the first mover’s peak share, even when spending equally on promotion (Régnier and Ridley 2015). McKinsey’s review of global launches similarly finds that first movers retain a 6 percent market share advantage even a decade after release (Cha and Yu 2014). These incentives encourage firms to rush from discovery to clinical trials, often before the mechanism of action is thoroughly validated. This “first-mover premium” rewards speed over certainty, particularly in fast-moving fields like oncology and immunotherapy. I propose a regulatory incentive that rewards preclinical validation to address this misalignment with commercial and scientific goals.

Checkpoint inhibitors, a novel cancer therapy that earned the 2018 Nobel Prize, are among the fastest-growing areas in biopharma, with multiple firms racing to begin trials on similar targets (Pan and Chen 2017). However, this haste carries a cost, as clinical success rates for oncology remain low. The Biotechnology Innovation Organization (BIO) reports that fewer than 8 percent of cancer drugs entering clinical trials ever reach approval, with most failures occurring in late-stage development (BIO 2021).

A systematic review by Jardim et al. (2017) identifies inadequate mechanistic understanding as a leading factor in failed oncology trials, especially when targets lacked validated biomarkers or clear pharmacodynamic endpoints. Similarly, Jentzsch et al. (2023) report that entire drug classes, such as IGF-1 receptor inhibitors, incurred billions in development costs without approved therapies, largely due to weak preclinical validation. These failures represent more than corporate losses: they also delay promising treatments, strain clinical trial capacity, and misallocate public and private investment. Jain et al. (2019) support this view, stating that late-stage attrition often stems not from luck but from “mechanistic misalignment” between biological promise and clinical reality.

The situation can be understood as a collective-action dilemma. Each company must choose between investing time in rigorous preclinical mechanistic validation or moving rapidly to capture first-mover advantages. While all firms would benefit from a standard practice of rigorous validation, the dominant individual strategy is to race ahead. The troubling aspect is that the companies and actors involved are fully aware of its downsides. Firms recognize that rushing increases the risk of costly trial failures and undermines the credibility of the field, yet competitive pressure leaves them unable to slow down without jeopardizing their position. This dynamic mirrors a Prisoner’s Dilemma, where rational self-interest produces a collectively suboptimal outcome. Empirical evidence supports this framing, with oncology attrition alone consuming billions annually in sunk costs (Jentzsch et al. 2023). From a welfare standpoint, society bears the burden of this inefficiency because resources that could fund diverse, well-validated research programs are instead tied up in duplicative or premature trials, delaying the arrival of genuinely effective therapies and limiting patient access to innovation.

To address this inefficiency, a Mechanistic Validation Voucher (MVV) program within the U.S. Food and Drug Administration could help correct this structural misalignment. Under this program, developers who publicly share rigorous preclinical validation—such as replication across independent models, mechanistic biomarker evidence, or human genetic support—before initiating human clinical testing (Phase I trials) would qualify for six additional months of regulatory exclusivity upon final drug approval. The MVV, modeled on the FDA’s existing Priority Review Voucher program, would reward transparency and rigor by linking early, high-quality validation to tangible market benefits. Because each company could independently earn the voucher, the system would reduce premature competition and align market incentives with scientific reliability rather than speed.

This proposed mechanism builds on successful precedent. The Priority Review Voucher (PRV) program, which accelerates review for drugs targeting neglected diseases, has demonstrably influenced research and development behavior (Aerts et al. 2022). PRVs trade modest extensions of exclusivity for major shifts in portfolio allocation, suggesting that well-calibrated regulatory rewards can alter investment strategy. The MVV would adapt this model, tying the reward not to the therapeutic area but to scientific rigor.

The logic is straightforward. A small, predictable extension of exclusivity increases expected net present value (NPV), or projected financial return, enough to offset the cost of slower entry. In the new payoff matrix, the validate option becomes both privately rational and socially optimal. Minikel et al. (2024) found that drugs supported by human genetic evidence were about twice as likely to succeed clinically as those without such evidence. By rewarding this kind of preclinical diligence, the MVV aligns scientific merit with commercial viability.

Implementing MVVs requires a clear definition of “rigorous validation.” Cobey et al. (2023) document persistent reproducibility gaps in translational science, while Samsa et al. (2018) outline specific practices—such as blinded replication, statistical pre-registration, and use of multiple model systems—that correlate with later clinical success. The FDA could operationalize these standards by issuing guidance similar to that used in the Biomarker Qualification Program.

Concerns about longer development timelines are valid. However, empirical data suggest that stronger validation substantially reduces downstream failure costs. Each late-stage trial failure can cost $50–100 million and delay other candidates’ development by years (Jentzsch et al. 2023). Even modest reductions in attrition would offset the societal cost of granting six additional months of exclusivity. Pilot programs could begin in high-risk, high-attrition areas such as oncology or neurodegeneration, where mechanistic rigor is most limited.

Pharmaceutical competition currently rewards speed over certainty, producing a landscape of redundant trials, wasted investment, and delayed access to more effective therapies. A Mechanistic Validation Voucher would rebalance the incentive structure, favoring evidence-based timing over reckless haste. Rather than stifling competition, the MVV would channel it toward a more productive frontier—one where the race to be first becomes a race to be right.

The views expressed in this publication are the authors' own and do not necessarily reflect the position of The Rice Journal of Public Policy, its staff, or its Editorial Board.

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References

Aerts, C., Vella Bonanno, P., Simoens, S., & Huys, I. “Priority Review Vouchers: A Systematic Review of Their Impact and Value as Policy Instruments.” Journal of Generic Medicines, 19(1), 2022, https://www.tandfonline.com/doi/full/10.1080/14656566.2022.2161366

Biotechnology Innovation Organization. Clinical Development Success Rates 2011–2020. 2021

Cha, Mike, and Felix Yu. “Pharma’s First-to-Market Advantage.” McKinsey & Company, 2014, https://www.mckinsey.com/industries/life-sciences/our-insights/pharmas-first-to-market-advantage

Cobey, Kelly D., et al. “Reproducibility in Preclinical Research: A Scoping Review.” Expert Opinion on Drug Discovery, vol. 16, no. 6, 2023, https://www.tandfonline.com/doi/full/10.1080/14656566.2022.2161366

Jain, Richa, et al. “A Review of Therapeutic Failures in Late-Stage Clinical Trials.” Expert Opinion on Pharmacotherapy, vol. 24, no. 3, 2023, pp. 389–399, https://doi.org/10.1016/j.biotechadv.2018.09.003

Jardim, David L., et al. “Factors Associated with Failure of Oncology Drugs in Late-Stage Clinical Development: A Systematic Review.” Cancer Treatment Reviews, vol. 52, 2017, https://doi.org/10.1016/j.ctrv.2016.10.009

Jentzsch, Valentin, et al. “Costs and Causes of Oncology Drug Attrition with the Example of Insulin-Like Growth Factor-1 Receptor Inhibitors.” JAMA Network Open, vol. 6, no. 7, 2023, e2324977, https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2807710

Minikel, Eric V., et al. “Refining the Impact of Human Genetic Evidence on Clinical Success.” Nature, vol. 629, no. 8012, 2024, pp. 624–629,

https://pubmed.ncbi.nlm.nih.gov/38632401

Pan, Chia-Lin, and Feng-Chi Chen. “Patent Trend and Competitive Analysis of Cancer Immunotherapy in the United States.” Human Vaccines & Immunotherapeutics, vol. 13, no. 11, 2017, pp. 2583–2593, https://doi.org/10.1080/21645515.2017.1361074

Régnier, Stéphane, and David B. Ridley. “Forecasting Market Share in the U.S. Pharmaceutical Market.” Nature Reviews Drug Discovery, vol. 14, no. 9, 2015, pp. 594–595, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2763659

Samsa, Gregory P., et al. “A Guide to Reproducibility in Preclinical Research.” Academic Medicine, vol. 94, no. 1, 2019, pp. 47–52, https://www.researchgate.net/publication/326340038_A_Guide_to_Reproducibility_in_Preclinical_Research

Schulze, Ulrich, and Mathias Ringel. “What Matters Most in Biopharma Commercial Success?” Boston Consulting Group, 2013, https://www.bcg.com/publications/2013/innovation-what-matters-most-biopharma-commercial-success