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      • Record: found
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      Is Open Access

      Use of Clinical Trial Characteristics to Estimate Costs of New Drug Development

      research-article
      , PhD, MPP 1 , , , PhD 2 , , MA 1 , , BA 2 , 3 , , MSc, MEng 2 , , MD, MS 2
      JAMA Network Open
      American Medical Association

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          Key Points

          Question

          What is the estimated cost to develop a new drug and how do research and development (R&D) costs vary across firms?

          Findings

          This economic evaluation examining 268 US-traded drug developers found that, in 2019, 20 firms accounted for 80.8% of R&D activity (measured as clinical trial patient-months) and had 27.4% lower mean and 26.7% lower median costs per patient-month vs other firms. Median and mean costs per 2019 new approved drug were $708 million and $1.31 billion, respectively, after cost of capital and discontinuation adjustments.

          Meaning

          These findings suggest that R&D costs per new drug are highly skewed, so both median and mean costs should be considered.

          Abstract

          This economic evaluation estimates per-drug research and development costs and describes firm-level costs per discrete unit of research and development activity.

          Abstract

          Importance

          Despite their importance to patients, health, and industry, the magnitude of investments in drug research and development (R&D) remain nebulous. New policies require more granular and transparent R&D cost estimates to better balance incentives for innovation and returns to developers.

          Objective

          To estimate per-drug R&D costs using a novel, reproduceable approach and to describe firm-level R&D costs per discrete unit of R&D activity (1 patient-month).

          Design, Setting, and Participants

          This economic evaluation used cross-sectional data to estimate 2014 to 2019 costs per patient-month. Costs per patient-month were calculated using data from 268 US publicly traded drug developers, contributing 1311 firm-year observations, that were highest ranked by assets or market capitalization, after exclusions. Per-drug costs were calculated from all R&D activity through approval for a cohort of 38 new drugs approved by the US Food and Drug Administration in 2019. Data were analyzed from January 2022 to July 2024.

          Exposure

          R&D activity, measured in terms of clinical trial patient-months.

          Main Outcomes and Measures

          This study used a 2-step approach to estimate R&D costs, first allocating firm-year–level total R&D spending across similarly aggregated patient-months, and then aggregating these incremental costs to estimate drug-level R&D costs per new drug.

          Results

          Among 268 developers assessed, 20 large firms accounted for 80.8% of all patient-months and had 27.4% lower mean and 26.7% lower median costs per patient-month compared with other firms. Each 1% increase in patient-months was associated with a 0.9% increase in R&D costs. R&D costs per new drug were highly skewed, with a lower median (IQR), at $708 million ($247 million to $1.42 billion) than mean (SD), at $1.31 ($1.92) billion, after adjusting for the cost of capital and discontinued products. Without these adjustments, direct costs per new drug were a median (IQR) of $150 ($67.6-$453) million and a mean (SD) $369 of ($684) million. While estimated R&D costs varied in sensitivity analyses, mean costs were always substantially greater than median costs.

          Conclusions and Relevance

          This economic evaluation found median per-drug R&D costs toward the lower end of the range from prior studies, with a mean closer to the middle of the existing range despite the broad scope of included costs. These findings suggest parallel development across indications, adjustment for discontinued products, and a small number of expensive development programs are particularly important drivers of R&D costs.

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          Most cited references24

          • Record: found
          • Abstract: found
          • Article: not found

          Innovation in the pharmaceutical industry: New estimates of R&D costs.

          The research and development costs of 106 randomly selected new drugs were obtained from a survey of 10 pharmaceutical firms. These data were used to estimate the average pre-tax cost of new drug and biologics development. The costs of compounds abandoned during testing were linked to the costs of compounds that obtained marketing approval. The estimated average out-of-pocket cost per approved new compound is $1395 million (2013 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a real discount rate of 10.5% yields a total pre-approval cost estimate of $2558 million (2013 dollars). When compared to the results of the previous study in this series, total capitalized costs were shown to have increased at an annual rate of 8.5% above general price inflation. Adding an estimate of post-approval R&D costs increases the cost estimate to $2870 million (2013 dollars).
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            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Estimation of clinical trial success rates and related parameters

            SUMMARY Previous estimates of drug development success rates rely on relatively small samples from databases curated by the pharmaceutical industry and are subject to potential selection biases. Using a sample of 406 038 entries of clinical trial data for over 21 143 compounds from January 1, 2000 to October 31, 2015, we estimate aggregate clinical trial success rates and durations. We also compute disaggregated estimates across several trial features including disease type, clinical phase, industry or academic sponsor, biomarker presence, lead indication status, and time. In several cases, our results differ significantly in detail from widely cited statistics. For example, oncology has a 3.4% success rate in our sample vs. 5.1% in prior studies. However, after declining to 1.7% in 2012, this rate has improved to 2.5% and 8.3% in 2014 and 2015, respectively. In addition, trials that use biomarkers in patient-selection have higher overall success probabilities than trials without biomarkers.
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              Economic Welfare and the Allocation of Resources for Invention

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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                6 January 2025
                January 2025
                6 January 2025
                : 8
                : 1
                : e2453275
                Affiliations
                [1 ]RAND, Arlington, Virginia
                [2 ]RAND, Santa Monica, California
                [3 ]Now with Department of Economics, University of California, Los Angeles
                Author notes
                Article Information
                Accepted for Publication: November 3, 2024.
                Published: January 6, 2025. doi:10.1001/jamanetworkopen.2024.53275
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2025 Mulcahy A et al. JAMA Network Open.
                Corresponding Author: Andrew Mulcahy, PhD, MPP, RAND, 1200 S Hayes St, Arlington, VA 22202 ( amulcahy@ 123456rand.org ).
                Author Contributions: Drs Mulcahy and Rennane had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Mulcahy, Rennane, Baker.
                Acquisition, analysis, or interpretation of data: All authors.
                Drafting of the manuscript: Mulcahy, Rennane, Schwam, Dickerson.
                Critical review of the manuscript for important intellectual content: All authors.
                Statistical analysis: Mulcahy, Rennane, Dickerson, Shetty.
                Obtained funding: Mulcahy, Rennane.
                Administrative, technical, or material support: Mulcahy, Schwam, Baker.
                Supervision: Mulcahy, Rennane.
                Conflict of Interest Disclosures: Dr Mulcahy reported receiving grants from Arnold Ventures outside the submitted work. Dr Baker reported grants from Genentech outside the submitted work, and that his spouse is employed by Takeda Pharmaceuticals. No other disclosures were reported.
                Funder/Support: This work was funded by a grant from Arnold Ventures (principal investigators: Drs Mulcahy and Rennane).
                Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Data Sharing Statement: See Supplement 2.
                Article
                zoi241488
                10.1001/jamanetworkopen.2024.53275
                11704977
                39761045
                e6024756-75c2-4c3e-896c-a24ae5e9baf0
                Copyright 2025 Mulcahy A et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 27 August 2024
                : 3 November 2024
                Categories
                Research
                Original Investigation
                Online Only
                Health Policy

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