Evidence map›Paper›PMID 37115539›Full record

ArticleJAMA health forum2023

Comparison of Research Spending on New Drug Approvals by the National Institutes of Health vs the Pharmaceutical Industry, 2010-2019.

Ekaterina Galkina Cleary, Matthew J Jackson, Edward W Zhou, Fred D Ledley

Open access · goldAbstract read
In one paragraph

Article in JAMA health forum, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
30.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 53 citations in OpenAlex.

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  13. "The ship is going down and we are powerless":bioRxiv : the preprint server for biology · 2025
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  17. Applications of artificial intelligence in drug discovery for neurological diseases.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2025
    Review
  18. Article
  19. Policy options for the drug pricing conundrum.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Ekaterina Galkina ClearyCenter for Integration of Science and Industry, Bentley University, Waltham, Massachusetts.
Matthew J JacksonCenter for Integration of Science and Industry, Bentley University, Waltham, Massachusetts.
Edward W ZhouCenter for Integration of Science and Industry, Bentley University, Waltham, Massachusetts.
Fred D LedleyCenter for Integration of Science and Industry, Bentley University, Waltham, Massachusetts.
Bentley University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Government and the pharmaceutical industry make substantive contributions to pharmaceutical innovation. This study compared the investments by the National Institutes of Health (NIH) and industry and estimated the cost basis for assessing the balance of social and private returns. Objectives: To compare NIH and industry investments in recent drug approvals. Design, Setting, and Participants: This cross-sectional study of NIH funding associated with drugs approved by the FDA from 2010 to 2019 was conducted from May 2020 to July 2022 and accounted for basic and applied research, failed clinical candidates, and discount rates for government spending compared with analogous estimates of industry investment. Main Outcomes and Measures: Costs from the NIH for research associated with drug approvals. Results: Funding from the NIH was contributed to 354 of 356 drugs (99.4%) approved from 2010 to 2019 totaling $187 billion, with a mean (SD) $1344.6 ($1433.1) million per target for basic research on drug targets and $51.8 ($96.8) million per drug for applied research on products. Including costs for failed clinical candidates, mean (SD) NIH costs were $1441.5 ($1372.0) million per approval or $1730.3 ($1657.6) million per approval, estimated with a 3% discount rate. The mean (SD) NIH spending was $2956.0 ($3106.3) million per approval with a 10.5% cost of capital, which estimates the cost savings to industry from NIH spending. Spending and approval by NIH for 81 first-to-target drugs was greater than reported industry spending on 63 drugs approved from 2010 to 2019 (difference, -$1998.4 million; 95% CI, -$3302.1 million to -$694.6 million; P = .003). Spending from the NIH was not less than industry spending considering clinical failures, a 3% discount rate for NIH spending, and a 10.5% cost of capital for the industry (difference, -$1435.3 million; 95% CI, -$3114.6 million to $244.0 million; P = .09) or when industry spending included prehuman research (difference, -$1394.8 million; 95% CI, -$3774.8 million to $985.2 million; P = .25). Accounting for spillovers of NIH-funded basic research on drug targets to multiple products, NIH costs were $711.3 million with a 3% discount rate, which was less than the range of reported industry costs with 10.5% cost of capital. Conclusions and Relevance: The results of this cross-sectional study found that NIH investment in drugs approved from 2010 to 2019 was not less than investment by the pharmaceutical industry, with comparable accounting for basic and applied research, failed clinical trials, and cost of capital or discount rates. The relative scale of NIH and industry investment may provide a cost basis for calibrating the balance of social and private returns from investments in pharmaceutical innovation.

Indexed as

Drug ApprovalDrug IndustryCross-Sectional StudiesNational Institutes of Health (U.S.)Pharmaceutical PreparationsUnited StatesPharmaceutical Preparations

Identifiers

PMID37115539
PMCPMC10148199
OpenAlexW4367311265

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.