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The widely cited estimate that unreproducible preclinical research costs the United States about $28 billion a year is a calculation published in 2015—not a current audit of research losses. Leonard P. Freedman, Iain M. Cockburn, and Timothy S. Simcoe arrived at the figure by applying an estimated 50% irreproducibility rate to estimated annual US preclinical research spending of $56.4 billion, using 2012 spending data. The National Academies later stressed that this was not a direct cost analysis.
How the authors calculated the $28 billion figure
In their 2015 paper, “The Economics of Reproducibility in Preclinical Research”, Freedman, Cockburn, and Simcoe estimated that US life-sciences research spending was $114.8 billion in 2012, of which $56.4 billion was preclinical research. They applied a conservative cumulative irreproducibility rate of 50% to the preclinical spending estimate:
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$56.4 billion × 50% = approximately $28 billion per year.
The authors described their estimate as approximately $28 billion spent annually on US preclinical research that was not reproducible. The underlying spending figures and the rate are estimates; the calculation does not track particular grants, experiments, or dollars and establish that each one was wasted.
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Is the estimate a current, verified loss?
No. It is a historical extrapolation based on 2012 spending data, published in 2015. It should not be presented as a measured 2026 cost, an audited budget loss, or proof that the same amount applies to current spending.
The National Academies’ 2017 report Fostering Integrity in Research notes that the $28 billion figure was not based on a direct cost analysis: it applied a 50% rate to estimated preclinical biomedical research spending. The report describes it as “intended to be used as a starting point for debate.” The original authors also acknowledge uncertainty about the true magnitude.
What can make preclinical research hard to reproduce?
The 2015 paper groups contributors into four broad areas. These are methodological and materials challenges; their presence does not, by itself, indicate misconduct.
- Biological reagents and reference materials: Materials may be mislabeled, contaminated, inconsistent, or insufficiently characterized, making results difficult to repeat across laboratories.
- Study design: Choices such as controls, sample size, randomization, and blinding can affect whether a result is reliable and reproducible.
- Data analysis and reporting: Weak statistical practices or incomplete reporting can make findings difficult to evaluate or reproduce. The National Academies also discusses barriers to access to data and code.
- Laboratory protocols: Missing detail or variation in procedures can prevent another team from carrying out the same work under comparable conditions.
The paper’s categories are broad areas of concern, not a claim that every study has all four problems or that any one factor explains the estimate.
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Does irreproducible research mean fraud?
No. A result that another team cannot reproduce may reflect differences in materials, methods, study design, analysis, or reporting. Fraud is a narrower matter involving intentional fabrication or falsification. The National Academies discusses reproducibility problems while distinguishing them from research misconduct; a failed replication alone does not establish fraud.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to interpret the headline responsibly
- Attribute the figure to Freedman, Cockburn, and Simcoe’s 2015 analysis.
- Keep its basis attached: estimated 2012 US preclinical spending of $56.4 billion multiplied by an estimated 50% cumulative irreproducibility rate.
- Call it an estimate or extrapolation, not a measured or audited loss.
- Do not treat it as a current figure or imply that all irreproducible findings result from misconduct.
The paper’s bibliographic record is available through PubMed. Contemporaneous general-audience coverage appeared in Science News; the original paper is the primary source for the calculation.
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