The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Scientific and Regulatory Reasons for Delay and Denial of FDA Approval of Initial Applications for New Drugs, 2000-2012
Abstract
IMPORTANCE: Some new drug applications fail because of inadequate drug performance and others are not approved because the information submitted to the US Food and Drug Administration (FDA) is unsatisfactory to make that determination. Resubmission of failed applications is costly, delaying marketing approval and the availability of new drugs to patients. OBJECTIVE: To identify the reasons that FDA marketing approval for new drugs was delayed or denied. DESIGN, SETTING, AND PARTICIPANTS: A retrospective review of FDA documents and extraction of data were performed. We examined all drug applications first submitted to the FDA between 2000 and 2012 for new molecular entities (NMEs), which are active ingredients never before marketed in the United States in any form. Using FDA correspondence and reviews, we investigated the reasons NMEs failed to obtain FDA approval. MAIN OUTCOMES AND MEASURES: Reasons for delayed FDA approval or nonapproval of NME applications. RESULTS: Of the 302 identified NME applications, 151 (50%) were approved when first submitted and 222 (73.5%) were ultimately approved. Seventy-one applications required 1 or more resubmissions before approval, with a median delay to approval of 435 days following the first unsuccessful submission. Of the unsuccessful first-time applications, 24 (15.9%) included uncertainties related to dose selection, 20 (13.2%) choice of study end points that failed to adequately reflect a clinically meaningful effect, 20 (13.2%) inconsistent results when different end points were tested, 17 (11.3%) inconsistent results when different trials or study sites were compared, and 20 (13.2%) poor efficacy when compared with the standard of care. The frequency of safety deficiencies was similar among never-approved drugs compared with those with delayed approval (43 of 80 never approved [53.8%] vs 37 of 71 eventually approved [52.1%]; difference, 1.7% [95% CI, -14.86% to 18.05%]; P = .87). However, efficacy deficiencies were significantly more frequent among the never-approved drugs than among those with delayed approvals (61 of 80 never approved [76.3%] vs 28 of 71 eventually approved [39.4%]; difference, 36.9% [95% CI, 20.25% to 50.86%]; P < .001). CONCLUSIONS AND RELEVANCE: Several potentially preventable deficiencies, including failure to select optimal drug doses and suitable study end points, accounted for significant delays in the approval of new drugs. Understanding the reasons for previous failures is helpful to improve the efficiency of clinical development for new drugs.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Can the pharmaceutical industry reduce attrition rates?
Kola, I., & Landis, J. (2004) · Nature Reviews Drug Discovery · doi:10.1038/nrd1470 · Cited by 4,167
Arrowsmith, J. (2011) · Nature Reviews Drug Discovery · doi:10.1038/nrd3439 · Cited by 622
Cited by
IBM Watson: How Cognitive Computing Can Be Applied to Big Data Challenges in Life Sciences Research
Chen, Y., Elenee Argentinis, J., & Weber, G. (2016) · Clinical Therapeutics · doi:10.1016/j.clinthera.2015.12.001 · Cited by 466
Nanoparticle protein corona: from structure and function to therapeutic targeting
Bashiri, G., Padilla, M. S., Swingle, K. L., Shepherd, S. J., Mitchell, M. J., & Wang, K. (2023) · Lab on a Chip · doi:10.1039/d2lc00799a · Cited by 296
A proposal for a drug product Manufacturing Classification System (MCS) for oral solid dosage forms
Leane, M., Pitt, K., Reynolds, G., & The Manufacturing Classification System (MCS) Working Group (2015) · Pharmaceutical Development and Technology · doi:10.3109/10837450.2014.954728 · Cited by 277
Cardiovascular Drug Development
Fordyce, C. B., Roe, M. T., Ahmad, T., Libby, P., Borer, J. S., Hiatt, W. R., Bristow, M. R., Packer, M., Wasserman, S. M., Braunstein, N., et al. (2015) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2015.03.016 · Cited by 202
Powers, J. H., Patrick, D. L., Walton, M. K., Marquis, P., Cano, S., Hobart, J., Isaac, M., Vamvakas, S., Slagle, A., Molsen, E., et al. (2017) · Value in Health · doi:10.1016/j.jval.2016.11.005 · Cited by 191
Metadata
- Authors
- Sacks, L. V., Shamsuddin, H. H., Yasinskaya, Y. I., Bouri, K., Lanthier, M. L., & Sherman, R. E.
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2014-01-22
- Volume
- 311
- Issue
- 4
- Pages
- 378
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W1986188871
- Cited by
- 214
- References
- 2
- FWCI
- 54.10
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Scientific and Regulatory Reasons for Delay and Denial of FDA Approval of Initial Applications for New Drugs, 2000-2012. https://app.cochat.ai/papers/10.1001/jama.2013.282542
- The paper
- Sacks, L. V., Shamsuddin, H. H., Yasinskaya, Y. I., Bouri, K., Lanthier, M. L., & Sherman, R. E. (2014). Scientific and Regulatory Reasons for Delay and Denial of FDA Approval of Initial Applications for New Drugs, 2000-2012. JAMA. https://doi.org/10.1001/jama.2013.282542
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.