The price of innovation: new estimates of drug development costs
Open accessAbstract
The research and development costs of 68 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 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 new drug is 403 million US dollars (2000 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a real discount rate of 11% yields a total pre-approval cost estimate of 802 million US dollars (2000 dollars). When compared to the results of an earlier study with a similar methodology, total capitalized costs were shown to have increased at an annual rate of 7.4% above general price inflation.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Conventional pharmaceutical development and deployment typically require hundreds of millions of US dollars.
“conventional pharmaceutical development and deployment typically require hundreds of millions of US dollars (51)”
Cited by
Sorted by citations
Can the pharmaceutical industry reduce attrition rates?
Kola, I., & Landis, J. (2004) · Nature Reviews Drug Discovery · doi:10.1038/nrd1470 · Cited by 4,167 · see citing works
The answer is 17 years, what is the question: understanding time lags in translational research
Morris, Z. S., Wooding, S., & Grant, J. (2011) · Journal of the Royal Society of Medicine · doi:10.1258/jrsm.2011.110180 · Cited by 3,340 · see citing works
Innovation in the pharmaceutical industry: New estimates of R&D costs
DiMasi, J. A., Grabowski, H. G., & Hansen, R. W. (2016) · Journal of Health Economics · doi:10.1016/j.jhealeco.2016.01.012 · Cited by 3,359 · see citing works
Self-citationThe present and future role of microfluidics in biomedical research
Sackmann, E. K., Fulton, A. L., & Beebe, D. J. (2014) · Nature · doi:10.1038/nature13118 · Cited by 2,995 · see citing works
Clinical development success rates for investigational drugs
Hay, M., Thomas, D. W., Craighead, J. L., Economides, C., & Rosenthal, J. (2014) · Nature Biotechnology · doi:10.1038/nbt.2786 · Cited by 2,536 · see citing works
Combination therapy in combating cancer
Mokhtari, R. B., Homayouni, T. S., Baluch, N., Morgatskaya, E., Kumar, S., Das, B., & Yeger, H. (2017) · Oncotarget · doi:10.18632/oncotarget.16723 · Cited by 2,543 · see citing works
Edmondson, R., Broglie, J. J., Adcock, A. F., & Yang, L. (2014) · ASSAY and Drug Development Technologies · doi:10.1089/adt.2014.573 · Cited by 2,515 · see citing works
Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018
Wouters, O. J., McKee, M., & Luyten, J. (2020) · JAMA · doi:10.1001/jama.2020.1166 · Cited by 1,531 · see citing works
The ascent of mouse: advances in modelling human depression and anxiety
Cryan, J. F., & Holmes, A. (2005) · Nature Reviews Drug Discovery · doi:10.1038/nrd1825 · Cited by 1,198 · see citing works
The productivity crisis in pharmaceutical R&D
Pammolli, F., Magazzini, L., & Riccaboni, M. (2011) · Nature Reviews Drug Discovery · doi:10.1038/nrd3405 · Cited by 918 · see citing works
Trends in antimicrobial drug development: Implications for the future
Spellberg, B., Powers, J. H., Brass, E. P., Miller, L. G., & Edwards, J. E. (2004) · Clinical Infectious Diseases · doi:10.1086/420937 · Cited by 867 · see citing works
Role of computer-aided drug design in modern drug discovery
Macalino, S. J. Y., Gosu, V., Hong, S., & Choi, S. (2015) · Archives of Pharmacal Research · doi:10.1007/s12272-015-0640-5 · Cited by 762 · see citing works
Delivering affordable cancer care in high-income countries
Sullivan, R., Peppercorn, J., Sikora, K., Zalcberg, J., Meropol, N. J., Amir, E., Khayat, D., Boyle, P., Autier, P., Tannock, I. F., et al. (2011) · The Lancet Oncology · doi:10.1016/s1470-2045(11)70141-3 · Cited by 718 · see citing works
Ethical and Scientific Implications of the Globalization of Clinical Research
Glickman, S. W., McHutchison, J. G., Peterson, E. D., Cairns, C. B., Harrington, R. A., Califf, R. M., & Schulman, K. A. (2009) · New England Journal of Medicine · doi:10.1056/nejmsb0803929 · Cited by 710 · see citing works
Organs-on-a-Chip: A Fast Track for Engineered Human Tissues in Drug Development
Ronaldson-Bouchard, K., & Vunjak-Novakovic, G. (2018) · Cell Stem Cell · doi:10.1016/j.stem.2018.02.011 · Cited by 657 · see citing works
Essential medicines for universal health coverage
Wirtz, V. J., Hogerzeil, H. V., Gray, A. L., Bigdeli, M., de Joncheere, C. P., Ewen, M. A., Gyansa-Lutterodt, M., Jing, S., Luiza, V. L., Mbindyo, R. M., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(16)31599-9 · Cited by 661 · see citing works
Itraconazole, a Commonly Used Antifungal that Inhibits Hedgehog Pathway Activity and Cancer Growth
Kim, J., Tang, J. Y., Gong, R., Kim, J., Lee, J. J., Clemons, K. V., Chong, C. R., Chang, K. S., Fereshteh, M., Gardner, D., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2010.02.027 · Cited by 527 · see citing works
Key cost drivers of pharmaceutical clinical trials in the United States
Sertkaya, A., Wong, H.-H., Jessup, A., & Beleche, T. (2016) · Clinical Trials · doi:10.1177/1740774515625964 · Cited by 401 · see citing works
Potential of quantum computing for drug discovery
Cao, Y., Romero, J., & Aspuru-Guzik, A. (2018) · IBM Journal of Research and Development · doi:10.1147/jrd.2018.2888987 · Cited by 357 · see citing works
Economics of New Oncology Drug Development
DiMasi, J. A., & Grabowski, H. G. (2007) · Journal of Clinical Oncology · doi:10.1200/jco.2006.09.0803 · Cited by 348 · see citing works
Self-citationMitosis is not a key target of microtubule agents in patient tumors
Komlodi-Pasztor, E., Sackett, D., Wilkerson, J., & Fojo, T. (2011) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2010.228 · Cited by 312 · see citing works
WITHDRAWN—a resource for withdrawn and discontinued drugs
Siramshetty, V. B., Nickel, J., Omieczynski, C., Gohlke, B.-O., Drwal, M. N., & Preissner, R. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1192 · Cited by 286 · see citing works
RetractedSuccessful aging: Advancing the science of physical independence in older adults
Anton, S. D., Woods, A. J., Ashizawa, T., Barb, D., Buford, T. W., Carter, C. S., Clark, D. J., Cohen, R. A., Corbett, D. B., Cruz-Almeida, Y., et al. (2015) · Ageing Research Reviews · doi:10.1016/j.arr.2015.09.005 · Cited by 292 · see citing works
Using evidence-based internet interventions to reduce health disparities worldwide.
Muñoz, R. F. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1463 · Cited by 242 · see citing works
Ye, Q., Hsieh, C.-Y., Yang, Z., Kang, Y., Chen, J., Cao, D., He, S., & Hou, T. (2021) · Nature Communications · doi:10.1038/s41467-021-27137-3 · Cited by 261 · see citing works
Risk in vaccine research and development quantified
Pronker, E. S., Weenen, T. C., Commandeur, H., Claassen, E. H. J. H. M., & Osterhaus, A. D. M. E. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057755 · Cited by 253 · see citing works
Consensus scoring criteria for improving enrichment in virtual screening.
Yang, J.-M., Chen, Y.-F., Shen, T.-W., Kristal, B. S., & Hsu, D. F. (2005) · Journal of Chemical Information and Modeling · doi:10.1021/ci050034w · Cited by 241 · see citing works
Yip, D., & Cho, C. H. (2013) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2013.03.008 · Cited by 236 · see citing works
Pharmaceutical research and development: what do we get for all that money?
Light, D. W., & Lexchin, J. R. (2012) · BMJ · doi:10.1136/bmj.e4348 · Cited by 258 · see citing works
Woolf, S. H. (2005) · The Annals of Family Medicine · doi:10.1370/afm.406 · Cited by 208 · see citing works
Lu, S.-H., Wu, J. W., Liu, H.-L., Zhao, J.-H., Liu, K.-T., Chuang, C.-K., Lin, H.-Y., Tsai, W.-B., & Ho, Y. (2011) · Journal of Biomedical Science · doi:10.1186/1423-0127-18-8 · Cited by 204 · see citing works
Multi-organ system for the evaluation of efficacy and off-target toxicity of anticancer therapeutics
McAleer, C. W., Long, C. J., Elbrecht, D., Sasserath, T., Bridges, L. R., Rumsey, J. W., Martin, C., Schnepper, M., Wang, Y., Schuler, F., et al. (2019) · Science Translational Medicine · doi:10.1126/scitranslmed.aav1386 · Cited by 199 · see citing works
Drug discovery through stem cell-based organoid models
Ranga, A., Gjorevski, N., & Lutolf, M. P. (2014) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2014.02.006 · Cited by 195 · see citing works
Synergistic drug combinations for tuberculosis therapy identified by a novel high-throughput screen
Ramón-García, S., Ng, C., Anderson, H., Chao, J. D., Zheng, X., Pfeifer, T., Av-Gay, Y., Roberge, M., & Thompson, C. J. (2011) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.00474-11 · Cited by 185 · see citing works
DNA photodamage stimulates melanogenesis and other photoprotective responses
Gilchrest, B. A., & Eller, M. S. (1999) · Journal of Investigative Dermatology Symposium Proceedings · doi:10.1038/sj.jidsp.5640178 · Cited by 182 · see citing works
Antonarakis, E. S., Heath, E. I., Smith, D. C., Rathkopf, D., Blackford, A. L., Danila, D. C., King, S., Frost, A., Ajiboye, A. S., Zhao, M., et al. (2013) · The Oncologist · doi:10.1634/theoncologist.2012-314 · Cited by 180 · see citing works
High-throughput organ-on-a-chip systems: Current status and remaining challenges
Probst, C., Schneider, S., & Loskill, P. (2018) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2018.02.004 · Cited by 171 · see citing works
Adult cancer clinical trials that fail to complete: an epidemic?
Stensland, K. D., McBride, R. B., Latif, A., Wisnivesky, J., Hendricks, R., Roper, N., Boffetta, P., Hall, S. J., Oh, W. K., & Galsky, M. D. (2014) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/dju229 · Cited by 161 · see citing works
van Westen, G. J. P., Wegner, J. K., IJzerman, A. P., van Vlijmen, H. W. T., & Bender, A. (2011) · MedChemComm · doi:10.1039/c0md00165a · Cited by 176 · see citing works
Speich, B., von Niederhäusern, B., Schur, N., Hemkens, L. G., Fürst, T., Bhatnagar, N., Alturki, R., Agarwal, A., Kasenda, B., Pauli-Magnus, C., et al. (2018) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2017.12.018 · Cited by 146 · see citing works
Thafar, M. A., Olayan, R. S., Ashoor, H., Albaradei, S., Bajic, V. B., Gao, X., Gojobori, T., & Essack, M. (2020) · Journal of Cheminformatics · doi:10.1186/s13321-020-00447-2 · Cited by 143 · see citing works
Computer-Aided Psychological Treatments: Evolving Issues
Marks, I., & Cavanagh, K. (2009) · Annual Review of Clinical Psychology · doi:10.1146/annurev.clinpsy.032408.153538 · Cited by 133 · see citing works
Applying computational modeling to drug discovery and development
Kumar, N., Hendriks, B. S., Janes, K. A., de Graaf, D., & Lauffenburger, D. A. (2006) · Drug Discovery Today · doi:10.1016/j.drudis.2006.07.010 · Cited by 131 · see citing works
Bioengineered 3D Human Kidney Tissue, a Platform for the Determination of Nephrotoxicity
DesRochers, T. M., Suter, L., Roth, A., & Kaplan, D. L. (2013) · PLoS ONE · doi:10.1371/journal.pone.0059219 · Cited by 128 · see citing works
Novel Methods and Technologies for 21st-Century Clinical Trials: A Review
Dorsey, E. R., Venuto, C., Venkataraman, V., Harris, D. A., & Kieburtz, K. (2015) · JAMA Neurology · doi:10.1001/jamaneurol.2014.4524 · Cited by 118 · see citing works
Bioinformatics opportunities for identification and study of medicinal plants
Sharma, V., & Sarkar, I. N. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbs021 · Cited by 121 · see citing works
Fraczek, J., Bolleyn, J., Vanhaecke, T., Rogiers, V., & Vinken, M. (2013) · Archives of Toxicology · doi:10.1007/s00204-012-0983-3 · Cited by 119 · see citing works
Long-Term Culture and Coculture of Primary Rat and Human Hepatocytes
Shulman, M., & Nahmias, Y. (2012) · Methods in Molecular Biology · doi:10.1007/978-1-62703-125-7_17 · Cited by 117 · see citing works
“Drug development is currently estimated at $400 million/drug with the majority spent on preclinical screening (5).”
BackgroundQuintana, D. S., Guastella, A. J., Westlye, L. T., & Andreassen, O. A. (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.166 · Cited by 107 · see citing works
Molecular imaging with SPECT as a tool for drug development
Gomes, C. M., Abrunhosa, A. J., Ramos, P., & Pauwels, E. K. J. (2011) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2010.09.015 · Cited by 100 · see citing works
Booth, F. W., & Laye, M. J. (2009) · The Journal of Physiology · doi:10.1113/jphysiol.2009.179507 · Cited by 99 · see citing works
Repurposing quinacrine for treatment-refractory cancer
Oien, D. B., Pathoulas, C. L., Ray, U., Thirusangu, P., Kalogera, E., & Shridhar, V. (2021) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2019.09.021 · Cited by 87 · see citing works
Accurate prediction of human drug toxicity: a major challenge in drug development
Li, A. P. (2004) · Chemico-Biological Interactions · doi:10.1016/j.cbi.2004.09.008 · Cited by 82 · see citing works
Toward the broad adoption of 3D tumor models in the cancer drug pipeline
Cox, M. C., Reese, L. M., Bickford, L. R., & Verbridge, S. S. (2015) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.5b00172 · Cited by 80 · see citing works
Butler, J., Subacius, H., Vaduganathan, M., Fonarow, G. C., Ambrosy, A. P., Konstam, M. A., Maggioni, A., Mentz, R. J., Swedberg, K., Zannad, F., et al. (2013) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2012.10.025 · Cited by 60 · see citing works
GFscore: a general nonlinear consensus scoring function for high-throughput docking.
Betzi, S., Suhre, K., Chétrit, B., Guerlesquin, F., & Morelli, X. (2006) · Journal of Chemical Information and Modeling · doi:10.1021/ci0600758 · Cited by 51 · see citing works
Toxicology Testing in Drug Discovery and Development
Dorato, M. A., & Buckley, L. A. (2007) · Current Protocols in Toxicology · doi:10.1002/0471141755.tx1901s31 · Cited by 49 · see citing works
Computational Biology and Drug Discovery: From Single-Target to Network Drugs
Ambesi-Impiombato, A., & Bernardo, D. (2006) · Current Bioinformatics · doi:10.2174/157489306775330598 · Cited by 47 · see citing works
Quintana, D. S., & Woolley, J. D. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.06.021 · Cited by 46 · see citing works
Zhang, X., & Yang, S.-T. (2011) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2010.11.012 · Cited by 43 · see citing works
Zhou, H., Cao, H., & Skolnick, J. (2018) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.8b00309 · Cited by 39 · see citing works
Strom, J. B., Faridi, K. F., Butala, N. M., Zhao, Y., Tamez, H., Valsdottir, L. R., Brennan, J. M., Shen, C., Popma, J. J., Kazi, D. S., et al. (2020) · Circulation · doi:10.1161/circulationaha.120.046159 · Cited by 37 · see citing works
Kansal, A. R., & Trimmer, J. (2005) · IEE Proceedings - Systems Biology · doi:10.1049/ip-syb:20050043 · Cited by 32 · see citing works
Genomics and Cardiovascular Drug Development
Plump, A. S., & Lum, P. Y. (2009) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2008.11.050 · Cited by 31 · see citing works
Microfluidic systems for modeling digestive cancer: a review of recent progress
Razavi, Z., Soltani, M., Pazoki-Toroudi, H., & Dabagh, M. (2024) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/ad6f15 · Cited by 24 · see citing works
Natarajan, S., Govindaraju, A., Rajmohamed, M., Palanisamy, P., & Abdulkader, A. (2017) · Pharmacognosy Magazine · doi:10.4103/pm.pm_57_17 · Cited by 20 · see citing works
Gabriel, J., Höfner, G., & Wanner, K. T. (2019) · Frontiers in Chemistry · doi:10.3389/fchem.2019.00665 · Cited by 20 · see citing works
Burt, T., Vuong, L. T., Baker, E., Young, G. C., McCartt, A. D., Bergstrom, M., Sugiyama, Y., & Combes, R. (2018) · Alternatives to Laboratory Animals · doi:10.1177/026119291804600603 · Cited by 18 · see citing works
Xue, H., Zhang, L., Shi, Y., Zhang, H., Zhang, C., Liu, Y., Tan, W., & Liu, Y. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1630588 · Cited by 15 · see citing works
- Authors
- DiMasi, J. A., Hansen, R. W., & Grabowski, H. G.
- Affiliations
- Tufts University (US)
- University of Rochester (US)
- Duke University (US)
- Corresponding author
- DiMasi, Joseph A
- ORCID
- DiMasi, Joseph A
- Venue
- Journal of Health Economics
- Publisher
- Elsevier BV
- Published
- 2003-03
- Volume
- 22
- Issue
- 2
- Pages
- 151-185
- ISSN
- 0167-6296 (ISSN-L)
- OpenAlex
- W2121175754
- Cited by
- 4,265
- References
- 0
- Citations by year
- 2026: 50 · 2025: 71 · 2024: 85 · 2023: 106 · 2022: 123 · 2021: 143 · 2020: 142 · 2019: 178 · 2018: 164 · 2017: 161 · 2016: 179 · 2015: 233 · 2014: 274 · 2013: 283 · 2012: 299
- FWCI
- 423.30
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-nd
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- Journal of Health Economics (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DukeSpace (Duke University) (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Pharmaceutical Economics and Policy
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmaceutical industry and healthcare
- Keywords
- drug development costs, pharmaceutical industry, cost of innovation, capitalized cost, marketing approval, pharmaceutical companies
- MeSH terms
- Capital Expenditures, Costs and Cost Analysis, Data Collection, Drug Evaluation, Drug Industry, Drug Evaluation, Preclinical, Humans, Inflation, Economic, Organizational Innovation, Research Support as Topic, United States, Drugs, Investigational, Drug Approval
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