Phase II and Phase III attrition rates 2011–2012
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Over 80% of anticancer drug candidates fail during clinical screening due to weak efficacy or adverse events.
“However, the success rate of anticancer drugs in clinical trials is very low, with over 80% of drug candidates failing during clinical screening due to weak efficacy or adverse events4–7.”
From Tumor-on-a-chip: from bioinspired design to biomedical application (2021) · cites this paper as [6]
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BackgroundPersonalized In Vitro and In Vivo Cancer Models to Guide Precision Medicine
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“The majority of projects fail for problems unrelated to a therapeutic hypothesis which may be due to unexpected side effects and tolerability [29, 30].”
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“A major concern in the pharmaceutical industry is late-stage failure, where novel compounds that show considerable potential in preclinical and animal studies turn out to lack efficacy or have important toxicological side effects in phase III clinical trials (6).”
BackgroundOpen Targets: a platform for therapeutic target identification and validation
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“However, analysis of progress through development pipelines has highlighted that lack of efficacy is a major cause of failure, particularly in the later, more expensive, clinical stages (3,4).”
BackgroundFailure of Investigational Drugs in Late-Stage Clinical Development and Publication of Trial Results
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“The problem is not unique to the United States; a recent analysis concluded in 2011 by the Centre for Medicine Research in the United Kingdom found that in the prior 3 years Phase II and III clinical trials had experienced rising failure rates, with only 18% of drugs making it out of Phase II to Phase III testing (14,…”
The emerging role of mass spectrometry-based proteomics in drug discovery
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WITHDRAWN—a resource for withdrawn and discontinued drugs
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“changing strategies (7 %), commercial reasons (5 %) and operational challenges (5 %) are the most probable reasons of failures that happened in phase II and phase III of clinical development [21].”
BackgroundRodent models of post-traumatic stress disorder: behavioral assessment
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“Why do so many clinical trials fail? A series of studies analyzed failures in phase II and phase III clinical trials for the time periods of 2007–2010 [5] and 2013–2015 [6], and reported that the most common reason for failure was lack of efficacy (56% and 52%, for each period respectively), followed by safety issues…”
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An Overview of Machine Learning and Big Data for Drug Toxicity Evaluation
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“We also know that more and more drugs are failing in clinical studies due to poor efficacy (Arrowsmith and Miller, 2013).”
BackgroundImpact of organ-on-a-chip technology on pharmaceutical R&D costs
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Peptide-based PET quantifies target engagement of PD-L1 therapeutics
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BackgroundMouse Tumor Models for Advanced Cancer Immunotherapy
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BackgroundReduction of Neuropathic and Inflammatory Pain through Inhibition of the Tetrahydrobiopterin Pathway
Latrémolière, A., Latini, A., Andrews, N., Cronin, S. J. F., Fujita, M., Gorska, K. I., Hovius, R., Romero, C., Chuaiphichai, S., Painter, M. W., et al. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.033 · Cited by 117 · see citing works
“and Inflammatory Pain through Inhibition of the Tetrahydrobiopterin”
BackgroundHuman-Derived Organ-on-a-Chip for Personalized Drug Development
Jodat, Y. A., Kang, M., Kiaee, K., Kim, G. J., Martinez, A. F. H., Rosenkranz, A., Bae, H., & Shin, S. R. (2019) · Current Pharmaceutical Design · doi:10.2174/1381612825666190308150055 · Cited by 118 · see citing works
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“control)) were assembled as described in Figure 2A, and were tested per experiment: (1) Combination of Liver and GI, (2) Liver alone and (3) GI alone.”
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BackgroundSmall molecule photocatalysis enables drug target identification via energy transfer
Trowbridge, A., Seath, C. P., Rodriguez‐Rivera, F. P., Li, B. X., Dul, B. E., Schwaid, A. G., Buksh, B. F., Geri, J. B., Oakley, J. V., Fadeyi, O., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2208077119 · Cited by 119 · see citing works
“We treated HeLa cells with 5 μM (+)-JQ1-Gen 2 (1) for 3 h before the addition of 250 μM Dz-PEG3-Biotin and subsequent 15-min irradiation (450 nm).”
InfluentialClinical Trials in Alzheimer’s Disease: A Hurdle in the Path of Remedy
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Advancements in 3D Cell Culture Systems for Personalizing Anti-Cancer Therapies
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“Ineffectiveness of therapies is the most common factor (57%) attributed to failure during clinical development (10, 11).”
BackgroundAnticancer drug discovery using multicellular tumor spheroid models
Zanoni, M., Pignatta, S., Arienti, C., Bonafè, M., & Tesei, A. (2019) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2019.1570129 · Cited by 109 · see citing works
Toxicity testing in the 21st century beyond environmental chemicals
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“Recent reports, including one from AstraZeneca, indicate that this trend has not changed over the last decade (Arrowsmith, 2011; Arrowsmith and Miller, 2013; Cook et al., 2014).”
ResultTwo-Dimensional (2D) and Three-Dimensional (3D) Cell Culturing in Drug Discovery
Joseph, J. S., Malindisa, S. T., & Ntwasa, M. M. (2019) · IntechOpen eBooks · doi:10.5772/intechopen.81552 · Cited by 101 · see citing works
“fail at phase II and phase III clinical stages due to poor efficacy and safety issues [2].”
BackgroundComprehensive Survey of Consensus Docking for High-Throughput Virtual Screening
Blanes‐Mira, C., Fernández-Aguado, P., de Andrés-López, J., Fernández-Carvajal, A. M., Ferrer-Montiel, A. V., & Fernandez-Ballester, G. J. (2022) · Molecules · doi:10.3390/molecules28010175 · Cited by 106 · see citing works
“This is mainly due to the high attrition rate in the clinical success of therapeutic agents [2].”
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“concerns on safetywhen the testing is taken fromcell culture to clinical trials.[3,4] Thus, it is understandable and necessary to focus on investigating different research models that can reduce animal testing, and”
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“Drug discovery and development is a lengthy and expensive process due to the high attrition rate in the clinical success of therapeutic agents [1].”
BackgroundMagdy, T., Jouni, M., Kuo, H., Weddle, C. J., Lyra‐Leite, D. M., Fonoudi, H., Romero‐Tejeda, M., Gharib, M., Javed, H., Fajardo, G., et al. (2021) · Circulation · doi:10.1161/circulationaha.121.055801 · Cited by 96 · see citing works
Using PDX for Preclinical Cancer Drug Discovery: The Evolving Field
Williams, J. A. (2018) · Journal of Clinical Medicine · doi:10.3390/jcm7030041 · Cited by 94 · see citing works
Human vascular microphysiological system for in vitro drug screening
Fernandez, C. E., Yen, R. W., Perez, S. M., Bedell, H. W., Povsic, T. J., Reichert, W. M., & Truskey, G. A. (2016) · Scientific Reports · doi:10.1038/srep21579 · Cited by 93 · see citing works
Perspectives for Clinical Translation of Adipose Stromal/Stem Cells
Patrikoski, M., Mannerström, B., & Miettinen, S. (2019) · Stem Cells International · doi:10.1155/2019/5858247 · Cited by 93 · see citing works
“Clinical phase study attrition rates have remained high, the majority of failures being due to lack of efficacy (56%) or due to safety issues (28%) [143].”
BackgroundImplementation of Quantitative and Systems Pharmacology in Large Pharma
Visser, S. A. G., de Alwis, D. P., Kerbusch, T., Stone, J. A., & Allerheiligen, S. R. B. (2014) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1038/psp.2014.40 · Cited by 91 · see citing works
Zietek, T., Giesbertz, P., Ewers, M., Reichart, F., Weinmüller, M., Urbauer, E., Haller, D., Demir, İ. E., Ceyhan, G. O., Kessler, H., et al. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.577656 · Cited by 92 · see citing works
“Species-specific differences and hence poor transferability from animal models to humans is the main reason for this high failure rate (Arrowsmith and Miller, 2013; Cook et al., 2014; Mullard, 2016).”
BackgroundPhenotype-driven precision oncology as a guide for clinical decisions one patient at a time
Chia, S., Low, J.-L., Zhang, X., Kwang, X.-L., Chong, F.-T., Sharma, A., Bertrand, D., Toh, S. Y., Leong, H. S., Thangavelu, M. T., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00451-5 · Cited by 91 · see citing works
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“These have shown relatively limited response rates in unselected patient populations (9), most likely due to activation of alternative compensatory pathways and inter-/intratumoral heterogeneity in expression and mutational status, which may be responsible for intrinsic and acquired resistance-driving mechanisms (10).”
Characterization of Differential Tissue Abundance of Major Non-CYP Enzymes in Human
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Reducing attrition in drug development: smart loading preclinical safety assessment
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Patient-derived xenografts as in vivo models for research in urological malignancies
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The Impact of Chemical Probes in Drug Discovery: A Pharmaceutical Industry Perspective
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Stanimirovic, D. B., Bani‐Yaghoub, M., Perkins, M., & Haqqani, A. S. (2014) · Expert Opinion on Drug Discovery · doi:10.1517/17460441.2015.974545 · Cited by 85 · see citing works
“CNS indications suffer from one of the highest clinical attrition rates in the industry [1].”
BackgroundYamamoto, Y., Välitalo, P. A. J., Wong, Y. C., Huntjens, D. R. H., Proost, J. H., Vermeulen, A., Krauwinkel, W. J. J., Beukers, M. W., Kokki, H. J., Kokki, M., et al. (2017) · European Journal of Pharmaceutical Sciences · doi:10.1016/j.ejps.2017.11.011 · Cited by 81 · see citing works
“Development of drugs for central nervous system (CNS) diseases faces high attrition rates (Arrowsmith and Miller, 2013).”
Background
- Authors
- Arrowsmith, J., & Miller, P.
- Affiliations
- Thomson Reuters (United Kingdom) (GB)
- Corresponding author
- Miller, Philip
- Venue
- Nature Reviews Drug Discovery
- Published
- 2013-08
- Volume
- 12
- Issue
- 8
- Pages
- 569-569
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- OpenAlex
- W1968779484
- Cited by
- 697
- References
- 0
- Citations by year
- 2026: 42 · 2025: 35 · 2024: 45 · 2023: 48 · 2022: 38 · 2021: 55 · 2020: 51 · 2019: 59 · 2018: 57 · 2017: 61 · 2016: 74 · 2015: 63 · 2014: 39 · 2013: 30
- Type
- other
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature Reviews Drug Discovery (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmaceutical industry and healthcare
- Keywords
- attrition rates, drug development, clinical trial failure, drug discovery pipeline
- MeSH terms
- Humans, Treatment Failure, Clinical Trials, Phase II as Topic, Clinical Trials, Phase III as Topic, Early Termination of Clinical Trials
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