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Phase II and Phase III attrition rates 2011–2012
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“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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“We also know that more and more drugs are failing in clinical studies due to poor efficacy (Arrowsmith and Miller, 2013).”
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“and Inflammatory Pain through Inhibition of the Tetrahydrobiopterin”
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BackgroundSmall molecule photocatalysis enables drug target identification via energy transfer
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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
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ResultTwo-Dimensional (2D) and Three-Dimensional (3D) Cell Culturing in Drug Discovery
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“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
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Using PDX for Preclinical Cancer Drug Discovery: The Evolving Field
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Human vascular microphysiological system for in vitro drug screening
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Perspectives for Clinical Translation of Adipose Stromal/Stem Cells
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“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
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
“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
Safety pharmacology investigations on the nervous system: An industry survey
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Cheung, A., Opzoomer, J. W., Ilieva, K. M., Gazińska, P., Hoffmann, R. M., Mirza, H., Marlow, R., Francesch-Domenech, E., Fittall, M. W., Dominguez-Rodriguez, D., et al. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-18-0652 · Cited by 90
“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
Basit, A., Neradugomma, N. K., Wolford, C. C., Fan, P. W., Murray, B. P., Takahashi, R., Khojasteh, S. C., Smith, B. J., Heyward, S. A., Totah, R. A., et al. (2020) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.0c00559 · Cited by 89
Reducing attrition in drug development: smart loading preclinical safety assessment
Roberts, R. A., Kavanagh, S. L., Mellor, H. R., Pollard, C. E., Robinson, S., & Platz, S. J. (2013) · Drug Discovery Today · doi:10.1016/j.drudis.2013.11.014 · Cited by 92
Current Status of Patient-Derived Ovarian Cancer Models
Maru, Y., & Hippo, Y. (2019) · Cells · doi:10.3390/cells8050505 · Cited by 92
Rutkowska, A., Thomson, D. W., Vappiani, J., Werner, T., Mueller, K. M., Dittus, L., Krause, J., Muelbaier, M., Bergamini, G., & Bantscheff, M. (2016) · ACS Chemical Biology · doi:10.1021/acschembio.6b00346 · Cited by 86
Patient-derived xenografts as in vivo models for research in urological malignancies
Inoue, T., Terada, N., Kobayashi, T., & Ogawa, O. (2017) · Nature Reviews Urology · doi:10.1038/nrurol.2017.19 · Cited by 88
The Impact of Chemical Probes in Drug Discovery: A Pharmaceutical Industry Perspective
Garbaccio, R. M., & Parmee, E. R. (2016) · Cell chemical biology · doi:10.1016/j.chembiol.2015.11.011 · Cited by 80
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 86
“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 82
“Development of drugs for central nervous system (CNS) diseases faces high attrition rates (Arrowsmith and Miller, 2013).”
Background
Metadata
- 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
- Health Sciences › Nursing › Issues, ethics and legal aspects › 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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