Trial Watch: Phase II and Phase III attrition rates 2011–2012

By J. Arrowsmith, Philip J Miller. Nature reviews. Drug discovery, 2013

619 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9ab0f468a64762ca5069335c776e1ab07fa2b3e2

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Citations in the corpus

Network-based in silico drug efficacy screening (2016, neutral): “Yet , given that the lack of efﬁcacy is the leading reason for failure in drug development 26 , we suspect that the drugs we fail to identify in the proximity of .”
Lost in translation: the valley of death across preclinical and clinical divide – identification of problems and overcoming obstacles (2019, background): “The majority of projects fail for problems unrelated to a therapeutic hypothesis which may be due to unexpected side effects and tolerability [29, 30].”
Biology-inspired Microphysiological System Approaches to Solve the Prediction Dilemma of Substance Testing (2016, neutral): “Despite continuous improvements, there are failures in drug programs, both in preclinical and in clinical stages (e.g., Arrowsmith and Miller, 2013).”
Toxicity Testing in the 21st Century Beyond Environmental Chemicals (2015, result): “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).”
Three-Dimensional in Vitro Cell Culture Models in Drug Discovery and Drug Repositioning (2018, background): “Currently, more than half of all drugs fail in Phase II and Phase III clinical trials due to a lack of efficacy and about another third of drugs fail due to safety issues including an insufficient therapeutic index (Arrowsmith and Miller, 2013).”
Open Targets: a platform for therapeutic target identification and validation (2016, background): “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).”
ADReCS: an ontology database for aiding standardization and hierarchical classification of adverse drug reaction terms (2014, neutral): “Furthermore, SADRs were responsible for ∼28% of new drug development failures in clinical trials (4) and led to the eventual withdrawal of drugs (5,6).”
Personalized In Vitro and In Vivo Cancer Models to Guide Precision Medicine (2017, background): “However, an understanding of the functionality of these alterations and the influence they have on treatment response remains limited due to a paucity of personalized preclinical models (14, 15).”
The druggable genome and support for target identification and validation in drug development (2016, background): “Since the target hypothesis advanced by preclinical and early phase clinical studies is all too frequently false, expensive late-stage failure in RCTs from lack of efficacy is a common problem affecting many therapeutic areas (10), posing a threat to the economic sustainability of the current model ”
Lessons learned from the fate of AstraZeneca's drug pipeline: a five-dimensional framework (2014, background): “20 (9) Indication selected does not fit strongest preclinical evidence”
Nanoparticle-based drug delivery systems: a commercial and regulatory outlook as the field matures (2017, background): “In general, safety failure is the predominant reason of study termination at this stage [62,63].”