The productivity crisis in pharmaceutical R&D

By Fabio Pammolli, Laura Magazzini, Massimo Riccaboni. Nature reviews. Drug discovery, 2011

913 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management of Technology and Innovation, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/973e82d271df525f0a829359e804f96ac981cf5c

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Albert-László Barabási

Citations in the corpus

Artificial intelligence and innovation management: A review, framework, and research agenda✰ (2021, background): “Drug development processes in the pharmaceutical industry show similar trends (Munos, 2009; Pammolli et al., 2011).”
Inverted-U relationship between R&D intensity and survival : evidence on scale and complementarity effects in UK data. (2016, neutral): “a Pavitt technology classes are from Pavitt (1984), as revised slightly by Bogliacino and Pianta (2010).”
Ligand–receptor interaction platforms and their applications for drug discovery (2012, background): “4 Drug residence time Poor in vivo efficacy has been found to be a primary source of high drug attrition rates, largely due to poor predicative power of in vitro results [6,17].”
ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support (2024, neutral): “The preclinical stage lays the crucial groundwork and, as a demanding phase in drug development, confronts a considerable attrition rate of approximately 93% ( 1 ).”
Systems biology approaches for advancing the discovery of effective drug combinations (2015, background): “Despite increasing investments in pharmaceutical research and development, the rate of introduction of successfully translated drugs has decreased [1].”
Meta-QSAR: a large-scale application of meta-learning to drug design and discovery (2017, background): “More generally, the pharmaceutical industry is struggling to copewith spiralling drug discovery and development costs (Pammolli et al. 2011).”
The Potential for microRNA Therapeutics and Clinical Research (2019, background): “In fluid specimens such as blood, the miRNA content can originate through a few pathways, including extracellular vesicles (exosomes) (Kanlikilicer et al., 2016; Bayraktar et al., 2017; Rashed et al., 2017; Paskeviciute and Petrikaite, 2019).”
Network-based approach to prediction and population-based validation of in silico drug repurposing (2018, background): “One of the primary reasons for this shortcoming in contemporary drug development may be the high failure rate of randomized controlled trials that are expensive and time-consuming (2-5).”
R&D and productivity in OECD firms and industries: A hierarchical meta-regression analysis ☆ (2016, neutral): “The latter is in line with case-study findings (Pammolli et al., 2011) and review evidence (DiMasi and Grabowski, 2012) on the pharmaceutical industry.”
The Emerging Paradigm of Network Medicine in the Study of Human Disease (2012, background): “67 Reasons for such declining productivity include a more intense regulatory environment, the exhaustion of “easy” or more obvious targets, an increasing attrition rate for developing drugs secondary to their unanticipated side effects, and, from the perspective of this review, an intrinsically…”