How to improve R&D productivity: the pharmaceutical industry's grand challenge

By S. Paul, D. Mytelka, C. Dunwiddie, Charles C. Persinger, B. Munos, S. Lindborg, A. Schacht. 2010

3,532 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Public Health, Environmental and Occupational Health

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Public Health, Environmental and Occupational Health

Citations in the corpus

SWEETLEAD: an In Silico Database of Approved Drugs, Regulated Chemicals, and Herbal Isolates for Computer-Aided Drug Discovery (2013, background): “approved new chemical entity (NCE) continue to soar[1-3],”
A survey of current trends in computational drug repositioning (2016, background): “mains the most important priority for pharmaceutical industry [3].”
Multisensor-integrated organs-on-chips platform for automated and continual in situ monitoring of organoid behaviors (2017, background): “D discovery is a lengthy process associated with tremendous cost and high failure rate (1).”
Rethinking drug design in the artificial intelligence era (2019, background): “Given the complexity of human disease and the challenges that medicinal chemists and drug designers need to overcome, a more thorough approach for hypothesis generation in drug design may be beneficial 67,68 .”
The productivity crisis in pharmaceutical R&D (2011, background): “In recent years, the R&D productivity challenge has become particularly difficult to overcome in the pharmaceutical secto”
The influence of lipophilicity in drug discovery and design (2012, background): “Further, roughly 10% of those compounds that are selected for further clinical study make it to the marketplace as effective drugs, demonstrating that the overall drug development process is far from ideal [2].”
Biology-inspired Microphysiological System Approaches to Solve the Prediction Dilemma of Substance Testing (2016, positive): “discovery and lead optimization (Paul et al., 2010), performing larger numbers of in vitro assays per lead identification and a significant number of laboratory animal tests per target or lead.”
Can we really do computer-aided drug design? (2011, background): “Even after selection of a candidate compound, the chance of this compound reaching the market is less than 10% [3].”
Structure-based drug screening for G-protein-coupled receptors. (2012, background): “For this and other reasons, the cost of drug development has escalated while revenue from new drugs has slipped [9].”