ReviewNature reviews. Drug discovery2011
The productivity crisis in pharmaceutical R&D.
Review in Nature reviews. Drug discovery, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 246 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
246 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- How Much Does It Cost to Research and Develop a New Drug? A Systematic Review and Assessment.PharmacoEconomics · 2021Pooled it
- The proteasome as a druggable target with multiple therapeutic potentialities: Cutting and non-cutting edges.Pharmacology & therapeutics · 2020Pooled it
- A comprehensive map of disease networks and molecular drug discoveries for glaucoma.Scientific reports · 2020Pooled it
- R&D implementation in a department of laboratory medicine and pathology: a systematic review based on pharmaceutical companies.Global journal of health science · 2015Pooled it
- Large scale integration of drug-target information reveals poly-pharmacological drug action mechanisms in tumor cell line growth inhibition assays.Oncotarget · 2014Pooled it
- Intra-Target Microdosing - A Novel Drug Development Approach: Proof of Concept, Safety, and Feasibility Study in Humans.Clinical and translational science · 2017Trial
- TechBio 3.0 closes the drug discovery loop with multimodal AI and generative chemistry.npj drug discovery · 2026Review
- Personalized drug discovery from rare diseases to cancer.npj drug discovery · 2026Review
- Leveraging neural network models for drug repurposing: a case study on cardiac hypertrophy.Scientific reports · 2026Article
- Pharmaceutical Market Analysis of Topical Semi-Solid Dosage Forms for Skin Disorders in Kazakhstan.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Using Deep Learning Models of Gene Regulation to Guide Drug Prioritization.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Using Deep Learning Models of Gene Regulation to Guide Drug Prioritization.bioRxiv : the preprint server for biology · 2026Article
- The statistical software revolution in pharmaceutical development: challenges and opportunities in open source.Drug discovery today · 2026Review
- A case-based explainable graph neural network framework for mechanistic drug repositioning.Bioinformatics (Oxford, England) · 2026Article
- Perspectives on Hybridizing Quantum Mechanics and Artificial Intelligence for Drug Design.Methods in molecular biology (Clifton, N.J.) · 2026Review
- BCheM: a framework integrating molecular attributes and behavioral representations for precise prediction of drug resistance across multiple disease contexts.Frontiers in bioinformatics · 2026Article
- HAFMMDA: HIN2vec-Based Attentional Factorization Machines for Predicting Microbe-Drug Associations.Interdisciplinary sciences, computational life sciences · 2025Article
- The changing landscape of medicinal chemistry optimization.Nature reviews. Drug discovery · 2025Review
- Repurposing Drug Metabolites into Dual β-Adrenergic Receptor-Carbonic Anhydrase Modulators as Potential Tools for Ocular Disorders.Journal of medicinal chemistry · 2025Article
- Computational toxicology in drug discovery: applications of artificial intelligence in ADMET and toxicity prediction.Briefings in bioinformatics · 2025Review
186 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advances in the understanding of the molecular basis of diseases have expanded the number of plausible therapeutic targets for the development of innovative agents in recent decades. However, although investment in pharmaceutical research and development (R&D) has increased substantially in this time, the lack of a corresponding increase in the output in terms of new drugs being approved indicates that therapeutic innovation has become more challenging. Here, using a large database that contains information on R&D projects for more than 28,000 compounds investigated since 1990, we examine the decline of R&D productivity in pharmaceuticals in the past two decades and its determinants. We show that this decline is associated with an increasing concentration of R&D investments in areas in which the risk of failure is high, which correspond to unmet therapeutic needs and unexploited biological mechanisms. We also investigate the potential variations in productivity with regard to the regional location of companies and find that although companies based in the United States and Europe differ in the composition of their R&D portfolios, there is no evidence of any productivity gap.
Indexed as
Identifiers
21629293What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.