ArticlePloS one2013
Tracking 20 years of compound-to-target output from literature and patents.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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
11 citing papers in PubMed.
- PROTAC-PatentDB: A PROTAC Patent Compound Dataset.Scientific data · 2025Article
- PatCID: an open-access dataset of chemical structures in patent documents.Nature communications · 2024Article
- Opening up connectivity between documents, structures and bioactivity.Beilstein journal of organic chemistry · 2020Review
- Development of an Efficient Enzyme Production and Structure-Based Discovery Platform for BACE1 Inhibitors.Biochemistry · 2019Article
- Caveat Usor: Assessing Differences between Major Chemistry Databases.ChemMedChem · 2018Review
- Prioritizing multiple therapeutic targets in parallel using automated DNA-encoded library screening.Nature communications · 2017Article
- SureChEMBL: a large-scale, chemically annotated patent document database.Nucleic acids research · 2016Article
- Managing expectations: assessment of chemistry databases generated by automated extraction of chemical structures from patents.Journal of cheminformatics · 2015Article
- Activity, assay and target data curation and quality in the ChEMBL database.Journal of computer-aided molecular design · 2015Article
- Expanding opportunities for mining bioactive chemistry from patents.Drug discovery today. Technologies · 2015Review
- Allosteric Modulation of G Protein-Coupled Receptors: An Emerging Approach of Drug Discovery.Austin journal of pharmacology and therapeuticsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The statistics of drug development output and declining yield of approved medicines has been the subject of many recent reviews. However, assessing research productivity that feeds development is more difficult. Here we utilise an extensive database of structure-activity relationships extracted from papers and patents. We have used this database to analyse published compounds cumulatively linked to nearly 4000 protein target identifiers from multiple species over the last 20 years. The compound output increases up to 2005 followed by a decline that parallels a fall in pharmaceutical patenting. Counts of protein targets have plateaued but not fallen. We extended these results by exploring compounds and targets for one large pharmaceutical company. In addition, we examined collective time course data for six individual protease targets, including average molecular weight of the compounds. We also tracked the PubMed profile of these targets to detect signals related to changes in compound output. Our results show that research compound output had decreased 35% by 2012. The major causative factor is likely to be a contraction in the global research base due to mergers and acquisitions across the pharmaceutical industry. However, this does not rule out an increasing stringency of compound quality filtration and/or patenting cost control. The number of proteins mapped to compounds on a yearly basis shows less decline, indicating the cumulative published target capacity of global research is being sustained in the region of 300 proteins for large companies. The tracking of six individual targets shows uniquely detailed patterns not discernible from cumulative snapshots. These are interpretable in terms of events related to validation and de-risking of targets that produce detectable follow-on surges in patenting. Further analysis of the type we present here can provide unique insights into the process of drug discovery based on the data it actually generates.
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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.