ReviewActa pharmaceutica Sinica. B2022
Why 90% of clinical drug development fails and how to improve it?
Review in Acta pharmaceutica Sinica. B, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 766 papers, 3 of them syntheses that pooled it.
What it found
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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
766 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- The role of AI-assisted drug repurposing in neurological disorders: a systematic review of validation strategies, challenges and opportunities.Journal of nanobiotechnology · 2026Pooled it
- Socioenvironmental determinants of polypharmacy in mental health disorders: a systematic review.BMC public health · 2026Pooled it
- Pooled it
- Deep Learning Protocols for Predicting Drug Mechanism of Action and Drug-Target Interactions.Methods in molecular biology (Clifton, N.J.) · 2027Article
- Animal organoids as models for integrated One Health research.One health (Amsterdam, Netherlands) · 2026Review
- Drug-likeness prioritised selection identifies anti-Journal of enzyme inhibition and medicinal chemistry · 2026Article
- Intranasal drug delivery to the brain for neurodegenerative diseases: Current efforts and challenges in delivery platforms and modeling.Advanced drug delivery reviews · 2026Review
- Microphysiological models of human gastrointestinal diseases.Nature biomedical engineering · 2026Review
- Article
- ThermoTargetMiner as a proteome integral solubility alteration target database for prospective drugs against lung cancer.Communications chemistry · 2026Article
- Clinical trials in a dish: cardiometabolic drug development with biological and digital twins.The Journal of clinical investigation · 2026Review
- Clinical metastatic cancer from initiation to colonization: emerging challenges and breakthroughs.Oncogene · 2026Review
- Single-allele nanoscale mapping of regulatory variants.Nature genetics · 2026Article
- The longevity dividend: Why governments and markets must catch up.Experimental physiology · 2026Article
- Schiff Base Derivatives of Benzothiazole and Benzamide as Promising Antimicrobial Agents: Integrated In Silico and In Vitro Evaluation.ChemMedChem · 2026Article
- Chemical language models for early-stage drug discovery: applications, pitfalls, and future directions.Journal of computer-aided molecular design · 2026Review
- New 1,3-Oxazole and 1,2,4-Oxadiazole Derivatives as Novel Agents Against Human Rhinovirus and Cytomegalovirus.ChemMedChem · 2026Article
- Establishment of an in vitro human blood-brain barrier model for antiviral screening against neurotropic viruses.Fluids and barriers of the CNS · 2026Article
- GEM-GPT Enables Personalized Cell Type-Resolved Therapeutic Design for Systems Pharmacology.bioRxiv : the preprint server for biology · 2026Article
- Pentacyclic Triterpenoid Acids in the Treatment of Breast Cancer.Molecules (Basel, Switzerland) · 2026Review
706 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ninety percent of clinical drug development fails despite implementation of many successful strategies, which raised the question whether certain aspects in target validation and drug optimization are overlooked? Current drug optimization overly emphasizes potency/specificity using structure‒activity-relationship (SAR) but overlooks tissue exposure/selectivity in disease/normal tissues using structure‒tissue exposure/selectivity-relationship (STR), which may mislead the drug candidate selection and impact the balance of clinical dose/efficacy/toxicity. We propose structure‒tissue exposure/selectivity-activity relationship (STAR) to improve drug optimization, which classifies drug candidates based on drug's potency/selectivity, tissue exposure/selectivity, and required dose for balancing clinical efficacy/toxicity. Class I drugs have high specificity/potency and high tissue exposure/selectivity, which needs low dose to achieve superior clinical efficacy/safety with high success rate. Class II drugs have high specificity/potency and low tissue exposure/selectivity, which requires high dose to achieve clinical efficacy with high toxicity and needs to be cautiously evaluated. Class III drugs have relatively low (adequate) specificity/potency but high tissue exposure/selectivity, which requires low dose to achieve clinical efficacy with manageable toxicity but are often overlooked. Class IV drugs have low specificity/potency and low tissue exposure/selectivity, which achieves inadequate efficacy/safety, and should be terminated early. STAR may improve drug optimization and clinical studies for the success of clinical drug development.
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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.