The DOI matches its Crossref record; 105 of the 106 references it cites were found in a registry or an index.
Why 90% of clinical drug development fails and how to improve it?
Open accessAbstract
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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“Despite these investments, less than 1% of compounds are expected to enter clinical trials, let alone reach the market.13–15”
From Drug repurposing for cancer therapy (2024) · cites this paper as [15]
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“As such, it takes 10–15 years and costs $1–2 billion to produce a new drug approved for clinical use.”
From Drug repurposing for cancer therapy (2024) · cites this paper as [15]
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Computational approaches streamlining drug discovery
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Metadata
- Authors
- Sun, D., Gao, W., Hu, H., & Zhou, S.
- Affiliations
- University of Michigan (US)
- Bristol-Myers Squibb (United States) (US)
- Corresponding author
- Sun, Duxin
- Venue
- Acta Pharmaceutica Sinica B
- Publisher
- Elsevier BV
- Published
- 2022-07
- Volume
- 12
- Issue
- 7
- Pages
- 3049-3062
- ISSN
- 2211-3835 (ISSN-L)
- PMC
- PMC9293739
- OpenAlex
- W4211238337
- Cited by
- 1,763
- References
- 106
- Citations by year
- 2026: 482 · 2025: 550 · 2024: 456 · 2023: 230 · 2022: 45
- FWCI
- 27.77
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Acta Pharmaceutica Sinica B (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- medication optimization, tissue selectivity, structure-activity relationship, target validation
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