Cited by 1,763Computational Drug Discovery MethodsAnimal testing and alternativesStatistical Methods in Clinical Trials

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Why 90% of clinical drug development fails and how to improve it?

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Sun, Duxin, Gao, Wei, Hu, Hongxiang, Zhou, Simon·2022·Acta Pharmaceutica Sinica B

DOI 10.1016/j.apsb.2022.02.002PMC PMC9293739

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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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Authors: Sun, D., Gao, W., Hu, H., & Zhou, S.
Affiliations: University of Michigan (US)
Bristol-Myers Squibb (United States) (US)
Corresponding author: Sun, Duxin
ORCID: Sun, Duxin
Gao, Wei
Hu, Hongxiang
Zhou, Simon
Venue: Acta Pharmaceutica Sinica B
Publisher: Elsevier BV
Published: 2022-07
Volume: 12
Issue: 7
Pages: 3049-3062
ISSN: 2211-3835 (ISSN-L)
DOI: 10.1016/j.apsb.2022.02.002
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: cc-by-nc-nd
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
creativecommons.org/licenses/by-nc-nd/4.0/ (vor)
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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