Human biology-based drug safety evaluation: scientific rationale, current status and future challenges
Abstract
INTRODUCTION: Animal toxicity studies used to assess the safety of new candidate pharmaceuticals prior to their progression into human clinical trials are unable to assess the risk of non-pharmacologically mediated idiosyncratic adverse drug reactions (ADRs), the most frequent of which are drug-induced liver injury and cardiotoxicity. Idiosyncratic ADRs occur only infrequently and in certain susceptible humans, but are caused by many hundreds of different drugs and may lead to serious illness. Areas covered: Idiosyncratic ADRs are initiated by drug-related chemical insults, which cause toxicity due to susceptibility factors that manifest only in certain patients. The chemical insults can be detected using in vitro assays. These enable useful discrimination between drugs that cause high versus low levels of idiosyncratic ADR concern. Especially promising assays, which have been described recently in peer-reviewed scientific literature, are highlighted. Expert opinion: Effective interpretation of in vitro toxicity data requires integration of endpoints from multiple assays, which each address different mechanisms, and must also take account of human systemic and tissue drug exposure in vivo. Widespread acceptance and use of such assays has been hampered by the lack of correlation between idiosyncratic human ADR risk and toxicities observed in vivo in animals.
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In vitro pharmacological profiling methods have not been able to predict clinical failures due to idiosyncratic toxicity.
“These methods have also not been able to predict clinical failures due to idiosyncratic toxicity and this may be due to the lack of in vitro-in vivo correlation5 while efficacy is as complex to predict6.”
From Exploiting machine learning for end-to-end drug discovery and development (2019) · cites this paper as [5]
The inability of in vitro pharmacological profiling to predict clinical failures due to idiosyncratic toxicity may be due to the lack of in vitro-in vivo correlation.
“this may be due to the lack of in vitro-in vivo correlation5”
From Exploiting machine learning for end-to-end drug discovery and development (2019) · cites this paper as [5]
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- Authors
- Kenna, J. G.
- Affiliations
- Safer Medicines Trust (GB)
- Corresponding author
- Kenna, J. Gerry
- ORCID
- Kenna, J. Gerry
- Venue
- Expert Opinion on Drug Metabolism & Toxicology
- Publisher
- Informa UK Limited
- Published
- 2017-02-14
- Volume
- 13
- Issue
- 5
- Pages
- 567-574
- ISSN
- 1742-5255 (ISSN-L)
- 1744-7607
- OpenAlex
- W2584499400
- Cited by
- 7
- References
- 68
- Citations by year
- 2025: 1 · 2022: 2 · 2019: 2 · 2018: 2
- FWCI
- 0.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Expert Opinion on Drug Metabolism & Toxicology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Drug-Induced Hepatotoxicity and Protection
- Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
- Health Sciences › Medicine › Pharmacology › Drug-Induced Adverse Reactions
- Keywords
- idiosyncratic drug reactions, drug safety assessment, drug-induced liver injury, cardiotoxicity, in vitro toxicity testing, in vitro-in vivo correlation, animal toxicity studies
- MeSH terms
- Animals, Humans, Species Specificity, Drug Design, Toxicity Tests, Endpoint Determination, Chemical and Drug Induced Liver Injury, Drug-Related Side Effects and Adverse Reactions, Cardiotoxicity
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