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The role of genetic toxicology in drug discovery and optimization
1Department of Genetic Toxicology, Bristol-Myers Squibb, Syracuse NY, 6000 Thompson Rd., Syracuse, NY 13057, USA. laura.custer@bms.com
Abstract:
Genetic toxicology data is used as a surrogate for long-term carcinogenicity data during early drug development. The aim of genotoxicity testing is to identify potentially hazardous drug candidates. Results from genetic toxicology tests in combination with acute and subchronic animal data are used as the basis to approve clinical trials of drug candidates. With few exceptions, mutagenic compounds are dropped from development and clastogenic compounds result in unfavorable labeling, require disclosure in clinical trial consent forms, and can impact the marketability of a new drug. Therefore, genetic toxicology testing in drug discovery and optimization serves to quickly identify mutagens and remove them from development. Additionally, clastogenicity can delay drug development by requiring additional testing to determine in vivo relevance of in vitro clastogenic responses. Clastogenicity screening is conducted so any additional testing can be planned and perhaps integrated into other toxicity studies to expedite progression of drugs into the clinic. Commercially available genotoxicity and carcinogenicity predictive software systems used for decision support by ICSAS, FDA/CDER is described along with the strengths and weakness of each system. The FDA has concentrated on using a consensus approach to maximize certainty for positive predictions at the expense of sensitivity. The consensus approach consists of requiring 2 complementary software packages, such as MC4PC and MDL QSAR models, to agree that a compound has a genotoxic or carcinogenic liability. Mutagenicity and clastogenicity screening tests are described along with advantages and disadvantages of each test. Several testing strategies are presented for consideration.
Insights
Genetic toxicology testing identifies hazardous drug candidates early in development. This screening prevents the progression of mutagens and manages clastogens, ensuring safer drug development and clinical trials.
Area of Science:
- Pharmacology and Toxicology
- Drug Discovery and Development
- Regulatory Science
Background:
- Genetic toxicology data serves as a surrogate for long-term carcinogenicity during early drug development.
- Identifying potentially hazardous drug candidates early is crucial for efficient drug development.
- Genotoxicity results, combined with animal data, inform decisions on advancing drug candidates to clinical trials.
Purpose of the Study:
- To outline the critical role of genetic toxicology in identifying and mitigating risks associated with drug candidates.
- To discuss the impact of mutagenic and clastogenic compounds on drug development timelines and marketability.
- To review available genotoxicity and carcinogenicity predictive software systems and their application in regulatory decision-making.
Main Methods:
- Description of mutagenicity and clastogenicity screening tests, including their advantages and disadvantages.
- Evaluation of commercially available genotoxicity and carcinogenicity predictive software systems.
- Explanation of the FDA's consensus approach using complementary software packages (e.g., MC4PC, MDL QSAR) for predicting genotoxic or carcinogenic liability.
Main Results:
- Mutagenic compounds are typically discontinued from development.
- Clastogenic compounds can lead to unfavorable labeling and impact marketability, often requiring further in vivo relevance studies.
- The FDA's consensus approach prioritizes certainty in positive predictions, potentially at the cost of sensitivity.
Conclusions:
- Genetic toxicology screening is essential for the rapid identification and removal of mutagens in drug discovery.
- Proactive clastogenicity screening allows for better planning of additional toxicity studies, potentially expediting drug progression.
- Strategic implementation of genetic toxicology testing and predictive software supports informed decision-making in drug development and regulatory submissions.
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