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De-risking seizure liability: integrating adverse outcome pathways (AOPs), new approach methodologies (NAMs), and in
Mamta Behl1, Agnes Karmaus2, Mohan Rao1
1Neurocrine Biosciences Inc., San Diego, CA 92130, United States.
Abstract:
Animal studies are commonly used in drug development and in chemical and environmental toxicology to predict human toxicity, but their reliability, particularly in the central nervous system (CNS), is limited. For example, animal models often fail to predict drug-induced seizures, leading to unforeseen convulsions in clinical trials. Evaluating environmental compounds, such as pesticides, also poses challenges due to time and resource constraints, resulting in compounds remaining untested. To address these limitations, a government-industry collaboration identified 27 biological target families linked to seizure mechanisms by combining key events from adverse outcome pathways (AOPs) with drug discovery data. Over a hundred in vitro assay endpoints were identified, covering 26 of the target families, including neurotransmitter receptors, transporters, and voltage-gated calcium channels. A review of reference compounds identified 196 seizure-inducing and 34 seizure-negative chemicals, with 80% being tested in the in vitro assays. However, some target familes were more data-poor than others, highlighting significant data gaps. This proof-of-concept study demonstrates how mechanistic seizure liability can be assessed using an AOP framework and in vitro data. It underscores the need for expanded screening panels to include additional seizure-relevant targets. By integrating mechanistic insights into early drug development and environmental risk assessment, this approach enhances compound prioritization, complements animal studies, and optimizes resource use. Ultimately, this strategy refines CNS safety evaluation in drug development, improves public health protection to neurotoxicants, and bridges knowledge gaps.
Insights
This study introduces a new method using adverse outcome pathways (AOPs) and in vitro data to predict chemical-induced seizures, improving drug development and environmental safety assessments.
Area of Science:
- Neurotoxicology
- Drug Development
- Environmental Risk Assessment
Background:
- Animal models for predicting human toxicity, especially for central nervous system (CNS) effects like seizures, have limited reliability.
- Existing methods face challenges in evaluating environmental compounds due to time and resource constraints, leading to untested chemicals.
- Drug-induced seizures are a significant concern in clinical trials, highlighting the need for better predictive models.
Purpose of the Study:
- To develop and demonstrate a novel approach for assessing seizure liability using an adverse outcome pathway (AOP) framework and in vitro data.
- To identify biological targets and in vitro assay endpoints relevant to seizure mechanisms.
- To highlight data gaps in current compound screening for seizure-related neurotoxicity.
Main Methods:
- A government-industry collaboration combined AOPs and drug discovery data to identify 25 biological target families linked to seizure mechanisms.
- Over 100 in vitro assay endpoints were identified, covering 24 target families, including key receptors, transporters, and ion channels.
- A review of 196 seizure-inducing and 34 seizure-negative reference compounds was conducted to assess existing data coverage.
Main Results:
- The study identified key biological targets and over 100 relevant in vitro assay endpoints for seizure mechanisms.
- Analysis revealed significant data gaps, with fewer than 30% of identified targets tested for known seizure-inducing or non-inducing compounds.
- This proof-of-concept demonstrated the feasibility of assessing mechanistic seizure liability using AOPs and in vitro data.
Conclusions:
- The AOP framework combined with in vitro data provides a robust method for assessing mechanistic seizure liability.
- Expanded screening panels incorporating additional seizure-relevant targets are necessary.
- This integrated approach enhances compound prioritization, optimizes resource use, refines CNS safety evaluation, and improves public health protection.
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