In Vitro Cardiotoxicity Screening Approaches
Cardiotoxicity, or toxicity to the heart, is a major cause of failure of new drugs in mid- to late-stage development. Most cardiotoxicity testing is currently done in animals; these animal-based tests are expensive and time-consuming, and can fail to fully predict effects in humans.
NICEATM is supporting an initiative to design, build, and test new non-animal approaches to assess cardiotoxicity hazard. The goal is to develop human cell- and protein-based assays to more efficiently screen drugs and chemicals for their potential to be toxic to the heart or circulatory system. The initiative is supported jointly by NICEATM and other offices within the NIEHS Division of Translational Toxicology, the FDA Center for Drug Evaluation and Research, and the Health and Environment Sciences Institute (HESI).
Two projects within this initiative focus on non-animal screening approaches for assessing cardiovascular safety.
Leveraging Existing Mechanistic In Vitro Cardiovascular Data
This project focuses on mining public data sources to compile a reference cardiotoxicant tool compound list and identify human-relevant data. Activities include:
- Collate and curate mechanistic in vitro cardiovascular data from public data sources and peer-reviewed literature, including Tox21 data.
- Prioritize Tox21 chemicals based on their activity against cardiotoxicity-related endpoints.
- Annotate performance standards for relevant endpoints.
- Map the available data and testing platforms to cardiovascular failure modes defined by the HESI Cardiac Safety Technical Committee.
- Develop in silico methods to apply quantitative structure activity relationship analyses and in vitro to in vivo extrapolation.
- Propose integrated testing strategies that cover cardiovascular failure modes and provide human-relevant mechanistic information.
Human-relevant data will be used to build and test the capabilities of the developed models and integrated testing strategies. Work completed so far (Krishna et al. 2021) has identified molecular and cellular events potentially contributing to cardiovascular failure modes that may be measurable by assays as part of a translational toxicology pipeline.
As part of this project, a computational approach was developed to predict whether a chemical would affect the human ether-a-go-go-related gene (hERG) potassium channel (Krishna et al. 2022). This function regulates heart rhythm and is often involved in drug-induced cardiotoxicity. Tox21 screening data were used to develop machine learning approaches that use statistical models to predict the probability of a new chemical to cause cardiotoxicity via this mechanism. A poster at the 2023 Annual Meeting of the Society of Toxicology (Krishna et al., Biological Modeling session) described how analyses of in vitro data and geographic estimates of chemical exposure can be used to prioritize potentially cardiotoxic chemicals for further testing.
Pathway-based Modeling of Cardiovascular Hazards
This project is using a whole-genome co-expressed network analysis (WGCNA) approach to characterize chemical effects that are potentially relevant to cardiotoxicity. Activities will include:
- Extract, collate, and curate cardiac-relevant transcriptomics data from DrugMatrix and other sources.
- Apply WGCNA approaches to construct cardiac-relevant modules from both in vivo (rat heart) and in vitro (rat and human cardiomyocyte) model systems.
- Map associations between WGCNA module effects and pathological manifestations observed in the DrugMatrix data.
- Identify modules that exhibit conservation across model systems/species to understand where in vitro systems best model toxicological response.
Findings of this project are guiding the use of cardiac-related in vitro systems for testing and identify areas for further model development. Use of in vitro systems to identify and characterize potential cardiotoxicants was presented in a poster (Ramaiahgari et al., Cardiovascular Toxicology/Hemodynamics session) at the 2023 Society of Toxicology annual meeting.