Automating Predictive Toxicology Using ComptoxAI

Abstract

ComptoxAI is a new data infrastructure for computational and artificial intelligence research in predictive toxicology. Here, we describe and showcase ComptoxAI’s graph-structured knowledge base in the context of three real-world use-cases, demonstrating that it can rapidly answer complex questions about toxicology that are infeasible using previous technologies and data resources. These use-cases each demonstrate a tool for information retrieval from the knowledge base being used to solve a specific task: The “shortest path” module is used to identify mechanistic links between perfluorooctanoic acid (PFOA) exposure and nonalcoholic fatty liver disease; the “expand network” module identifies communities that are linked to dioxin toxicity; and the quantitative structure–activity relationship (QSAR) dataset generator predicts pregnane X receptor agonism in a set of 4,021 pesticide ingredients. The contents of ComptoxAI’s source data are rigorously aggregated from a diverse array of public third-party databases, and ComptoxAI is designed as a free, public, and open-source toolkit to enable diverse classes of users including biomedical researchers, public health and regulatory officials, and the general public to predict toxicology of unknowns and modes of action.

Knowledge graph aids comprehensive explanation of drug and chemical toxicity

“…ComptoxAI 19 , 20 is a comprehensive graph knowledge base that contains curated relationships among chemicals, genes, assays, and many other entities. It contains two types of relationships linking compound and gene nodes: physical binding (with protein product) and expression‐alteration (upregulation/downregulation).…”

“…ComptoxAI 19,20 is a comprehensive graph knowledge base that contains curated relationships among chemicals,…”

“…Although these models ensure the wide applicability of DTox, they are vulnerable to prediction errors and data scarcity, causing exclusion of certain genes from the feature space. To address this limitation, we used curated knowledge from the toxicology‐focused graph knowledge base ComptoxAI 19 to refine the input feature profile of DTox. ComptoxAI provides extensive profiling of chemical‐gene connections across multiple gene categories, which can be used for feature profile construction.…”

Knowledge Graph Aids Comprehensive Explanation of Drug Toxicity

“…ComptoxAI 19, 20 is a comprehensive graph knowledge base that contains curated relationships between chemicals, genes, assays, and many other entities. It contains two types of relationships linking compound and gene nodes: physical binding (with protein product) and expression-alteration (up-regulation/down-regulation).…”

“…While these models ensure the wide applicability of DTox, they are vulnerable to prediction errors and data scarcity, causing exclusion of certain genes from the feature space. To address this limitation, we used curated knowledge from the toxicology-focused graph knowledge base ComptoxAI 19 to refine the input feature profile of DTox. ComptoxAI provides extensive profiling of chemical-gene connections across multiple gene categories, which can be used for feature profile construction.…”