CoTox: Chain-of-Thought-Based Molecular Toxicity Reasoning and Prediction

Summary

This paper talks about CoTox, a new system that combines large language models with a way of thinking called chain-of-thought reasoning to better predict how toxic different molecules might be. It uses information about chemical structures, biological processes, and genes to make its predictions clearer and more accurate.

What's the problem?

The problem is that predicting the toxicity of molecules, which is important in developing safe drugs, is very complicated. Traditional methods often struggle to explain their results or miss important biological details, which makes it hard to trust them when designing new medicines.

What's the solution?

The solution was to build CoTox, which helps the AI model break down its reasoning step-by-step using chain-of-thought techniques while including extra knowledge about how chemicals affect biological pathways and genes. This makes the predictions more understandable and improves the accuracy of identifying toxic effects of molecules.

Why it matters?

This matters because better toxicity prediction helps scientists create safer drugs faster by knowing which molecules might be harmful early in the development process. CoTox improves trust in AI predictions and supports advances in medicine by combining detailed reasoning with important scientific information.