Biological Foundation Models for Complex Disease Research and Clinical Translation
TL;DR
Biological foundation models are new artificial intelligence tools that can learn useful patterns from large biological datasets and apply them to different research questions to help researchers understand disease mechanisms, identify important genetic changes, predict drug responses, and discover treatment targets.
Abstract
Simple Summary Complex diseases are difficult to study because they involve many interacting genetic and cellular factors. Biological foundation models are new artificial intelligence tools that can learn useful patterns from large biological datasets and apply them to different research questions. This review introduces the major types of these models and explains how they are designed, trained and adapted for biomedical applications. We explain how they may help researchers understand disease mechanisms, identify important genetic changes, predict drug responses, and discover treatment targets. We also discuss current limitations, especially the need for better validation, clearer interpretation, improved data integration, and stronger protection of patient privacy before these models can be widely used in clinical practice.
