AI-Enabled Animal Behavior Analysis for Translational Pharmacology and Therapeutic Discovery

Animal behavior is a critical endpoint in preclinical pharmacology, toxicology, and therapeutic discovery, yet conventional behavioral scoring remains labor-intensive, low-dimensional, and difficult to reproduce across laboratories. Artificial intelligence (AI) can now quantify behavior from video with greater spatial, temporal, and phenotypic resolution. This review summarizes how object detection, markerless pose estimation, unsupervised behavioral segmentation, foundation models, and autonomous analysis agents are reshaping behavioral phenotyping. General-purpose object detectors rapidly localize and track animals, whereas open-source pose-estimation tools extend measurement beyond centroid tracking to body-part trajectories and fine motor patterns; paired with supervised classifiers, they have matched human scoring and exceeded some commercial systems. Technical accuracy alone does not establish behavioral construct validity or pharmacological validity. Unsupervised methods such as Motion Sequencing represent drug responses and disease-model phenotypes as structured changes in behavioral states rather than only as predefined endpoints, providing high-dimensional fingerprints of pharmacological action. Segmentation and tracking foundation models may reduce annotation burden but require validation across species, strain, sex, apparatus, and paradigm. AI agents may assist with literature review, code generation, analysis auditing, and figure production but must remain within transparent, human-supervised workflows. In behavioral pharmacology, pose estimation is established as a measurement method and emerging as a drug-effect endpoint, supervised classification and unsupervised segmentation are emerging, and foundation models and agents remain prospective. AI-enabled behavioral analysis can become a reproducible phenotyping layer for drug discovery and toxicology if researchers adopt open pipelines, rigorous validation, and reporting standards, rather than replacing one opaque measurement system with another.