Papers for

biopharmaceutical safety teams

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Toxicology vision models improve pathology across animals and organs

Scaling Vision Foundation Models for Toxicologic Pathology

Abstract: Here, we present TOX-FM, a family of non-clinical PFMs trained on large-scale diverse histopathology datasets of over one million whole slide images consisting of over 60 organs across six animal species from over 14,000 toxicology studies across six decades. We introduce a comprehensive benchmark of 18 non-clinical downstream tasks, incorporate an established benchmark of 9 clinical downstream tasks, and evaluate TOX-FM against state-of-the-art clinical PFMs across both non-clinical and clinical domains. Notably, we explore open questions surrounding domain-specific training and cross-domain generalization, offering insights into the opportunities and challenges of applying PFMs in the non-clinical domain.

Mon 19 OctComputer Vision and Pattern Recognition

The gist

Toxicologic pathology involves studying tissue samples from animals to detect harmful effects of chemicals or drugs. The authors developed TOX-FM, a large family of computer models trained using over a million images from diverse animal tissues collected over decades. These models can perform many different pathology tasks better than existing clinical models, including ones they were not specifically trained for. The authors also studied how training on specialized non-clinical data affects model performance on clinical tasks and vice versa.

Open → 2610.26586v1