Dana-Farber Cancer Institute

Pan-cancer clinico-genomic model for treatment response and survival prediction, transferring zero-shot to unseen hospitals and cancer types.

Single-cell foundation model that forecasts how cancer cells evolve, autoregressively generating future gene expression from prior cell states.

Contrastive alignment framework that projects H&E histology and single-cell transcriptomic foundation model embeddings into one shared latent space.

Spatial proteomics foundation model, marker-aware and panel-agnostic, pretrained on 47 million multiplexed tissue-imaging patches from 175 markers.

Drug-combination safety prediction that fuses molecular structure, pathway knowledge, cell viability, and transcriptomic response to perturbation.

Slide-level pathology foundation model that encodes a whole-slide image of any size into one embedding, supervised by paired sequencing data.

3D vision foundation model for computed tomography, contrastively pretrained on 148,000 scans for segmentation, triage, retrieval, and concept search.

Self-supervised vision foundation model for structural brain MRI, providing a reusable encoder for brain age, survival, and image classification.

Histopathology patch encoder turning 512x512 tiles into 768-dimensional features, trained with a CoCa objective on 1.26 million captioned images.

Enhancer-promoter interaction prediction from DNA sequence and ATAC-seq alone. Spearman above 0.90 on cell types unseen during training.

Self-supervised 3D CT foundation model that extracts general-purpose tumor representations for cancer imaging biomarker discovery and prognosis.

Blind protein-ligand docking that transfers to binding domains absent from training, scoring 22.6% top-1 on DockGen and 50% on PoseBusters.

Enzyme optimum pH prediction from sequence, ensembling a light-attention network and a support vector regression over frozen ESM-1v embeddings.

Single-cell foundation model pretrained on about 30 million human transcriptomes, using rank-value encoding for context-aware gene network inference.

Spatial proteomics imputation from a 7-plex immunofluorescence panel, generating in silico CODEX expression for 33 more biomarkers per cell.