DP Technology

Molecular reasoning language model for molecule captioning and text-to-molecule generation, trained by chain-of-thought distillation then reward RL.

Organic reaction foundation model that tokenizes 3D molecular structure to predict products, retrosynthetic routes, conditions, and yields.

Proteomics foundation model for peptide-spectrum scoring and open de novo sequencing, reading over 1,300 modifications from tandem mass spectra.

Multimodal drug-response model coupling cell and molecule foundation models, pretrained on 1.8M perturbation RNA-seq profiles over 22,000 compounds.

Protein-ligand binding affinity model that tokenizes quantum electron-cloud density into discrete codes, plus a distilled cloud-free variant.

Autoregressive 3D structure model built on an octree tokenizer, spanning molecule generation, molecular docking, and protein pocket prediction.

Neural ODE model of protein network dynamics, pretrained on 38 million perturbed protein measurements for drug efficacy and synergy prediction.

Binding free energy change prediction for antibody mutations, from a lightweight transformer that scores 10,000 variants in under five minutes.

Multimodal contrastive model aligning protein structure and sequence with ligand conformation and graph to retrieve binders without docking.

RNA foundation model trained on 1 billion sequences, with a 400M-parameter variant for secondary and tertiary structure and functional annotation.