Bioptimus

Ingest digitized breast tissue histology slides into the system.

Process the images using the H-Optimus-1 foundation model to extract morphological features.

Integrate the extracted features with the STAMP protocol for recurrence modeling.

Generate a structured risk prediction score to guide personalized treatment decisions.

Upload raw whole-slide images from patient biopsies to the diagnostic pipeline.

Run the images through H-Optimus-1 to identify and classify key cellular anomalies.

Pass the model's visual embeddings into an integrated medical Large Language Model.

Automatically output a draft, structured pathology report for physician review and sign-off.

Prepare and upload spatial transcriptomic datasets alongside corresponding tissue morphology images.

Utilize H-Optimus-1 to establish morphological anchors across the tissue map.

Align spatial gene expression coordinates with the derived morphological boundaries.

Identify specific inflammatory cell phenotypes and mapping markers to accelerate IBD drug target discovery.

Aggregate historical and active multimodal patient data from clinical partners.

Apply Bioptimus' predictive models, tuned for oncology survival metrics.

Cross-reference predictions with cohort variables evaluated in the MIT partnership study.

Output reliable Progression-Free Survival probabilities to support therapeutic intervention strategies.

Define specific clinical contexts and raw performance baselines required by the biopharma partner.

Run proprietary biological datasets through Bioptimus foundation models.

Apply interpretability tools to ensure the model's outputs align with known biological mechanisms.

Generate a comprehensive validation report confirming data integrity and deployment readiness.