M-Optimus-1
Multimodal foundation model for oncology. M-Optimus-1 turns a routine H&E slide into ~6,000-gene spatial expression readouts. Pre-trained on millions of proprietary H&E whole-slide images (50+ tissues) plus paired patient cohorts with aligned H&E, bulk RNA-seq, and spatial transcriptomics.
- Category
- Healthcare & Life Sciences
- Registry category
- Software Development
- Vendor
- Bioptimus
- Location
- Not disclosed
- Reviews
- Not rated (0 reviews on the listing)
- Listed on
- AWS Marketplace
- Pricing
- 3 plans listed
Each fact carries one Provenance score: the average of its Disclosure and Evidence scores, the same rule the page uses for the overall score. Click any score to see the math behind it.
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What the publisher says
Use M-Optimus-1 to build oncology models from H&E whole-slide images, optionally paired with bulk RNA-seq. Generate multimodal embeddings and reconstruct spatial gene expression across a curated panel of 6,000+ genes.
M-Optimus-1 is a multimodal foundation model for oncology, learning cross-modal representations across H&E, bulk RNA-seq, and spatial transcriptomics. Pre-trained using a unique proprietary dataset comprising millions of H&E whole slide images from more than 50 organ tissues, and thousands of patient records where H&E, bulk and spatial transcriptomics are paired and aligned.
Deploy M-Optimus-1 as an Amazon SageMaker model package inside your AWS account. Run real-time inference via SageMaker endpoints or batch inference on S3. Your data stays private, and is never accessed by Bioptimus.
Plans and pricing
3 plans listed
Linked repositories
Unknown
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Publisher resources
Sources
- Marketplace listingAWS Marketplace (opens in a new tab)
- Legal linkCustomEula (opens in a new tab)
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