The multimodal patient data you're missing

Predict missing biological modalities from the data you already have.

90%

of clinical trials fail

Many fail not because the drug doesn't work, but because the right patients weren't selected. The biomarker that would have changed the outcome was hiding in the modality that was never measured.

Strand fills in these gaps from existing data, predicting the missing modalities so you can find what you're looking for.

See what you've been missing

Multimodal AI needs multimodal data. But acquiring every modality for every patient is expensive, invasive, and often impossible.

Rescue incomplete cohorts

Patients drop out. Assessments get skipped. Predict the missing modalities instead of discarding valuable subjects.

Skip the expensive assay

Predict proteomics or transcriptomics from the H&E slides and genotypes you already have on the shelf.

Unlock rare disease cohorts

Small populations mean sparse coverage. Fill in the modalities your cohort lacks so the models actually train.

Find biomarkers you never assayed

Impute unmeasured markers across your entire cohort. Surface predictive signatures without re-acquisition.

Request Access

Enter your email and we'll be in touch.