Unlock the Full Potential of Your Clinical Trials with Predictive Multimodal Patient Data

Strand AI helps life sciences teams overcome the limitations of incomplete patient data, a major contributor to the 90% failure rate of clinical trials, by predicting missing biological modalities from existing data, enabling more accurate patient selection and biomarker discovery.

Key Features

• Rescue incomplete cohorts by predicting missing modalities, reducing the need for additional invasive and expensive assays

• Generate high-quality multimodal patient data, including gene expression, proteomics, and spatial transcriptomics, from routinely collected samples

• Unlock rare disease cohorts by filling in missing modalities, enabling more effective model training and biomarker discovery

• Impute unmeasured biomarkers across entire cohorts, surfacing predictive signatures without the need for re-acquisition

• Streamline clinical trial workflows by skipping the expensive and time-consuming process of acquiring every modality for every patient

Ideal For

• Life sciences teams running clinical trials and seeking to improve patient selection and biomarker discovery

• Researchers working with rare disease cohorts and requiring more comprehensive and accurate data

• Biopharmaceutical companies aiming to reduce the cost and time associated with clinical trials and improve drug development outcomes