Image-Based Digital Biomarkers Detected by AI Platform to Transform Drug Development and Clinical Care with Susan Wood VIDA TRANSCRIPT
Download PDFAug 6, 2026
Susan Wood, CEO of VIDA, develops AI-driven imaging-based biomarkers that quantitatively measure biological processes and disease states using imaging modalities such as CT, MRI, PET, and ultrasound. Unlike traditional visual image analysis, VIDA's technology extracts approximately 25,000 measurements per imaging timepoint, enabling detection of therapeutic responses at the sub-millimeter level. This convergence of advanced scanner technology, high-quality imaging data, and AI-powered analysis represents a significant new frontier in precision medicine and drug development.
Susan explains, "I'll start with what VIDA brings in. Our background has been the development and validation of AI-driven imaging-based biomarkers. I'll start by defining a biomarker, specifically an imaging-based biomarker. It's a quantitative measurement derived from an imaging modality. An imaging modality can be a CT scan, an MRI, a PET scan, or an ultrasound, and the measurement reflects a biological process, a disease state, or a response to therapy. VIDA's formation was focused on the production and validation of those imaging-based biomarkers and on incorporating them into provider-based clinical workflows as well as clinical trial or drug development workflows."
"I would say that in general, traditionally radiology has relied on radiologic images, those imaging modalities have been read visually. And if you read an image visually, there's just a fraction of information that you can get from those images versus reading them with these AI-generated processes. So there's less than 1% of that image you'll be able to understand the extent and the complexity of the measurements that image can offer. We read, or we combine that visual reading with a highly quantitative process. So for each imaging time point, we'll measure 25,000 measurements per imaging time point. Obviously that's well beyond what a human eye could do just from an efficiency standpoint, but certainly from a precision standpoint, they wouldn't be able to measure that level of precision in the imaging by an eyeball alone."
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