Ground Truth Labs AI platform quantifies complex spatial biomarkers from images of routine histopathology slides, guiding drug development, de-risking clinical trials and advancing clinical diagnosis.
Current methods are limited
- Analysis variability: Subjectivity causes inconsistencies across samples and timepoints. The use of categofical grading systems to combat this strip away nuanced details, critical for accurate analysis.
- Slow turnaround times: Traditional methods often require batching and can cause delays, leading to increased study durations and cost overruns.
- Limited tissue samples: The need for larger samples can limit the scope of tests, potentially affecting the depth of the trial's analysis.
AI-powered spatial biomarkers overcome traditional limitations and enhance trial decisions
Objective comparisons between patients, cohorts, and treatments.
Transforming traditional grading with robust, spatial metrics in near real-time.
Measure therapeutic response against a backdrop of morphological disease variation.