DrugVision.AI
Assay Capabilities
In-house developed analysis pipelines and metrics powering actionable insights.
Normalised Organoid Growth Rate (NOGR)
NOGR is our in-house developed growth rate–based metric designed to improve the accuracy of longitudinal organoid drug response profiling. With intra-well normalization, automated QC, and correction for baseline growth differences across organoid lines, it robustly distinguishes cytostatic from cytotoxic effects across organoid models. By extracting growth directly from brightfield images through Orbits, our proprietary label-free viability and cell death segmentation model, NOGR avoids the confounding effects of fluorescent viability dyes.
Deben C, et al. Commun. Biol., 2024
Standard relative viability metrics also available
Response Dynamics
Monitor drug effects over time, not just at a single endpoint. Capture onset, kinetics, and recovery of drug effects with growth-rate dynamics tracked across multiple timepoints.
Example: KRAS G12D mutant pancreatic cancer organoids treated with MRTX1133
Drug Synergy Studies & Selectivity
Our platform identifies synergistic and tumor-selective drug combinations with the added power to separate cytotoxic synergy from cytostatic or merely additive effects. Using HSA, ZIP, Loewe, and Bliss models together with NOGR heatmaps, we generate a more precise and biologically relevant assessment of drug combination activity.
Deben C, et al. J Exp Clin Cancer Res., 2024
High-Throughput Insights for Generative Drug Design, QSAR Profiling & Benchmarking
Strengthen every stage of your drug development process with patient-relevant efficacy data generated in tumor organoid models. From early hit identification and hit-to-lead optimization to candidate selection and translational positioning, our platform supports de novo drug design, QSAR profiling and enables benchmarking against established anticancer agents. This provides a more informed framework to guide compound design, compare performance, and de-risk development decisions.
Service available through a strategic platform partnership with Sightera Biosciences, a spin-off originating from the DrugVision.AI platform.
Prioritize Biomarker Candidates
Our platform integrates phenotypic response data with baseline molecular profiling to help prioritize biomarker candidates linked to therapy response. By revealing features associated with sensitivity, resistance, and tumor selectivity, we support smarter biomarker strategies for early patient stratification and precision medicine.
Deben C, et al. J Exp Clin Cancer Res., 2024
Organoid Biobank
Patient-relevant models for improved translational insights.
Healthy and Tumor Organoid Biobank
We maintain a continuously expanding biobank of patient-derived solid tumor organoids, including pancreatic, colorectal, and esophageal cancer models, together with healthy organoids to evaluate tumor selectivity. Our platform also includes organoids cultured in both traditional Wnt-based media and Thermo Fisher Scientific OncoPro medium, which we recently showed can yield important differences in drug response for certain therapeutic classes with a potential increased clinical relevance.