ON-DEMAND WEBINAR
From clone to screen: an integrated patient-derived organoid workflow
Patient-derived organoids (PDOs) offer researchers a highly relevant, patient-reflective disease-model system, as organoids often mirror the drug-response profiles of the individuals from whom they were derived. Although PDOs provide rich phenotypic and functional insights, screening large compound sets remains labor-intensive and requires significant hands-on time. This webcast will demonstrate a practical, end-to-end workflow that simplifies and scales PDO culture and screening, enabling teams to increase reproducibility, throughput and confidence in their data.
Beginning with the use of ClonePix to generate stable, high-WNT–producing cell lines for consistent production of conditioned media to support robust PDO growth, colorectal cancer PDOs (CRC) PDOs are then expanded using the CellXpress.ai Automated Cell-Culture System, which integrates AI-driven imaging, monitoring and automated passaging. This automated process has been validated across multiple CRC organoid lines in multisite studies, confirming its reliability and transferability.
From there, the workflow transitions into streamlined drug-response assessment, beginning with automated, plate reader–based viability assays that efficiently identify compounds with measurable effects. Selected hits can then be advanced into high-content imaging studies, employing a variety of fluorescent labels and analytical techniques to extract deeper phenotypic insights — culminating in a fully integrated pipeline from clone generation to decision-ready data.
Learn:
- How to develop stable, high-performance cell lines to support consistent, scalable PDO workflows
- How to reliably scale and automate CRC PDO culture using AI-driven monitoring and automated passaging
- How to streamline quantitative screening workflows to deliver reproducible, decision-ready data across sites
Thank you for your interest.
We’re excited to share with you our latest learnings – from new product innovations to improved methods for automating complex biology workflows – our experts look forward to connecting with you and exploring ways to advance scientific research, together.