Why screen drugs in patient-derived organoids?
Organoids are three-dimensional cultures grown from patient tissue that keep many features of the tissue they came from. Tuveson and Clevers (Science, 2019) review how the technology is used to model cancer. In one living biobank from heavily pretreated patients with metastatic gastrointestinal cancers, organoid drug responses matched patient responses with 100% sensitivity and 93% specificity across 21 comparisons (Vlachogiannis et al., Science 2018). That was a small study, so treat the figures as indicative, not general.
How should an organoid screen be designed?
Driehuis, Kretzschmar and Clevers (Nature Protocols, 2020) give a step-by-step protocol for establishing patient-derived cancer organoids and screening them. The main design choices are the same as for any dose-response screen, with a few organoid-specific ones:
- How many independent models (donors): differences between donors are large, so a claim about a tumor type needs several lines, not more wells of one
- Seeding density per well, set from a growth curve for each line
- Concentration range and number of points, bracketing the expected response
- Controls on every plate: vehicle, a cytotoxic positive control and background wells
- Exposure period and readout, for example ATP-based viability or imaging
- The dose-response metric to report, such as IC50 or area under the curve
How many wells will the screen use?
The planner multiplies models x compounds x concentrations x replicates. Control and background wells are not included because they depend on the plate layout; plan those with the Plate Layout Planner, which also handles 384-well plates and empty edge wells.
Frequently asked questions
Are organoid drug responses predictive of patient response?
Some studies report close agreement. Vlachogiannis et al. (2018) found 100% sensitivity and 93% specificity across 21 comparisons in metastatic gastrointestinal cancers. These are small studies, so predictive value should be checked for each indication and assay.
What viability readout is used for organoids?
ATP-based luminescence and imaging are both common. Choose the readout before the screen, because it affects the plate type, the exposure time and how results are normalized.
How many organoid models should a screen include?
Enough independent donors to support the claim you want to make. Responses vary between donors, so conclusions about a tumor type need several models. The planner records your number and counts the wells.
What controls does an organoid screen need?
A vehicle control at the same vehicle concentration as the test wells, a positive control that kills the organoids, and background wells for the readout. Put them on every plate so each plate can be normalized.
Should I use 96-well or 384-well plates?
384-well plates save organoids and compound when screening many conditions; 96-well plates are easier to handle and image. The choice also changes seeding numbers and volumes, so record it as a decision in the plan.
Is anything I type stored or shared?
No. The planner runs entirely in your browser. Nothing you enter is saved, sent to BioBridgeX, put in the page address or passed to analytics or AI services. Closing or refreshing the page clears it, so copy or print the plan before you leave.
Is the generated plan a protocol?
No. It organizes the requirements you entered into a structured outline and lists what is still undecided. It is not a validated protocol, it does not recommend sample sizes, and it does not establish GLP, GMP or regulatory compliance. Have the plan reviewed by qualified scientific, statistical, ethical and regulatory experts.
Related free tools
- In Vitro Assay and Screening Planner: Assay type, cell models, compounds, concentration series, controls, replicates and readout as an organized assay plan.
- PDX Study Planner: Indication, biomarkers, number of models, groups, dosing schedule, tissue collection and analysis in a PDX outline.
- 96 and 384 Well Plate Layout Planner: Lay out compounds, concentrations, replicates and controls on 96- or 384-well plates and count the plates.
- All study planners and every free tool on BioBridgeX.
Sources
- Driehuis E, Kretzschmar K, Clevers H. Establishment of patient-derived cancer organoids for drug-screening applications. Nature Protocols 2020;15(10):3380-3409
- Tuveson D, Clevers H. Cancer modeling meets human organoid technology. Science 2019;364(6444):952-955
- Vlachogiannis G et al. Patient-derived organoids model treatment response of metastatic gastrointestinal cancers. Science 2018;359(6378):920-926
- Sebaugh JL. Guidelines for accurate EC50/IC50 estimation. Pharmaceutical Statistics 2011;10(2):128-134
This planner organizes requirements. It is not a validated protocol, does not recommend sample sizes, and does not establish GLP, GMP or regulatory compliance. Review every plan with qualified scientific, statistical, ethical and regulatory experts. Facts on this page last checked 27 October 2026.
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