Target discovery services · Functional genomics

Target discovery with PDO 1.0 & PDO 2.0

Discover and validate targets through organoid genetic-library screening, functional assays and treatment-response studies.

Discuss a target-discovery project Explore R&D collaboration ↓

Library screeningGenes, pathways & controls
Hit confirmationIndependent perturbation & molecular checks
Functional validationGrowth, structure & immune function
Target prioritizationResponse, mechanism & R&D decision

From library screening to target prioritizationView full diagram ↗

R&D decisions

Answer the target questions that move your program forward

Candidate target validation

Does perturbing the target change a disease-relevant phenotype, and what supports further investment?

Dependencies & synthetic lethality

Which genes may be required in a defined molecular background, and how selective are those dependencies?

Resistance mechanisms & combination hypotheses

Which changes accompany resistance, and which interventions merit combination studies?

Immune-regulatory target exploration

How could perturbations in tumor or immune cells affect recognition and killing, and which models and readouts can test those effects?

PDO 1.0 + PDO 2.0 · Complementary research platforms

From tumor-intrinsic mechanisms to microenvironmental function

Use PDO 1.0, PDO 2.0 or both to connect genetic perturbation with disease-relevant function.

PDO 1.0

Explore tumor-intrinsic dependencies

Design candidate-gene validation, genetic library screening and resistance studies around tumor-cell growth, survival and drug response, connecting targets to tumor phenotypes.

Compare PDO 1.0 and PDO 2.0 ↗

PDO 2.0 / ALI

Explore microenvironment-associated targets and functions

Investigate target function in tissue and immune context through tumor–immune interactions, recognition, killing and drug response.

Explore PDO 2.0 / ALI ↗

Connecting the platforms

PDO 1.0 helps compare tumor-intrinsic phenotypes; PDO 2.0 adds tissue and immune context. Combine screening and functional validation around your target and program goal to prioritize candidates for follow-up.

Genetic library screening & target prioritization

Genetic library screening in organoids

Screen genetic libraries to investigate disease dependencies, drug sensitivity and resistance. Confirm hits through molecular and functional assays in independent models.

From project goal to candidate targetsFive stages of a library-screening study

01
Select models
PDO 1.0 / PDO 2.0
Match the project goal
02
Design libraries
Genes, pathways & controls
Define screening scope
03
Perturb genes
Delivery & perturbation checks
Establish study groups
04
Analyze the screen
Sequencing or phenotype
Prioritize candidate hits
05
Validate targets
Tumor & microenvironment readouts
Inform R&D decisions

Comparison design

Control conditionDrug-treated or study condition

Connect perturbations with growth, survival and drug response to identify candidates for validation.

Target discovery & disease dependencies

Design focused libraries around disease-associated pathways or candidate gene sets to identify potential dependencies affecting organoid growth and survival.

Resistance & combination targets

Compare perturbation effects between drug-treated and control conditions to explore sensitivity, resistance mechanisms and combination strategies.

Functional validation of screening hits

Plan independent perturbations, molecular confirmation, functional assays and validation in additional models to inform target prioritization.

Choose CRISPR or RNA interference, with library scope, controls and sequencing or phenotypic assays tailored to your genes and models.

Discuss a library-screening study ↗

TRiCBIO study results

Models and readouts for target studies

01 · Target-informed model selection

Select matched samples for target research

Under the same staining conditions, candidate tissues show different TGF-β1 expression levels.

Use this comparison to select samples for follow-on PDO drug-response and mechanism studies.

TGF-β1 expression in lung cancer tissue: LC-026 on the left and LC-023 on the right — Left: LC-026, moderate-to-high expression; right: LC-023, relatively low expression. Tissue sections were stained under the same conditions; two fields per sample show DAPI, TGF-β1 and merged channels from top to bottom.

02 · Gene delivery and expression

Gene delivery and expression in HCC organoids

Comparing organoid morphology and expression signals under scramble shRNA and lncRNA shRNA conditions informs experimental conditions for molecular confirmation and functional studies.

Explore gene delivery and perturbation studies ↗

HCC organoids under scramble shRNA, day-3 bright-field and green fluorescence overlay — Day-3 bright-field and green fluorescence overlays show morphology and expression after delivery.

HCC organoids under lncRNA shRNA, day-3 bright-field and green fluorescence overlay — Day-3 bright-field and green fluorescence overlays show morphology and expression after delivery.

03 · Cellular and molecular context

Use paired single-cell profiling to select study endpoints

Paired single-cell profiling of liver cancer tissue and a PDO shows T-cell-related groups, B cells, macrophages and other populations in each sample, helping select models and readouts for immune-associated target studies.

Use that cellular context to select readouts for mechanistic studies and drug evaluation.

Single-cell groups and legend for liver cancer source tissue — One matched tissue–PDO pair, with independent embeddings; interpret cell groups using each panel’s legend.

Single-cell groups and legend for liver cancer PDO — One matched tissue–PDO pair, with independent embeddings; interpret cell groups using each panel’s legend.

Team research foundation

Move from genomic clues to functional validation

A Nature Medicine study involving a member of our team shows how candidate function can be tested: compare Igf2, miR-483 and their combination in Apc-deficient mouse colon organoids, then use histology, proliferation and invasion results to assess candidate driver function.

Li et al., Nature Medicine, 2014 · Fig. 5 ↗

Project deliverables

Project plan: model selection, perturbation strategy, experimental groups and quality criteria.
Project data: perturbation confirmation, functional assay data and candidate-target ranking.
Validation and next steps: confirm key candidates, interpret mechanisms and prioritize follow-up research.

Ways to work together

Contract research & R&D collaboration

Contract research services

Tailor models, screening and validation to your targets, drug candidates and R&D questions, with experimental data, analytical reports and recommendations for follow-up studies.

Discuss a target-discovery project ↗

Joint discovery & validation

Combine complementary models, data, technology and drug candidates to discover and validate targets, investigate mechanisms and advance promising research programs.

Discuss R&D collaboration ↗

Promising targets and candidate programs can progress from joint discovery and validation toward drug co-development.

Field developments

Public studies are expanding organoid target discovery

Three peer-reviewed Nature studies published in August 2026 highlight practical directions for study design: larger patient-derived model resources, genome-wide CRISPR screening in organoids, and dependency maps that include additional cancer subtypes and cell states.

These public studies use patient-derived organoids, spheroids and other patient-derived cancer models, offering references for model coverage, screening scale and hit validation. For client studies, PDO 1.0 can address tumor-intrinsic dependencies; PDO 2.0 can be considered when tissue architecture, immune context or microenvironmental function matters.

A compendium of next-generation patient-derived models for diverse cancers ↗Nature5 August 2026
A resource of 665 patient-derived models across 25 cancer types, linked to clinical and multi-omic annotation for functional research.
A tumour-derived organoid biobank maps cancer gene dependencies ↗Nature5 August 2026
A biobank of 256 characterized tumor organoids, with genome-wide CRISPR screens across 162 models mapping cancer dependencies.
A dependency map enhanced with next-generation 3D cancer models ↗Nature5 August 2026
A set of 147 genome-wide CRISPR screens in organoids and spheroids across 10 cancer types, extending DepMap to new molecular subtypes and state-associated dependencies.

Project discussion

Planning a target-discovery study

What information can start a target-discovery project?

Start with the disease area, candidate targets and the question you want to answer. Our scientists will use any available models or data to recommend screening, genetic perturbation and functional validation. Non-confidential information is enough for the first discussion.

Can target studies use both PDO 1.0 and PDO 2.0?

Yes, separately or together. PDO 1.0 focuses on tumor-cell dependencies, growth and drug response. PDO 2.0 adds tissue architecture and the immune microenvironment. We recommend a platform combination around your target and study objective.

Can target discovery proceed as contract research or joint R&D?

Yes. Contract research provides screening and validation for your targets or candidates. Joint R&D combines complementary models, data and expertise for shared discovery. We agree research roles, data use and intellectual property before the collaboration begins.

Plan your target-discovery study

For the initial discussion, share non-confidential disease context, candidate targets, available models or data, and the R&D decision you need to support.

Discuss a target-discovery project