Oncology Evaluation Services

Layers of Biological Context in Oncology Evaluation

Oncology candidates that clear preclinical screening still fail in the clinic, and the failure often traces to biology the model never contained - the stromal barrier the molecule had to cross, the immunosuppressive signaling that shut the response down, the immune compartment that was never there at all.

Adding complexity is not, by itself, the answer. A reconstructed tumor microenvironment is only useful when it contains the specific biology your decision turns on, and when the data arrives with the information needed to know how far it can be pushed. Our oncology services are organized as layers of biological context. Each layer answers a different class of question, and most programs enter at one and escalate into another.

Layer Service The Question It Answers Interrogates Throughput
Model foundation - patient-derived tumor models and TME reconstruction Patient-Derived 3D Tumor Model Efficacy Evaluation Does the tumor respond? Sensitivity, resistance, stromal and vascular biology Medium
Functional assay - defined immune effectors against 3D targets Advanced 3D Tumor–Immune Co-Culture Assays Does the immune system do the work? Engagement, killing, exhaustion, potency Medium to high (reconstitution format)
Native tissue context - intact fragments with source matrix and immunity ALI 3D Tumor Fragment Models for ADC Does the molecule reach the work? Penetration, payload release, bystander and off-target effects Low

What Standard Oncology Models Leave Out

Stroma is a barrier, not background. Dense matrix and cancer-associated fibroblasts govern whether a large molecule or a T cell physically reaches tumor cells. Infiltration is a rate-limiting step for cell therapies against solid tumors, and it cannot be modeled in a monolayer.

The immune compartment cannot be assumed. Tumor-cell-only models cannot report on antigen presentation, T-cell activation and exhaustion trajectories, checkpoint biology, or payload toxicity toward immune populations. Animal models carry interspecies immunological differences; humanized models address this partially, at the cost of extended timelines and variable engraftment.

Matrix identity changes the measurement. Animal-derived basement membrane extracts carry lot-to-lot variability and a composition and density that differ from source tissue - which matters directly when the endpoint is diffusion or penetration.

Extended culture moves the target. Target antigen expression can drift away from the source tissue over successive passages, which undermines binding and internalization data unless expression is characterized at assay start rather than assumed.

Our Services

Patient-Derived 3D Tumor Models for Efficacy Evaluation

Patient-Derived 3D Tumor Model Efficacy Evaluation Services

Where conventional patient-derived 3D culture expands tumor cells alone in animal-derived matrix, this service reconstructs the microenvironment: tumor cells together with immune cells, cancer-associated fibroblasts and endothelial cells, in defined synthetic hydrogels or decellularized ECM, under static, air–liquid interface or dynamic perfusion culture selected by endpoint.

Applied to: immune checkpoint inhibitor evaluation in autologous immune-competent models; CAR-T trafficking and solid tumor penetration under perfusion; bispecific T-cell bridging efficiency in 3D; CAF-directed and anti-angiogenic agents in vascularized configurations; resistance, invasion and matrix remodeling biology.

Model Panel: clinically annotated patient-derived models across breast (TNBC, HR+/HER2−, HER2+), colorectal (primary and hepatic metastasis, MSI-H/dMMR vs MSS), pancreatic (desmoplastic, chemo-resistant, with stromal density scoring), ovarian (high-grade serous, platinum-resistant, HRD status) and melanoma (BRAF V600, NRAS, PD-L1 expression).

Endpoints: flow cytometry, live-cell and confocal imaging, cytokine profiling, spatial transcriptomics, with viability, morphology and marker-expression QC at each passage and inter-replicate CV reported with every dataset.

Where It Stops: throughput is medium - this is deep mechanistic and immuno-oncology work, not primary sensitivity screening, for which conventional high-throughput 3D expansion remains the appropriate and complementary tool. Microvascular networks are available on MPS-based configurations and are preliminary rather than a full vascular bed. Model establishment success rate and expansion timeline are reported per case before assay initiation, because they are case-dependent.

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ALI 3D Tumor Fragment Models for ADC Penetration and Efficacy

ALI 3D Tumor Fragment Models for ADC Penetration & Efficacy

The tissue-context layer, applied to the delivery problem. Minced tumor tissue is combined with a collagen matrix on a permeable membrane support, fed by diffusion from below with the upper surface exposed to the gas phase. Stroma, native matrix and endogenous CD45⁺ immune populations - CD8⁺ T cells, regulatory T cells, macrophages - are carried over from the source tissue rather than reconstituted from purified components.

Applied to: ADC penetration depth through dense stroma as a function of DAR and payload hydrophobicity; free payload release kinetics; cytotoxic potency mapped against where the molecule actually reached; bystander activity; effects on the local immune compartment; and ADC–checkpoint inhibitor combination arms.

Endpoints: target antigen characterization at assay start by IHC and immunofluorescence; binding and internalization with labelled material; penetration by three orthogonal routes - confocal imaging of labelled ADC, mass spectrometry imaging of unlabeled payload, and IHC on sectioned fragments; free payload quantification by LC-MS/MS in tissue and medium, with method performance established in matched matrix at feasibility.

Where It Stops: low throughput, technically demanding, and gated by fresh resected tissue availability within a defined collection window. Dosing and readout commonly run 7–14 days from establishment; the assay window is set so the populations relevant to your endpoint are present throughout, not to the maximum achievable duration. Not a screening tool.

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3D Tumor–Immune Co-Culture Assays

Advanced 3D Tumor–Immune Co-Culture Assays

The functional immunology layer. Patient-derived 3D tumor microtissues are paired with defined immune effector populations to generate data on immune-mediated killing, cytokine response and effector phenotype - with 3D architecture retained, so that chemotaxis, matrix penetration and target engagement are represented rather than bypassed.

Effector modules:

  • T cell (CD8⁺, CD4⁺, CAR-T, TCR-T) - checkpoint inhibitor evaluation, adoptive cell therapy penetration and cytotoxicity, tumor-reactive T-cell expansion. Readouts include proliferation, CD107a degranulation, IFN-γ/TNF-α/IL-2 profiling, granzyme B and perforin, and exhaustion phenotyping (PD-1, TIM-3, LAG-3, TIGIT).
  • Macrophage / TAM - polarization under 3D oxygen and metabolite gradients, phagocytosis-directed agents including CD47-axis antibodies and CSF-1R inhibitors, and macrophage-derived suppression of T-cell access.
  • NK cell - ADCC quantification, CAR-NK potency against solid tumor models, and combination strategies including NKG2D ligand upregulation and IL-15 support. Not MHC-restricted, which makes allogeneic healthy-donor NK a practical effector source; KIR–HLA relationships are accounted for in donor selection.
  • Dendritic cell - vaccine and neoantigen-driven maturation, TGF-β-mediated suppression of antigen presentation, and DC-directed checkpoint regulation in three-way DC–T–tumor configurations.

Where It Stops: allogeneic T-cell configurations carry alloreactive killing unrelated to the mechanism under test, so antigen-specific endpoints require autologous or HLA-matched material - which extends the timeline substantially and depends on matched availability. Tumor-reactive responses are not detected in every donor–tumor pair; where a reactivity threshold matters to the program, the interpretation of a negative result is agreed at Stage 1 rather than after the fact.

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The Decision That Shapes Every Study: Where the Immune Cells Come From

Across this portfolio, the single most consequential design choice is not which tumor model - it is which immune source. The two formats answer different questions and trade against each other on every axis.

Endogenous-Immune Format (ALI Fragment) Reconstitution Format (Defined Co-Culture)
Immune source Native TILs, macrophages and stromal fibroblasts carried over with the tissue PBMCs, expanded TILs, isolated subsets, or client-supplied engineered effectors
Composition control Limited: reflects what was present in the sample Defined: subset identity, purity and E:T ratio set by design
Consistency across arms Lower: varies between donors and within a sample Higher: one effector preparation across all arms
Usable window Constrained: composition and viability shift over culture Extended: effectors can be replenished
Throughput Low Compatible with plate-based screening
Material Fresh resected tissue within a defined collection window Established 3D model plus a separate immune source
Answers What does the TME do, as it arrived from the patient? What does this effector or antibody do, under controlled conditions?

Choosing the Right Entry Point

Question Addressed Start with the Model Indicative Program Duration* Not The Right Fit For
Which patient-derived models does my target hit, and how does the stroma modify it? Reconstructed TME Model Confirmed at design; establishment timeline reported per case Primary high-throughput sensitivity ranking
Does my checkpoint antibody reactivate T cells against autologous tumor? Co-Culture (autologous configuration) ~4–6 months, subject to matched material Programs that cannot wait on matched donor material
Is my CAR-T / CAR-NK product potent against a 3D solid tumor with intact matrix? Co-Culture (reconstitution format) ~3–5 months Establishing clinical potency specifications
Does my CAR-T actually traffic and extravasate before it kills? Reconstructed TME Model, perfusion configuration Confirmed at design Static-format budgets and timelines
Does my ADC penetrate dense stroma, and where does the free payload go? ALI 3D Tumor Fragment ~4–7 months, gated by tissue availability Ranking a construct library
Is my payload's bystander benefit costing me immune toxicity? ALI 3D Tumor Fragment ~4–7 months Any design needing a single composite efficacy number
I need to rank many candidates before going deep. Conventional high-throughput 3D expansion, then escalate - Immuno-oncology or TME-dependent endpoints

* Indicative only, derived from the stage durations published on each service page and subject to design.

Start from Your Modality

Target Molecule Route Endpoint
Immune checkpoint inhibitor Co-Culture - autologous, or ALI fragment Whether T-cell reactivation requires the donor's own antigen background
Bispecific antibody / T-cell engager Co-Culture - reconstitution format Bridging efficiency in 3D space under a controlled effector preparation
CAR-T / TCR-T Co-Culture; Reconstructed TME Model under perfusion where trafficking is the question Cytotoxicity versus extravasation and barrier penetration
CAR-NK / ADCC-competent mAb Co-Culture - NK module MHC-unrestricted killing permits allogeneic effectors; KIR–HLA still modifies activity
Myeloid-directed agent (CD47 axis, CSF-1R) Co-Culture - macrophage / TAM module Polarization under 3D oxygen and metabolite gradients
Cancer vaccine / neoantigen / DC-directed Co-Culture - DC module, three-way configuration Maturation and cross-presentation, then downstream T-cell priming
Antibody–drug conjugate ALI 3D Tumor Fragment Penetration depth, free payload, bystander resolved from off-target toxicity
ADC + checkpoint combination ALI 3D Tumor Fragment with a checkpoint arm Endogenous immune compartment must be present at assay start
Stroma-directed / anti-angiogenic Reconstructed TME Model, vascularized perfusion configuration Requires a microvascular network and flow
Chemotherapy / targeted small molecule Tumor-only model configuration Throughput and mutation stratification, not immune context

Patient-Derived Material: Sourcing and Governance

Oncology work depends on human tissue, and the governance around it is part of the service rather than an administrative footnote.

  • Consent and Ethics: Models and fresh tissue are sourced under documented informed consent and applicable ethics approvals, with clinical annotation supplied alongside the model.
  • Collection Windows: Fresh resection and core biopsy work is scheduled against collection availability for the specified indication; minimum viable tissue mass is confirmed at intake.
  • Sample Economy: How many conditions one resection supports depends on tumor size, viable tumor content and endpoint mix - sectioning-based endpoints consume fragments that imaging endpoints can share. Assessed at design, confirmed at feasibility. Where a design exceeds one sample, the study runs across multiple donors with donor identity tracked in the analysis.
  • Cross-Border and Data Considerations: Where a program involves transfer of human biological material or associated genetic data across jurisdictions, applicable regulatory approvals are identified at scoping and built into the timeline.
  • Client-Supplied Cell Products: Receipt requirements and biosafety documentation for engineered effector products such as CAR-T or CAR-NK preparations are agreed at Stage 2.

One Operating Standard Across the Portfolio

Different biology, identical scientific governance.

1

Criteria are set before the data exists.

Endpoints, controls, E:T strategy, replicate number, statistical approach and acceptance criteria are fixed in a written protocol and signed off before work begins.

2

Feasibility is a stage, not an assumption.

Working E:T ratio, achievable assay window, target antigen expression range and analytical method performance in matched matrix are established on a small scale before the full study commits.

3

Runs are released against pre-defined criteria.

Vehicle-control viability at readout, antigen expression within the feasibility range, positive-control response, analytical system suitability, and inter-replicate or inter-fragment variation within a defined range.

4

Distinct biology gets distinct endpoints.

Where two different biological effects can occur at the same concentration, they are reported as two measurements rather than one composite. Bystander killing and off-target immune toxicity, for instance, are never merged; cytotoxicity is reported both overall and as a spatial pattern relative to penetration depth, because whether killing tracks with where the molecule reached is a different question from how much killing occurred.

5

Variability is tracked, not absorbed.

Inter-replicate CV is reported with every dataset. Donor identity is retained in the analysis. Comparative studies run on matched fragments from the same source tissue, structured so each donor contributes to both arms.

6

Divergence is reported, not resolved.

Where results conflict across endpoints or with your existing data, the report states it and its likely sources. A weaker signal in a more complex model is not treated as grounds for discounting a liability.

How An Engagement Runs

How An Engagement Runs

Design Your Oncology Evaluation

Tell us the decision the data has to support. We will tell you which layer of the portfolio fits, what it can conclude, and where it stops.

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