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Contact Us Select Models
Select Models

Next-Generation Sequencing (NGS) is a high-throughput DNA sequencing technology that enables the rapid and simultaneous sequencing of millions to billions of DNA fragments, revolutionizing genetic analysis compared to traditional Sanger sequencing. At Champions, our experts can help integrate Whole Exome Sequencing (WES), RNA sequencing (RNA-Seq), Digital RNA with Perturbation of Genes Sequencing (DRUG-seq), or Whole Transcriptome Sequencing (WTS) into preclinical studies or clinical trials. By utilizing fluorescently tagged nucleotides, Next-Generation Sequencing services allows for the analysis of a millions of genes and targets at once, enabling the identification of novel and rare variants for in vivo and ex vivo studies using tumor and cells. 


Why choose Champions for your next NGS study?

  • Scientific Oncology Expertise : Champions scientists help you plan each in vivo/ex vivo study with endpoint NGS, to gain meaningful and superior results
  • Quick Turnaround & Execution : Short turn around for analysis post study completion
  • High Quality Results : Multistep quality control results in excellence in each NGS dataset
  • State of the Art NGS Data Visualization : Access to Champions’ Lumin web application to assess your datasets in concert with data assembled from over 12,000+ cancer patients, including thousands of clinical treatment responses not available in any public dataset
 
Champions' Next-Generation Sequencing Services Workflow
NGS workflow
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PDX Models with Measured ADC Response

ADC development is expanding quickly across targets, payloads, and tumor types, and target expression alone does not tell the whole story of which models will respond.

Our PDX portfolio includes 1,500+ models across 12 targets, with 250+ benchmarked against clinical ADCs, in vivo. This gives you the opportunity to select models on observed response, in the context of target expression, molecular features, and treatment history, ahead of evaluating your own molecule where comparator data exist.

Coverage across the ADC target landscape

Our PDX portfolio spans established and emerging ADC targets, including HER2, TROP2, CEA, MET, FRα, Nectin-4, and B7-H3, across 12 targets, with models that represent a range of tumor types, molecular backgrounds, and treatment histories. Bring a target and indication, and we can identify models worth testing from the start.
ADC MoA
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Benchmark against models with known ADC response

Model selection increasingly starts with in vivo response rather than expression. We have benchmarked ADCs across our portfolio and captured the full range of activity, from tumor regression to limited or no response. Examine those response patterns alongside tumor type, molecular features, treatment history, and target expression to select the models most relevant to your program. Where a program calls for it, we can also scope models derived from patients pretreated with a specific ADC or payload class, or models with documented resistance.

Published example: Daiichi Sankyo's ifinatamab deruxtecan (DS-7300), a B7-H3 ADC, was benchmarked across Champions' PDX models to characterize its in vivo efficacy during preclinical development.¹

Molecular response and clinical context

We pair observed ADC response with genomic, expression, and treatment-history data so you can choose models that match the biology and clinical context of your program.

NSCLC

Rank models by response to a TROP2 ADC (datopotamab deruxtecan), then cross-filter by EGFR, KRAS, MET, and prior EGFR-targeted therapy. Models with similar TROP2 expression can respond differently, so observed response guides selection.

Ovarian cancer

FRα expression anchors an approved companion diagnostic. We combine FRα IHC with in vivo response, platinum sensitivity, and resistance-associated features such as ABCB1 and ABCC1 expression.

Published example: AstraZeneca’s AZD5335, a novel FRα-targeted TOP1-inhibitor ADC, was evaluated across Champions’ PDX models during its preclinical development.²

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Bispecific ADCs and emerging targets

As ADCs move into bispecific formats and newer targets, selection often starts from target expression, before comparator data exist.

  • Bispecific ADCs

    We can identify models that express both of your targets, e.g., models expressing both EGFR and HER3.

  • Emerging targets

    For HER3 and B7-H4 we identify models with relevant expression; for NaPi2b, in vivo response data are available for benchmarking.

  • Novel payloads

    Our ex vivo platform assesses payload sensitivity independent of the intact ADC.

Published example: ABL Bio's ABL206, a B7-H3 × ROR1 bispecific ADC, was evaluated across Champions' PDX models and has advanced to Phase 1 testing in solid tumors.³ Tubulis's TUB-040, a NaPi2b ADC, was evaluated across ovarian and NSCLC PDX models.⁴

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Go deeper when a program needs it

Beyond model selection, we can characterize the biology behind a response: HT-RNA-seq to surface molecular correlates of response and resistance, cell-surface proteomics to quantify antigen density, and flow-based readouts of ADC activity. We scope these alongside a study when they add value.

Shortlist before you commit

Before you build an in vivo panel, we work through four questions with you, using data we already hold:
  1. 01

    Indication

    Does the tumor type and lineage fit your clinical question?
  2. 02

    Target expression

    High, low, or negative for your target.
  3. 03

    Treatment history and response

    What the patient received, and how they did
  4. 04

    Molecular profile

    Mutations and pathways that could explain a result.

This comes at no cost, so budget is committed only once the shortlist is right.

From there we scope the study: IHC/TMA, surface proteomics, an in vivo PDX panel, or ex vivo payload screening.

On-Demand Webinar

Mastering ADC Model Selection and Navigating Resistance

Antibody-drug conjugates are moving fast, and so is the science behind choosing the right model to develop them. Target expression alone doesn't tell the full story as tumors vary in target density within themselves and across patients, and even a well-selected model can eventually face resistance.
Watch Now

Frequently Asked Questions

We have dosed patient-derived models with the clinical ADCs that hit the same target, at clinically relevant doses and schedules, and recorded how they responded, so you can see the range of responses before running your own study.

As essential context for selection, not a stand-alone predictor. Target density is a real driver of ADC activity and the right place to start, but on its own it does not determine response, because bystander payloads, antigen heterogeneity, and treatment history also shape the outcome.

Established targets such as HER2, TROP2, CEA, MET, and FRα, and emerging targets such as Nectin-4, B7-H3, HER3, B7-H4, and NaPi2b, across 12 targets. The list is not exhaustive, so ask about yours.

Yes. For bispecific ADCs we identify models that express both targets. For novel payloads, our ex vivo platform assesses payload sensitivity independent of the intact ADC.

Yes. We use HT-RNA-seq, cell-surface proteomics, and flow-based readouts to characterize the biology behind a response, and we can scope models with prior ADC exposure or documented resistance.

References

  1. Yamato M, Hasegawa J, Maejima T, et al. DS-7300a, a DNA Topoisomerase I Inhibitor, DXd-Based Antibody-Drug Conjugate Targeting B7-H3, Exerts Potent Antitumor Activities in Preclinical Models. Mol Cancer Ther. 2022;21(4):635-646. doi:10.1158/1535-7163.MCT-21-0554

  2. Zoeller JJ, Tammali R, Dodd RB, et al. Derivation of AZD5335, a Novel FRα-Targeted TOP1i-Loaded ADC, for the Treatment of FRα-Expressing Cancers. Clin Cancer Res. 2025;31(24):5261-5275. doi:10.1158/1078-0432.CCR-25-1749

  3. Kwon JA, Lee S, Kim J, et al. Preclinical development of ABL206, a novel bispecific antibody-drug conjugate targeting B7-H3 and ROR1. MAbs. 2026;18(1):2731283. doi:10.1080/19420862.2026.2731283

  4. Vogl AM, Schmitt S, Mai I, et al. TUB-040, a Homogeneous and Hydrophilic NaPi2b-Targeting ADC with Stably Linked Exatecan, Exhibits Long-lasting Antitumor Activity and a Well-Tolerated Safety Profile. Mol Cancer Ther. 2025;24(11):1685-1700. doi:10.1158/1535-7163.MCT-25-0254 

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Get started

Discuss your program with a Champions Oncology expert

Tell us your target and indication, and we will identify the models we have, how they have performed against clinical ADCs, and the context that matters for your decision, so you move into in vivo work with evidence in hand.