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JAX Frontend Platform

Preclinical Oncology Platforms​

We develop innovative preclinical models and services that enable informed decision making and compound evaluation. De-risk drug development and move your therapeutic into the clinic faster.

JAX Preclinical Services offers the most translational and predictive efficacy, pharmacokinetics (PK) and safety testing for therapeutics such as monoclonal antibodies, bispecifics, CAR-T, antibody-drug conjugates, and combination therapies.

By combining genetically defined tumors with innovative humanized mouse models, JAX enables the validation of therapeutic candidates in an array of in vivo platforms that better recapitulate the human condition.

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Oncology Models And Study Capabilities

Be confident in your lead selection and dosing decisions with predictive and translationally relevant data delivered by JAX Preclinical Oncology Services.

PDX Library
  • Confirm biomarkers with slides and FFPE samples
  • RNASeq data available for many models
  • Comprehensive efficacy studies available using your therapeutic
  • Verified growth characteristics
  • Low passage tumor models
Onco-Hu Studies
  • Most translational model for immunotherapies
  • Test therapeutic efficacy in the presence of human immune cells and human tumors
  • Compare multiple CD34+ donors or multiple tumor profiles
HuPK For Antibody Therapeutics
  • Accurately evaluates pharmacokinetics of monoclonal antibodies, bispecifics, ADCs, and albumin conjugates
  • Determine first-in-human dosing
  • Reduce dependency on non-human primates
CRS Safety Studies
  • Test clinically-relevant cytokines in the presence or absence of tumor
  • Compare multiple PBMC donors or multiple tumor models
  • Measure downstream toxicities
  • In-life measures and comprehensive histopathology available

Learn More About The
Jackson Laboratory's Oncology
Capabilities

Watch our on-demand webinar on humanized platforms for mAb, bispecific, and CAR-T therapeutics to see how JAX's models and services can produce the most predictive and translationally-relevant data for your next IND

Watch the Video

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