Drug Efficacy Prediction

Predict anti-cancer drug efficacy prediction with confidence.

OUR PRODUCTS ARE USED BY DRUG DEVELOPERS (PHARMA, BIOTECH AND STARTUP), CROs, AND ARTIFICIAL INTELLIGENCE INNOVATORS.

DRUG TESTING ON CALICO BIOSYSTEMS’ EX VIVO TUMOR EXPLANT PLATFORM IS THE TRUTH BIOLOGICAL ENGINE FOR YOUR CLINICAL SUCCESS.

CaliTarget

Precision Target Assessment for Smarter Clinical Trials

  • Generate real‑world evidence of target expression and co‑expression across the full tumor ecosystem

  • Quantify target expression levels and the percentage of expressing cells, enabling anticipation of on‑target/off‑tumor drug effects

  • Enable rapid, cost‑effective, and accurate measurement of intact, surface‑accessible target epitopes across all cell populations, reflecting true drug accessibility

  • Integrate tumor cell lines used in prior in vitro pharmacology studies, enabling direct comparative analyses and ensuring continuity across experimental datasets

  • Incorporate mouse tumor models for cross‑species comparison, supporting the selection of in vivo models that recapitulate clinically relevant target expression levels and provide a strong, data‑driven rationale for model selection

CaliPower
Calipower Predict Anti-Cancer Drug Efficacy with Confidence

Predicts patient response at the preclinical stage with unmatched precision

ORR vs CaliPower

  • Integrate experimental multi‑omics data generated on tumors to feed proprietary algorithms that predict and quantify drug efficacy

  • Assess the efficacy of any class of oncology drugs across the top 12 solid tumor indications

  • Evaluate drug efficacy across up to six treatment conditions per tumor

  • Validated in 9 real‑world studies comparing CaliPower drug efficacy scores with clinical objective response rates (ORR)

  • Validated across 7+ indications and >300 patient tumor specimens

  • Enable ranking of lead drug candidates and benchmarking against standard of care (SoC) and competitor therapies

  • Support indication prioritization and optimal combination selection for clinical development

  • Anticipate dose efficacy and inform dose–response relationship studies

CaliHow

Decipher the mechanism of action of your drug to enhance therapeutic potency

  • Leverage multi‑omics data generated from tumor exposure to drugs to characterize MoA in situ at cellular and molecular levels

  • Rationally design and evaluate drug combinations to enhance clinical potency

  • Identify and validate experimental biomarkers of drug responsiveness

  • Enable patient stratification strategies and the design of clinical cohorts enriched for responders

  • Build a precision medicine framework to maximize therapeutic impact and durability of response

Calitarget
CALIDATA

 

Starting 2027

Access a unique, large-scale patient tumor data library ubnder on- and off-treatment conditions

CaliData

  • CaliData captures tumor responses across multiple controlled drug perturbations, creating a distinctive dataset

  • Deep multi‑omics profiles linked to clinical and pathological annotations at the patient level

  • A proprietary, dynamic data asset that trains AI models, guides drug design, and predicts clinical outcomes with high accuracy

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