How does ICE Bioscience reduce IP and know-how risks when sponsors transfer proprietary compounds and assay designs?

ICE Bioscience builds discovery campaigns on internal platform technologies, including ICESTP Safety Panels and ICECP and KRAS cancer cell panels, which reduces the need for sponsors to transfer proprietary assay architectures or cell assets. ICESTP uses predefined target sets aligned with Bowes-44 and Safety-77 literature, and ICECP uses an internal bank of more than 600 tumor cell lines, over 100 engineered and resistant lines, and more than 500 human tumor cell lines for panel construction.

How does ICE Bioscience address assay reproducibility and false-positive or false-negative risk?

ICESTP Safety Panels 44 and 77 are functional secondary pharmacology panels run in both single-concentration and full dose–response modes with potency estimation. All kinase targets are profiled at 1 mM ATP, and reports include radar plots and concentration–effect curves, allowing sponsors to evaluate consistency and confirm pharmacology across targets.

How does ICE Bioscience support raw data transparency and secondary pharmacology data integrity?

ICESTP outputs include full dose–response data, numerical effect tables, and graphical plots for each target, giving sponsors visibility from primary response values through to IC50 or EC50 metrics. The panels are aligned with published Bowes-44 and Safety-77 recommendations, which provide an external reference for target selection and data structure.

How does ICE Bioscience limit variability in high-throughput screening compared with manual offshore setups?

ICE Bioscience operates a joint automated laboratory with SPT Labtech in Beijing that integrates firefly liquid handling into high-throughput screening and assay development workflows. Firefly supports non-contact positive displacement dispensing over nanoliter to milliliter ranges in 96-well and 384-well formats and is used for 2D and 3D viability, clonogenic, and panel assays, reducing operator and plate-to-plate variability.

How does ICE Bioscience align safety pharmacology services with Western regulatory expectations?

ICESTP Safety Panel 44 is described as aligned with historical Bowes-44 off-target selection and ICH expectations, and ICESTP Safety Panel 77 is described as aligned with the industry Safety-77 framework for secondary pharmacology. The ICESTP Drug Abuse Safety Panel follows FDA recommendations for assessing drug abuse potential with 55 CNS targets and 101 assays.

ADC-Focused CDX Models

ADC CDX Models

Why In Vivo Models Are Essential for ADC Development

Antibody-Drug Conjugates (ADCs) represent one of the most promising modalities in modern oncology. However, their complex mechanism of action—combining target binding, internalization, lysosomal processing, payload release, and bystander effects—cannot be fully captured by in vitro assays alone.

CDX Models — The Strategic Choice for Early-Stage ADC Research

Cell Line-Derived Xenograft (CDX) models are generated by implanting well-characterized human tumor cell lines into immunocompromised mice. While Patient-Derived Xenograft (PDX) models offer high clinical relevance, CDX models offer distinct advantages that make them particularly well-suited for ADC drug discovery and early-stage development.

Key Advantages of CDX Models for ADC Studies：

✅ Controlled Antigen Expression — Cell lines can be pre-screened and selected for high, medium, or low antigen expression, enabling direct correlation between target density and ADC efficacy.

✅ Rich Molecular Characterization — Well-defined genetic backgrounds facilitate mechanistic interpretation and biomarker discovery.

✅ Rapid Tumor Establishment — Faster tumor formation compared with PDX models, accelerating your screening timeline.

✅ High Reproducibility — Genetically homogeneous cell populations ensure statistically robust data for efficacy and toxicity studies.

✅ Extensive Library & Scalability — Access a diverse catalog of models that balance scientific rigor with budget efficiency for high-throughput screening.

✅ Drug Resistant Models Availability — Beyond conventional CDX models, ADC-resistant xenograft models are available to support next-gen ADC optimization and resistance mechanism research.

Our ADC-Focused CDX Model Portfolio

At ICE Bioscience, we've built a comprehensive portfolio of ADC-focused CDX models spanning multiple cancer indications and targeting key antigens including HER2, TROP-2, Nectin-4, and TOP1.

Representative ADC-Focused CDX Models (Updated regularly)

No.	Indication	Cell Line	Positive Control (Antigen)
1	Breast Cancer	MCF-7	DS-8201a (HER2)
2	Breast Cancer	HCC1954	Kadcyla (HER2)
3	Breast Cancer	HCC1806	Trodelvy and SKB264 (TROP-2)
4	Breast Cancer	MDA-MB-231	Trodelvy and SKB264 (TROP-2)
5	Breast Cancer	JIMT-1	DS-1062a (TROP-2)
6	Breast Cancer	MDA-MB-468	Padcev (Nectin-4)
7	Gastric Cancer	NCI-N87	DS-8201a (HER2)
8	Gastric Cancer	NCI-N87/DS8201-R	DS-8201a (HER2)
9	Pancreatic Cancer	BxPC-3	DS-1062a (TROP-2)
10	Uterine Cancer	ISHIKAWA	DS-1062a (TROP-2)
11	Ovarian Cancer	SK-OV-3	DS-8201a (HER2)
12	Colorectal Cancer	DLD-1	Exatecan and DXd

Whether you're optimizing payload selection, evaluating combination strategies, or investigating resistance pathways, our validated ADC CDX platform is designed to deliver actionable insights and accelerate your path to IND.

ADC and Resistance Study

Figure: ADC efficacy evaluation in different CDX models. (A) MCF-7 Xenograft Model (HER2); (B) HCC1806 Xenograft Model (TROP-2); (C) NCI-N87/DS-8201a-R Model (HER2 Acquired Resistance)

Learn more:

Antibody/ADC In Vitro Screening and Evaluation

In Vitro Bystander Effect Assays

Non-Clinical DMPK Services for ADC

ADC Payload Screening and Profiling