Advanced 3D Cancer Models for Translational Drug Evaluation

We offer an integrated preclinical platform based on physiologically relevant 3D cancer models to support drug development, mechanism-of-action studies, and biomarker discovery. By incorporating tumor microenvironment features and immune interactions, our approach bridges the gap between conventional in vitro systems and clinical outcomes.

3D Model Development and Validation - We develop and optimize hydrogel-based 3D cancer models using client-selected or approved cell lines. Matrix composition, cell density, and culture conditions are tailored to recreate tumor-like architecture. Models are validated through spheroid morphology, growth kinetics (2D vs. 3D), and baseline proliferation and viability. Where applicable, immune co-culture systems (e.g., PBMCs) are incorporated to better reflect tumor–immune interactions.

Efficacy Assessment - We assess compound activity in both 2D and 3D systems under physiologically relevant conditions. This includes dose–response profiling (IC50/GR50), evaluation across models with diverse sensitivity profiles, and testing in mono- and co-culture settings. These studies enhance translational relevance and support dose selection aligned with clinically meaningful exposure levels.

Mechanistic Studies, Biomarker Discovery, and Patient Selection - We provide in-depth insight into drug response through mode-of-action studies and multi-parametric profiling, including gene expression, metabolomics, calcium signaling, and extracellular pH. Integrated RNA-seq and metabolomic analyses enable identification of predictive biomarkers and molecular signatures. These data support patient selection by identifying features that predispose tumors to sensitivity or resistance, informing targeted therapy development and clinical positioning.

Advanced Study Designs - We enable complex and longitudinal studies, including repeated dosing, combination therapies, and spatial drug distribution analysis, to investigate treatment durability, resistance mechanisms, and therapeutic optimization.