ICE Bioscience Posters

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In drug discovery, proactive toxicological risk assessment is critical for mitigating clinical-stage attrition and post-market withdrawals. Traditional preclinical strategies face significant limitations: in vivo models often exhibit poor human translatability due to species differences, alongside ethical and cost constraints, while conventional in vitro binding assays fail to capture functional biological effects. Given that approximately 75% of clinical adverse drug reactions (ADRs) are dose-dependent and originate from off-target interactions, the demand for more predictive early-risk identification tools is pressing. Addressing this need, the IQ DruSafe consortium—a preeminent alliance of global pharmaceutical companies—has advocated for enhancing predictive power by expanding and refining secondary pharmacology screening. Aligned with this initiative and the SLAS Europe 2026 theme of “Shaping the Future of Life Sciences and Automation,” this study investigates the implementation of an advanced, automation-driven in vitro screening system utilizing functional assay formats. By integrating high-throughput automation platforms, such as automated liquid handling systems, this strategy moves beyond mere binding affinity to generate rich, quantitative pharmacological data with high precision and reproducibility. The purpose is to leverage this automated, functionally-oriented screening to enable a more accurate and earlier identification of potential safety liabilities, thereby providing highly translatable insights for lead compound optimization and reshaping the paradigm of early safety assessment.

The ICESTP SAFETYPANEL™ 77 Dose Response platform provides a comprehensive functional screening strategy that integrates single-point primary screening with quantitative dose-response (curve-based) profiling. This strategy is supported by a broad suite of mechanism-relevant functional assay technologies, including FLIPR calcium flux assay, HTRF, ADP-Glo, fluorescence polarization (FP), and other mechanism-relevant functional formats. The entire workflow exemplifies the convergence of functional biology and advanced automation. The process is fully automated—from initial compound handling via Echo and Firefly systems, through functional readouts on platforms like BMG. This integrated approach ensures exceptional efficiency, reproducibility, and data richness. By accelerating the safety profiling process, minimizing manual error, and delivering mechanistically insightful, quantitative datasets (e.g., IC₅₀/EC₅₀), the platform enables more reliable optimization of candidate compounds early in the drug discovery pipeline.