High-Throughput Target Validation & Data-Driven Target Prioritization

Target validation is a critical step in drug discovery, yet traditional approaches remain slow, difficult to scale, and dependent on iterative, target-specific assays. Long experimental cycles, model uncertainty, and fragmented workflows can delay decision-making and increase the risk of advancing poorly validated targets.

Evotec’s Target Validation Engine enables high-throughput target validation by combining scalable genetic perturbation, disease-relevant in vitro models, high-dimensional readouts, and AI/ML-enabled data analysis. This integrated, data-driven approach accelerates validation cycles, expands the number of targets evaluated in parallel, and supports earlier, more confident target prioritization.

Evotec’s Target Validation Engine combines deep experience in CRISPR and phenotypic screening with complex disease-relevant in vitro models, high-dimensional data generation, and AI/ML-enabled analysis. The platform is designed to overcome the scale, speed, and data limitations of traditional target validation workflows.

• Automated perturbation at scale: Evotec applies extensive CRISPR and phenotypic screening expertise to evaluate more targets in parallel, improve experimental consistency, and reduce iterative validation cycles.
• Broad disease model applicability: The platform supports a wide range of disease-relevant in vitro models, including primary and iPSC-derived cells in 2D and 3D formats across therapeutic areas.
• Hypothesis-free, multidimensional readouts: High-content and multi-omics readouts reduce reliance on bespoke target-specific assays, accelerate data generation, and provide data-driven starting points for downstream assay development and discovery biomarker identification.
• AI/ML-enabled data integration and modeling: Knowledge graphs and AI/ML-driven analysis integrate complex phenotypic and multi-omics datasets to reveal disease-relevant networks, improve target prioritization, reduce false positives, and support more translationally relevant target selection.

Evotec’s Target Validation Engine replaces slow, sequential target validation workflows with an integrated, high-throughput approach combining scalable genetic perturbation, disease-relevant in vitro models, and hypothesis-free, high-dimensional readouts.  By integrating CRISPR-based perturbation data with multi-omics datasets, AI/ML-driven modeling, and knowledge graph analysis to reveal disease-relevant networks, we can improve target prioritization and reduce false positives. Ultimately, this expands the number of targets that can be evaluated in parallel, strengthens decision quality, and accelerates the progression of the most promising targets into drug discovery.