Ksilink's expertise
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Our Expertise

Patient-based disease models carry a huge potential for the identification of novel MOAs and targets and the generation of more efficient drugs. Aligning Europe’s best experts from academia and industry, we conduct most valuable drug discovery programs from early disease modeling and data correlation up to preclinical candidates.

Our Rationale

With a strong focus on monogenic diseases, we design most authentic patient-based disease models with isogenic healthy controls. Our models benefit from a whole set of unique proprietary technologies for high quaility cell differentiation, upscaling methodologies, cryopreservation, and expertise in 2D and 3D disease modelling.

Ksilink’s key assets lay in our tailored AI-powered phenotypic profiling capacities, applied to high-content image analysis, allowing for extracting the maximum of phenotypic information within a minimum of time. Applying these assets, our models become fully automated 2D assays in 384 format, ready for large phenotypic screening campaigns. 

In order to identify and develop most valuable first-in-class compounds, with the best efficacy and safety profile, we combine phenotypic screening campaigns of annotated and high-quality diversity compound libraries with latest technologies, including validation of Hit compounds on patient-based 3D cellular models, data correlation from large cell-painted compound libraries, AI-assisted evaluation of safety profiles etc.

Our technological expertise and innovative spirit accompagnies each program up to the validation of most valuable preclinical candidates.


How we maximize success:

  • Bundling clinical, academic and industrial expertise
  • Covering the entire value chain around patient-based drug discovery
  • Applying outstanding disease modelling expertise and cell differentiation protocols
  • Developing powerful AI-based algorithms enabling large phenotypic screening campaigns
  • Smart and flexible use of high-quality annotated libraries and cell painted data sets
  • Identifying novel MOAs by combining powerful target deconvolution technologies