The transformation of the analytical data to information in a fast and automate fashion is not really the end of the process, conversely, it is the starting to take informed decisions on how to proceed on assay utilization, structure optimization, formulation selection, hypothesis validation, compound characterization, etc. Consequently, we are not only providing tools to analyze data but also using the information generated from that analysis to develop for example Machine Learning model for multiple endpoints, studying potential secondary pharmacology for the compound, the metabolites or reporting the results comparing multiple experiments types. Therefore, the user can make informed decisions in the Design-Synthesis-Test cycle that follows the scientific methodology in the development of a new medicine.
Since we are not limited to any specific workflow with a high degree of flexibility, our solutions are useful for Drug Metabolism and Pharmacokinetics departments, Life Sciences, Chemistry, Omics, Translational medicine, etc.