Recherche et Développement

Logiciels scientifiques > Adme/Tox    PAGE EN COURS DE TRADUCTION

Cytotoxicity

HazardExpert Pro upgrades

• Elimination of cytotoxic compounds in the early phases of drug discovery can save substantial amounts of research and development costs. The nonlinearity, proven to be involved in the relationship between the molecular structure and ADME/Tox properties, explains the successful application of neural networks on this field. An artificial neural network based approach using atomic fragmental descriptors has been developed to categorize compounds according to their in vitro human cytotoxicity. This novel method can be used to filter out drug candidates with potential cytotoxic side effects in the early phases of the drug discovery pipeline. such as before synthesis or assays during lead development or lead optimization. The developed algorithm is available as a part of HazardExpert Pro module of the newest generation of the Pallas software family.
• A new artificial neural network based approach using atomic fragmental descriptors has been developed to categorize compounds according to their in vitro human cytotoxicity. Fragmental descriptions were obtained from the linear logP calculation method implemented in Pallas PrologP program.