Skip To Content

ACD/Labs Blog

Scientists’ ability to detect drug-related metabolites at trace concentrations has improved over recent decades. Various cheminformatics tools have been developed to address these metabolite identification challenges. This article describes the current state of these tools, and presents a description of pre-experimental and post-experimental metabolite structure generation using MetaSense.

The knowledge generated in metabolite identification studies can provide valuable insights for intelligent drug design, and the maximum value from these studies can be harvested only if the data are stored and easily accessible within the organization. Similarly, synthetic reactions, forced degradation/stability studies, impurity identification, structural characterization, environmental stability studies and many other activities generate...

Current deformulation scientists face MASSive exSPECtations—they are required to detect, screen, and identify unknowns with increasing efficiency despite shrinking analytical group sizes, pressure to perform more diverse activities, increased outsourcing of work, and slow, tedious, and error-prone methods. As a result analysts are left with much less time to devote to complex deformulation projects, while...

Current metabolite identification (MetID) scientists face MASSive exSPECtations—they are required to detect and identify metabolites with increasing efficiency despite shrinking analytical group sizes, pressure to perform more diverse activities, increased outsourcing of work, and slow, tedious, and error-prone methods. As a result analysts are left with much less time to devote to complex MetID projects,...