ACD/Labs Launches MetaSense Platform at ASMS
Product News Jun 07, 2016
ACD/Labs has announced the launch of MetaSense, an automated metabolite identification platform. This new product combines the industry's most-comprehensive metabolic transformation prediction with efficient analysis of LC/MS analytical measurements to identify, visualize, and report chemical biotransformations. ACD/Labs’ solution will yield faster, easier, and more accurate detection and identification of predicted and unexpected metabolites. This offers scientists a significant advantage over existing methodologies.
Built on the ACD/Spectrus Platform, MetaSense uniquely offers knowledge management capabilities that allows the information gained in metabolite studies to be applied in other areas of R&D. The live data environment and new web-based visualization components will facilitate decision-support and effective knowledge sharing throughout organizations and between partners. This will allow discovery chemists to more easily drive synthetic directions to increase/decrease stability, for example, or help development scientists investigate the potential toxicity of parent compounds.
"Having spoken to a number of MetID and DMPK groups, I was surprised to learn of the lack of effective tools to manage metabolite knowledge, and the continued burden of manual data processing and analysis. Scientists are faced with increasing pressures to do more with less. The challenge to more accurately and rapidly identify metabolites and determine the most promising drug candidates must be balanced with shrinking groups and sometimes dilution of expertise," said Richard Lee, Solution Manager, ACD/Labs. "MetaSense substantially improves the efficiency of data analysis and provides best in industry knowledge management for assembled analytical and chemical data to support faster decision-making."
MetaSense provides a broad array of functionality for analytical scientists that undertake detailed metabolism studies, including:
• Native LC/MS vendor format support
• Fractional mass filter for untargeted metabolites
• Metabolite prediction engine
• Ability to fully control the manual processing of data
• A fully featured set of configurable options to automate processing and interpretation of LC/MS data
• Automatic tracking of parent and metabolites for stability studies
• Automatic creation of live biotransformation maps from interpreted data, in chemical context; and creation of a searchable knowledgebase for more efficient collaboration and data dissemination.