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Melissa Launches Clinical Data Quality Solution Powered by Machine Reasoning

Melissa, a provider of global contact data quality and identity verification solutions, has announced Druginator, a new element of its comprehensive data quality toolset to clean, harmonize, and connect disparate content sources for clinical insight and discovery. As part of the Melissa Informatics array of data quality solutions, datasets, and knowledge engineering resources, Druginator checks and validates millions of pharmaceutical drug names, variants, dosages, and spellings in real time, against a comprehensive drug lexicon aligned with industry standards. 

Druginator provides a web-based UI for checking, verifying, and enriching drug names or lists of drugs, as well as web service APIs for drug data. Diverse, misspelled, and otherwise "dirty" drug information, whether from electronic medical records (EMRs) or from pharmaceutical dictionaries, studies, or public sources, is checked and reported with standardized "preferred terms" to become instantly usable for pharmaceutical and healthcare informatics. This provides an efficient resource to help researchers and clinicians check, verify, and normalize drug terms to reduce costs, increase accuracy, and improve research and patient outcomes. 

Aligning with the industry goal to advance medicine through optimized data, Druginator uses the formal semantic technologies to apply machine reasoning to infer new concepts, linkages, and corrections to data about drugs. Future versions of Druginator will harmonize other types of mission-critical clinical data, such as diseases, genes, and proteins.

Disconnected data is messy and not contextualized, and this can result in slowing mission-critical goals such as FDA approval, time to market, and understanding real-world use patterns for drugs, said Daniel Kha Le, vice president, Melissa Informatics.  Melissa found a single medical records database that was shown to contain nearly 200 different variations, spellings, and compounds of one drug commonly used in the treatment of Parkinson's disease, according to Kha, who noted that discrepancies such as this can have crucial implications on patient analyses, treatments, and treatment outcomes.

Druginator is part of Melissa Informatics' Sentient platform—semantic technologies that can be applied horizontally to accommodate the broad spectrum of pharmaceutical and clinical data harmonization and enrichment needs, integrating content across virtually any data format or terminology regardless of its original source. For more information, go to www.Melissa.com.

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