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Melissa Launches Druginator, Clinical Data Quality Powered by Machine Reasoning

Verify, Append, and Autocomplete Millions of Pharmaceutical Names, Variants and Dosages to Improve Clinical Data Integrity and Outcomes; Demos at Bio-IT World



Rancho Santa Margarita, CALIF – May 1, 2018 – Melissa, , a leading provider of global contact data quality and identity verification solutions, today announced Druginator, a new, tightly targeted 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. The Melissa Informatics team will feature Druginator at the Bio-IT World Conference and Expo, #BioIT18, booth M634, May 15-17, 2018, at the Seaport World Trade Center in Boston.


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 harnesses the power of 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, slowing mission-critical goals such as FDA approval, time to market and understanding real-world use patterns for drugs. For example, a single medical records database was shown to contain nearly 200 different variations, spellings, and compounds of just one drug commonly used in the treatment of Parkinson’s disease. Discrepancies like this can have crucial implications on patient analyses, treatments, and treatment outcomes,” said Daniel Kha Le, vice president, Melissa Informatics.

Melissa Informatics’ drug, patient, disease, gene, protein, metabolic, and consumer-centered ontologies allow clinicians to easily refocus their research, tapping into different contextual insights based on the same data sets. With Druginator, drug names are checked and verified against a database of drug standard names, to meet FDA, UMLS and other terminology standards as required. Druginator’s append feature searches variations, alternate names, combination drugs, and available dosages to deliver comprehensive intelligence about your checked and verified drug. Autocompletion capabilities accelerate data entry, ensure standardization, and reduce clerical errors by offering an auto-populated list of variants matched in real-time.


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.To connect with Melissa Informatics or members of Melissa’s global intelligence team, visit www.melissa.com or call 1-800-MELISSA.