By Gail Dutton, Contributing Editor
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Natural language processing (NLP) can be a useful way to extract meaningful information from unstructured data, such as text and tables from electronic health records (EHRs), journals, and social media, but it isn’t ready for full-scale use, according to speakers at the FDA’s June workshop Use of Natural Language Processing to Extract Information from Clinical Text.
"The FDA’s goal is to personalize NLP capabilities to make our medical officers more effective when reviewing adverse events,” Mark Walderhaug, Ph.D., CBER (Center for Biologics Evaluation and Research), said. Workshop speakers suggested NLP may be used to support evidence generation and to improve the scientific validity of efficacy, safety, and post-marketing submissions. It also may find applications in IND (investigational new drug) safety reports, NDA (new drug application) and BLA (biologic license application) submissions, labels, adverse event reports, pharmacoepidemiological studies, and social media and internet queries.