Natural Language Processing Solutions for Healthcare and Pharma | Linguamatics

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From real world data analytics to precision medicine research and IDMP compliance, our NLP solutions drive value from textual data across the entire healthcare continuum.

Drug Development Safety and Pharmacovigilance

The growing cost of drug development is driving pharmaceutical companies to identify potential safety issues earlier in the drug development process.

Regulatory Compliance

The pharmaceutical industry is among the most heavily regulated in the world. Linguamatics Natural Language Processing (NLP) can bring time-saving benefits for regulatory compliance compared to manual efforts, which are often slow and expensive.

Precision Medicine

Precision medicine refers to the ability to tailor treatment to the most appropriate group of patients, either at the clinical level, or within drug discovery and development.

Population Health Management and Analytics

To enhance population health analysis and identify the care needs of individuals, providers and payers must extract insights from data stored in unstructured text in EHRs.

Scientists reviewing information

Real World Data Analytics

Linguamatics Natural Language Processing (NLP) extracts the key facts from structured and unstructured data, transforming real world data into insights for decision making.

Clinical Trial Analytics

Clinical trials are used to gather safety and efficacy data on new drugs in development, or existing drugs being tested for new indications.

Clinical Research

Mining unstructured data to support medical research has been prevalent for many years. This requires analysis of Big Data sets and often includes manual chart review to identify patients and extract specific attributes.

Patient Safety

Patient safety is always a priority. Detecting early signs of clinical risk and disease gives us a greater chance of a successful outcome.

Quality Measures

The regulatory burdens of initiative quality measures continue to put a strain on overworked hospital departments, and payers alike.

Disease Registries

Better disease management may be obtained by adding vital information in the form of unstructured data to your disease registries.

Big Data Analytics in Healthcare

The term "big data" was coined in the early 2000s by industry analyst Doug Laney. In Laney's definition, the term referred to information existing in large data sets, with high update rates and in a variety of formats.

Success Stories

Case Study: How Roche Is Using NLP to Gain Patient Insights from Social Media

Case Study: How Roche Is Using NLP to Gain Patient Insights from Social Media

Full Case study

Customer Success

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