Market-leading    
Natural language processing AI platform for Healthcare & Pharma

Transform your text into positive outcomes to advance human health. Trusted by 18 of the top 20 pharma, the US FDA and leading payers & providers.

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Market-leading Natural language processing AI platform for Healthcare and Pharma

Why Linguamatics?

15+ years’ experience deploying natural language processing solutions to pharma and healthcare
Quantifiable ROI, 95% plus F-scores, trusted by 18 of the top 20 pharma
Award-winning technology

Boost innovation

Provide vital, previously hidden insights needed to speed up drug discovery and identify new candidate targets.

Speed R&D and clinical processes

Tasks that used to take months, or were previously not feasible, can be done in hours or minutes.

Optimize quality and improve efficiency

Augment the review of free text to support quality assessment and reporting, decrease manual chart review.

Reduce risk and costs

Significantly reduce manual chart review, improving review efficiency.

Improve patient outcomes

High-accuracy results across large datasets for population stratification – identify at-risk patients and close care gaps.

Trusted by 18 of the top 20 global pharmaceutical companies, leading healthcare organizations & the US FDA

Agios
FDA
GSK
Johnson & Johnson
Penn Medicine
Roche
80% of biomedical data is unstructured text. Unlock insights, quickly, using natural language processing-based text mining

Text mining (also referred to as text analytics) is an artificial intelligence (AI) technology that uses natural language processing (NLP) to transform the free (unstructured) text in documents and databases into normalized, structured data suitable for analysis or to drive machine learning (ML) algorithms.

More about NLP text mining

Our Solutions

Discover our NLP solutions for pharma, biotech, IDNs, payers, providers, government and healthcare technology organizations.

All solutions for Pharma

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.
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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.
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Voice of the customer data

Voice of the Customer

Voice of the customer (VoC) call feeds can provide a rich source of real world data (RWD). Pharma and healthcare organizations need to understand how their customers (e.g. patients, clinicians) are responding to marketed drugs and gain a broader picture of patient reported outcomes
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All solutions for Pharma
All solutions for Biotechs

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.
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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.
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Drug Discovery

Drug Discovery

Understanding gene-disease associations, pathways and systems, is critical for drug discovery and basic research. Text mining can access the landscape of relevant information.
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All solutions for Biotechs
All solutions for Healthcare Providers

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.
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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.
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Social Determinants of Health (SDoH)

Identifying the social determinants of health (SDoH) hidden within clinical notes and other patient data enables providers and payers to build a complete picture of their patients and members.
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All solutions for Healthcare Providers
All solutions for Healthcare Payers
Risk adjustment for payers

Risk Adjustment

With growing populations of increasingly complex patients, the importance and challenge of accurately documenting and capturing patient disease under value-based care arrangements has never been greater. Technology that enables accurate and consistent coding of patient conditions improves outcomes and mitigates financial risk in delivery of value-based care.
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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.
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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.
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All solutions for Healthcare Payers
All solutions for Academic Medical Centers

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.
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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.
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Disease Registries

Better disease management may be obtained by adding vital information in the form of unstructured data to your disease registries.
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All solutions for Academic Medical Centers
All solutions for Cancer centers

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.
More

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.
More

Disease Registries

Better disease management may be obtained by adding vital information in the form of unstructured data to your disease registries.
More
All solutions for Cancer centers
All solutions for Government

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.
More

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.
More
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.
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All solutions for Government

What our customers say

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Linguamatics has people behind the software that back it up, develop it and continue to evolve it, which makes a big difference.

Samir Courdy, CRIO at Huntsman Cancer Institute

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Linguamatics has really helped us tackle our big data challenges.

Baerbel LoSacco, Computational Biology Group at Boehringer Ingelheim

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Si ergo illa tantum fastidium compesce contra naturalem usum habili, quem habetis vestra potestate.

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Healthcare NLP APIs

Healthcare-tuned application programming interfaces (APIs) provide instant, secure access to our award-winning natural language processing (NLP) platform

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