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Return on Investment

Linguamatics NLP platform enables pharmaceutical companies to boost innovation by providing the previously-hidden insights needed to speed up the drug discovery pipeline and identify new candidate targets.

  1. Boosting Innovation
  2. Speed R&D and Clinical Processes
  3. Reduce Risk and Cost
  4. Improve Patient Outcomes
  5. Optimize Healthcare Quality
  6. Customer Testimonials

Linguamatics NLP platform enables pharmaceutical companies to boost innovation, accelerate research and development while also reducing costs.

The infographic below illustrates the dramatic advances our customers have seen in the processing of clinical documentation in all its forms, together with the resulting improvements in patient outcomes that our technology has helped to deliver.

NLP Linguamatics Return on Investment figures

Boosting Innovation

Linguamatics NLP platform enables pharmaceuticals to boost innovation by providing vital, previously hidden insights needed to speed up drug discovery and identify new candidate targets - while cutting significant costs and wasted time in later drug discovery phases by failing early.

Customers quote time savings of 10x to 1000x in answering very complex questions, with more relevant results.

Agios Pharmaceuticals have used the Linguamatics NLP platform to identify candidate diseases and candidate target genes to develop a whole therapeutic area using text mining technologies.

We don’t just use Linguamatics NLP to find an answer, we use it to build a pipeline. Our rare genetic program was founded on an understanding of the global space of rare genetic diseases which we mined extensively with Linguamatics to identify candidate diseases and candidate target genes - so we actually developed a whole therapeutic area using text mining technologies. 

- Stuart Murray, Research Fellow/Director Informatics, Agios Pharmaceuticals

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Having access to accurate information, for example whether a gene is implicated in a particular disease area, could be the difference between a go no-go decision. Linguamatics NLP lets you put the pieces together to get the whole picture. Linguamatics has really helped us tackle our big data challenges.

- Baerbel LoSacco, Computational Biology Group, Boehringer Ingelheim Pharmaceuticals, Inc.

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The payback has been excellent. Our researchers are experiencing 10x to 1000x time savings to answer very complex questions over conventional literature searching, and with more relevant results.

- Top 10 pharma customer


Rapid identification of new therapeutic opportunities is a key activity in deploying a new platform technology such as Syntaxin’s Targeted Secretion Inhibitors (TSI). Applying an advanced text mining approach via Linguamatics NLP allows companies to access the literature at scale and rapidly define targeting and therapeutic approaches for their technology.

- Keith Foster, Founder & Chief Technology Officer, Syntaxin

In a multiple sclerosis (MS) drugs biomarker project, Sanofi more than doubled the known gene mutations associated with MS using Linguamatics NLP text mining platform.

If we are able to identify causal gene mutations associated with a disease there is a better chance that we can develop a drug that corrects the mutation. [With Linguamatics NLP] we were not only able to identify all 22 previously published autoimmune diseases and drug sensitivities associated with HLA alleles and haplotypes, we also uncovered 33 novel unpublished disease and drug sensitivities - more than doubling previously known associations.

- Dongyu Liu, Associate Director of Translational Science, Sanofi1



We also worked on a social media project where we were looking for digital opinion leaders. We utilize Linguamatics NLP to mine twitter, looking for emerging obesity KOL's in the digital space. Previous to our project with Linguamatics, our medical affairs team paid tens of thousands of dollars to have a similar project done with a vendor.

- Thierry Breyette, Associate Director, Information Analytics, Novo Nordisk

1 Quoted in Outsourcing Pharma external article

Speed R&D and Clinical Processes

Linguamatics NLP platform can speed many research and development and clinical processes. Tasks that used to take months, or were previously not feasible with manual methods, can be done in hours or minutes.

To understand the best treatment pathway for patients, clinicians often try to identify patients’ clinical phenotypes. At the University of Iowa, the average time to curate a single phenotype using the Linguamatics platform decreased from 70 minutes with manual searches to one-minute NLP technology.

If I manually sit at a computer, I could find 25 phenotypes but after training Linguamatics, I can find 130.

Benjamin Darbro, MD, Associate Professor of Pediatrics at the Stead Family Department of Pediatrics 2

Drexel University College of Medicine wanted to reduce the amount of manual chart review needed to identify patients with specific disease comorbidities. Using Linguamatics NLP in patient cohort selection 67% additional relevant patients with HIV and Hepatitis C were identified, with an 80% reduction in manual chart review.


NLP is the preferred means for a growing number of cancer centers to turn unstructured and structured text into smart data by developing workflows automating the capture of information useful for downstream clinical research - reducing to nanoseconds what would have taken hours to do manually […] using the I2E Natural Language Processing engine of Linguamatics to do the otherwise laborious extraction work.

"Pulling Value Out Of Data With Natural Language Processing", Clinical Research News 3

Linguamatics NLP was a huge time-saver. When you’re looking at hundreds of thousands or millions of patient records, the value might be not the ones you have to look at, but the ones you don’t have to look at.

- Walter Niemczura, Director of Application Development, Drexel University College of Medicine 4

Agios Pharmaceuticals is using Linguamatics text mining platform to speed up decision support across multiple applications from drug discovery through to pharmacovigilance:

We’ve used Linguamatics NLP for 10 years, and the reason we use Linguamatics is speed: to get decision support as fast and as comprehensively as possible. We’ve used Linguamatics NLP platform from very early exploratory research to discover targets for our pipeline through to pre-clinical development looking for safety signals, and now most recently for pharmacovigilance to understand what is going on in our clinical trials

- Stuart Murray, Research Fellow/Director Informatics, Agios Pharmaceuticals

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One top 10 pharmaceutical customer used Linguamatics NLP to automate trend analysis from voice of the customer (VoC) call center feeds. For one drug on the market they estimated the automation & workflow implemented saved 4 FTE weeks per year. This workflow would save 1 FTE a year for every 10-12 drugs monitored.

One of the key projects that we've worked on using the Linguamatics NLP Platform is a publication gap analysis. We used Linguamatics to mine PubMed abstracts looking for publications on products, both ours and our competitors. It used to take six weeks of time to get done; and it is now being brought down to hours. We see this as a very big time saver.

- Thierry Breyette, Associate Director, Information Analytics, Novo Nordisk



Spending a couple of hours with Linguamatics NLP saved us around $40,000, by not investing in a project that would have had a negative outcome and wasted money. The answer was already buried in the existing literature but not found using a conventional search engine based analysis.

- Top 20 Pharma customer


Many customers use Linguamatics NLP platform to extract detailed clinical end-points from One top 10 pharma reduced the manual effort of curation from 60 minutes to 5 minutes per record. This also saves experienced staff from “error-prone and psychologically draining” manual curation.


A top healthcare payer is using Linguamatics to extract detailed information from claims data:

In our old NLP system our most complex algorithm took one week of herculean effort to build. With Linguamatics NLP it took just 90 seconds.

- Senior Data Scientist, large US Healthcare Payer

City of Hope Cancer Center is using Linguamatics NLP solution to turn unstructured and structured text into smart data by developing workflows automating the capture of information for downstream clinical research, resulting in a huge time saving:

Given that it takes a person between eight and 12 hours to abstract one patient record - and possibly longer, depending on the patient’s journey and treatment length and complexity—the value yielded by NLP over the long term should be notable.

- Samir Courdy, City of Hope Cancer Center, previously Huntsman Cancer Institute 3


Researchers at the Medical University of South Carolina (MUSC) are using NLP technology to reduce the amount of human effort required to find mentions of social isolation and other social determinants of health in clinical notes from electronic health records (EHRs):

When people go to the doctor, they do talk about social isolation and other determinants of health. But you won’t find that in the coded data. You have to look at the clinical notes – that’s where the information is embedded. It would take a human many months to sort through the notes looking for mentions of social isolation. In contrast, the [Linguamatics] NLP software combed through the 55, 516 clinical notes comprising 150,990 documents from 3138 prostate cancer patients in the training data set in just eight seconds.

- Vivienne Zhu, M.D., M.S., MUSC Biomedical Informatics Center (BMIC) 5


Re-using existing data from clinical trials can help to speed up drug development, and enhance patient care. The process of extracting summary statistics to feed into new clinical trial design is resource-consuming and the risk of human error is relatively high. Eric Su’s team at Eli Lilly uses Linguamatics NLP platform to automate the process and get results which may not have been otherwise possible:

Linguamatics NLP provides data that would take 10s or 100s times longer with tedious manual work. It enables downstream calculations to provide insight. Some work would not have been done or done comprehensively without I2E.

- Eric Su, Principal Research Scientist at Eli Lilly and Company



2 Quoted in Health Data Management external article

3 Quoted in Clinical Research News external article

4 Quoted in Healthcare Innovation external article

5 Quoted in ScienMag external article

Reduce Risk and Cost

Drexel University College of Medicine reduced chart review from five months to less than a week.

Drexel clinical researchers used Linguamatics NLP to sift through 5,700 patient records for HIV and hepatitis comorbidity.

We reduced the number of candidates to 1,150...The project demonstrated the potential for efficiency gains from NLP...We were able to reduce chart review to 20% of the population. The original effort was five months, and we got it down to less than a week... We're at the point where we can use NLP as part of an AI solution to improve care and improve the business.

- Walter Niemczura, Director of Application Development, Drexel University College of Medicine 6

Atrius Health improved management of at-risk populations. With manual chart review, Atrius Health reviewed 1000 charts to identify one care gap. Linguamatics NLP platform reduced manual review needed to only six per care gap identified, improving nurse review efficiency over 150-fold. Atrius also estimated an improvement of $50-100k in risk-adjusted revenue per disease area.

Seventy to seventy-five percent of our annual revenues come from full-risk contracts, so being able to monitor our quality metrics continuously is critical, to ensure we are providing consistently high-quality care...with Linguamatics [our nurses] can now be more targeted in manual chart review. For example, where we used to review 1000 charts to find one patient with conditions like CHF and COPD, now with Linguamatics NLP we only have to review 6.

- Craig Monsen, M.D., CMIO, Atrius Health


6 Quoted in Healthcare Innovation external article

Improve Patient Outcomes

Linguamatics NLP platform is able to provide high-accuracy results across large datasets of unstructured data for population stratification - to more rapidly and better identify at-risk patients and close care gaps.

A large mid-West Health System delivered a Real-World Evidence study at 95-99% accuracy across 100,000 patients in three months with Linguamatics - with 2 analysts who had no previous NLP experience.


Natural language processing has a role to play in precision medicine because data is where value is derived from. It will help you find the answers to the questions you are asking and improve processes, outcomes, and care because you’re learning from the data you’re collecting.

- Samir Courdy, City of Hope Cancer Center, previously Huntsman Cancer Institute 7

NLP has come a long way. I have been a skeptic based on others’ experiences, but this is my first time involved and the results have been tremendous. Those F-measure scores are amazing to me; it’s restored my faith in NLP’s ability to get us out of this data capturing conundrum.

-Joseph Drozda, JR., M.D., FACC, Mercy Health 8

As a healthcare provider leader, Atrius Health requires ready access to clinical notes and data to identify patients with specific conditions, and to address reporting requirements. The shared objective of Atrius Helath and Linguamatics is to advance quality care initiatives, including programs that require the proper identification of at-risk patients to minimize care gaps.

In identifying more patients with particular chronic conditions, we can make sure we are lining them up with our disease management services, ensuring we are resourced to provide those services, and obtain better outcomes. With the additional filtering capabilities that NLP queries provide, we are able to minimize the risk of inadvertently overlooking at-risk patients without adding to the burden of data entry and overload that our clinicians face.

- Craig Monsen, M.D., CMIO, Atrius Health

Linguamatics NLP allows us to close gaps in care, enhance clinical documentation for chronic disorders, reduce litigation risks, and streamline Medicare ACO quality reporting.

- Joe Kimura, M.D., Chief Medical Officer for Atrius Health

Linguamatics NLP can help physicians to better understand their patients and acknowledge the health-related challenges in their day-to-day lives. Researchers at the Medical University of South Carolina (MUSC) are using NLP technology to find mentions of social isolation and other social determinants of health in clinical notes from electronic health records (EHRs):

Sometimes physicians focus excessively on the ‘medical’ problems and don’t pay enough attention to the context that people live in and the social aspects that influence their health. Our study [utilizing Linguamatics NLP] once again highlights the importance of knowing this information in order to provide patients our very best care.

- Leslie Lenert, M.D., MS, Chief Research Information Officer for MUSC and director of MUSC’s Biomedical Informatics Center (BMIC) 9


7 Quoted in external article

8 Quoted in external article

9 Quoted in ScienMag external article

Optimize Healthcare Quality

Mercy hopes to put the Linguamatics NLP to work on an array of other projects to help optimize its workflows and improve quality and outcomes.

One of the biggest benefits for us was availability of Linguamatics medical ontology libraries. Instead of us having to sit here and try to come up with every single way a doctor could have said 'shortness of breath' in a note, they have these libraries: We can start our queries with the libraries, do some validation and maybe alter the query a bit so it's more tailored to the Mercy system. It's been a real time-saver.

- Kerry Bommarito, Director of Data Science at Mercy

NLP allowed Mercy to collect a rich set of medical device information...we were able to show the life cycle of a heart failure patient to see risk factors for heart failure, medications, labs performed, date of heart device implantation, and outcomes such as ejection fraction results...The project showed NLP has the potential to ease the EMR burden on physicians.

-- Kerry Bommarito, Director of Data Science at Mercy 10

At Georgetown University Medical Center, Jonathan Hartmann is using Linguamatics NLP platform to accompany physicians' work and pull up useful information in a time-effective manner.

I work with the doctors in our hospital to find information for them, and I use Linguamatics NLP to help me do that more efficiently. [...]Having Linguamatics allows us to get to that information that we otherwise wouldn’t be able to get to at all or in a timely manner, and this really impacts the care given positively.

- Jonathan Hartmann, Clinical Informationist, Georgetown University Medical Center

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10 Quoted in Health Leaders external article 

Customer Testimonials

Here are some of our satisfied customers...

We use Linguamatics to mine PubMed abstracts and patent Information. Linguamatics have done the hard work for you, so you can focus on the science and interpreting the results a lot faster. Not only does it mean you have less work to do but the work you are doing is a lot more valuable because you are focused on actually answering the question – and you look like a rock star because you can do so really quickly. 

Linguamatics has a great track record: I2E is a very mature product, and the staff are really good at translating the needs of their customers into solutions. The people behind Linguamatics are just as great as the software.

- Principal Scientist, top 10 Pharma

You demonstrated Linguamatics can do exactly what you said you could.

- Director, Information Governance, large Healthcare Payer


We did a through review of different options including Linguamatics. We found that Linguamatics had a very good NLP engine and the flexibility to apply different ontologies was very important to us. It’s easy to plug in any ontology or dictionary and you can extract any domain knowledge. We use Linguamatics NLP for early drug research, gene disease mapping, target identification and prioritization, drug repurposing, interpretation of genes/proteins identified by ‘omics experiments, full patent text mining for new targets, opportunity scouting, pharmacovigilance, competitive intelligence and social media analysis.

- Dongyu Liu, Associate Director of Translational Science, Sanofi 11



The results we have gotten [from Linguamatics NLP] have been tremendous… It’s restored my faith in NLP’s ability to get us out of this data capturing conundrum.

- Joseph Drozda, M.D., cardiologist, Director of Outcomes Research at Mercy 12

We’ve been using [Linguamatics NLP for over 7 years] and we’ve been very happy. We are able to abstract data in an automated sense and identify the data elements that are important to our researchers...Linguamatics has people behind the software that back it up, develop it and continue to evolve it, which makes a big difference.

- Samir Courdy, Chief Research Information Officer, Huntsman Cancer Institute

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The Linguamatics NLP platform is very powerful, it offers you a lot of features a lot of functionality. Frankly there aren’t other tools that are comparable - and I have seen quite a few tools, especially for unstructured data. Linguamatics is definitely our tool of choice.

- Information Analytics Director, Top 10 pharma


There is a rich trove of clinical information in electronic health records that is not accessible to study on a large scale or use to improve patient care because it’s written by doctors in their medical notes, procedure reports, and exam findings. Natural language processing allows us to use a computer to scan through medical records the way Google scans web pages to glean information that can help researchers, physicians, and patients.

In minutes [Linguamatics NLP] identified nearly 54,000 patients with [aortic stenosis], a process that would likely have taken years for physicians to perform manually.

-  Matthew Solomon, cardiologist and physician researcher, Kaiser Permanente North


11 Quoted in Outsourcing Pharma external article 

12 Quoted in Healthcare Innovation external article 

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