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NaturalText A.I. uses novel artificial intelligence technology to uncover patterns and reveal insights hidden in text data.

NaturalText, L.L.C.

Ellicott City, MD 21043

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PHARMACEUTICALS & LIFE SCIENCES USE CASE (1/10)

Drug Discovery & Target Identification

Problem
R&D in the pharmaceutical, biotechnology, and life sciences industries incur a daily flood of data—mostly in the form of unstructured text. While this provides fertile ground for drug discovery and pipeline development, the huge volume of information also challenges traditional search methods at each stage. First, mapping the disease pathway and genes involved requires a comprehensive review of public domain literature. Examining patent filings are also critical for understanding the current market and its gaps, which key intervention targets should be prioritized for development, and unmet medical needs.
Staying abreast of the latest developments is necessary to maintaining your competitive advantage, but traditional search methods are not equipped to meet the demands of today's seemingly-limitless supply of literature and data. Critical pieces of information can fall between the cracks.
  • Research is filled with jargon that keyword search ignores, making it extraordinarily difficult to compare, rank, and cluster data within and across organizations.
  • Manual methods of handling data, the lack of a standard storage format, and data silos frustrate attempts to integrate data for better understanding and usage.
  • Complicating things further is the massive size of R&D datasets: with dimensions in the millions, it can be nearly impossible to get any output at a business-viable cost.
 
Current Solutions
Traditional search methods make conducting research very costly: you must guess the keywords that will return the most robust and relevant set of results, search keyword-by-keyword, and then spend countless hours determining what is useful. The volume of information available would take far too long for a human to read and digest, but machine learning solutions designed to fix this issue have their own limitations.
Algorithms are only trained to deliver results based on your interests and reading habits. This stunts your ability to find related and eye-opening results from fields outside of your expertise, or interdisciplinary research projects. Different data formats must be analyzed separately, causing the cost to balloon. Both of these types of solutions have no concept of context, leaving you to conjecture about relationships and trends buried in the data.
Next-generation text mining solutions, powered by natural language processing, can help your organization access more information in less time, uncover new insights from existing information, and be confident in the evidence supporting strategic decisions.
  • Traditional keyword search excludes jargon, synonyms, and misspellings. It may also return irrelevant results, such as documents appearing to use the same keyword, but with a different meaning.
  • Today’s enterprise search platforms rank results based on the number of times a keyword appears in each document, not contextual relevance. This still forces users to read each result and decide, on their own, which ones are most relevant.
  • Machine learning methods require extensive preparation, training of data, and tuning and retraining over time, incurring high upfront costs. Each model is prepared for one set of data, and cannot be applied across domains (contexts) or data formats.
NaturalText Advantages
Because NaturalText A.I. understands the content and context of text data—structured and unstructured—you can be confident that you have the latest, most relevant informationIts powerful natural language processing technology can integrate various data formats from internal and public sources, revealing hidden relationships and insights that other software solutions miss. Search for multiple keywords or concepts at a time to extract existing relationships, such as between genes and pharmaceuticals, or uncover new relationships, such as between a disease and a mutation.
On their own, researchers and scientists would not be able to stay up-to-date on the constantly-evolving landscape of information, including patent filings, internal documents, scientific literature, clinical trial documentation, and competitor intelligence. NaturalText makes it possible to use the latest developments to your advantage and acquire efficiency during throughout the drug discovery process.
  • Works out-of-the-box to save companies and labs valuable time and money—no need to tag, train, and tune models!
  • Produces both results and rationales behind the results in human-readable formats, making it infinitely easier to analyze, understand, and explain
  • Leverages information more effectively through seamless integration of text data, bio-sequences, and other formats, so you can make informed decisions more quickly
  • Enables you to search billions of concepts and entities to identify hidden trends and relationships, and find new information
  • Draws the most value out of existing intellectual property and prior research
 
PHARMACEUTICALS & LIFE SCIENCES USE CASE (2/10)

Biomarker Discovery & Pharmacogenomics

Problem
Biomarker identification is critical to gaining efficiency in the drug discovery process and maximizing the value of a drug to consumers. "Biomarkers" is an umbrella term for many physiological signs that guide patient risk prediction, disease diagnosis, drug toxicity assessment, and more. Gene expression levels, the presence of certain proteins, and enzyme activity are all examples of biomarkers. They are instrumental in patient selection for clinical trials, the establishment of treatment safety and efficacy, and the development of personalized medicine.
Pharmacogenomic biomarkers, in particular, are key to personalized medicine, because they provide insight into whether and how a patient responds to medication. Next-generation sequencing (NGS) analysis has opened a much faster pathway to identifying these biomarkers, through accelerating the rate at which genes are sequenced. NGS produces a comprehensive genetic profile, which includes pharmacogenomic biomarkers, variants, and other data necessary to establishing drug–gene association.
Unfortunately, this process is time-consuming and expensive. Final analysis requires scientists and researchers to conduct a manual review of internal research and external literature. Data on known biomarkers, novel biomarkers, genetic mutations, drugs, and diseases are stored in several different formats, making it difficult to extract relationships between them to demonstrate drug–gene association.
  • Manual search methods of literature and databases make it likely that critical information for establishing drug–gene associations will be missed.
  • Different types of biomarker data may be stored in a variety of formats, complicating the process to glean safety, efficacy, and other insights from them.
  • Custom formats are also frequently used to store biomarker data, which further limit which analysis software can be used.
Current Solutions
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
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NaturalText Advantage
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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PHARMACEUTICALS & LIFE SCIENCES USE CASE (3/10)

Drug Re-Positioning

Problem
As competition in the pharmaceutical and biotechnology industry becomes more fierce, and the cost of bringing a new drug to market rises, pressure on companies to widen the markets of their existing drugs continues to grow. One avenue to accomplish this goal lies in finding novel indications, or uses, for existing drugs. Abundant biopharmaceutical research makes this a feasible and straightforward task, in theory. As is the case with drug discovery research, however, searching massive amounts of information for alternative disease applications poses practical issues.
The sheer volume of data and literature available today overwhelms the capabilities of traditional search methods. This means that critical pieces of information are at risk of being lost in the noise. Furthermore, it is not enough just to find literature describing applications that might be relevant—a researcher must spend time reading the whole document, evaluating whether it is relevant, and then reading all other retrieved documents to compare relevance.
  • Jargon and terminology differences appearing in research on potential alternative disease applications will be ignored in traditional keyword search, causing documents that could illuminate a viable re-positioning opportunity to be missed.
  • Analyzing massive datasets and integrating various data types to extract a complete understanding are beyond the reach of traditional search methods.
  • Relationships between the drug, its mechanism of action, and the disease pathway of a potential application must be identified and validated, which is incredibly time-consuming when done manually.
Current Solutions
Traditional search methods make conducting research very costly: you must guess the keywords that will return the most robust and relevant set of results, search keyword-by-keyword, and then spend countless hours determining what is useful. The volume of information available would take far too long for a human to read and digest, but machine learning solutions designed to fix this issue have their own limitations.
Algorithms are only trained to deliver results based on your interests and reading habits. This stunts your ability to find related and eye-opening results from fields outside of your expertise, or interdisciplinary research projects. Different data formats must be analyzed separately, causing the cost to balloon. Both of these types of solutions have no concept of context, leaving you to conjecture about relationships and trends buried in the data.
Next-generation text mining solutions, powered by natural language processing, can help your organization access more information in less time, uncover new insights from existing information, and be confident in the evidence supporting strategic decisions.
  • Traditional keyword search excludes jargon, synonyms, and misspellings. It may also return irrelevant results, such as documents appearing to use the same keyword, but with a different meaning.
  • Today’s enterprise search platforms rank results based on the number of times a keyword appears in each document, not contextual relevance. This still forces users to read each result and decide, on their own, which ones are most relevant.
  • Machine learning methods require extensive preparation, training of data, and tuning and retraining over time, incurring high upfront costs. Each model is prepared for one set of data, and cannot be applied across domains (contexts) or data formats.
NaturalText Advantages
Because NaturalText A.I. understands the content and context of text data—structured and unstructured—you can be confident that you have the latest, most relevant informationIts powerful natural language processing technology can integrate various data formats from internal and public sources, revealing hidden relationships and insights that other software solutions miss. Search for multiple keywords or concepts at a time to extract existing relationships, such as between genes and pharmaceuticals, or uncover new relationships, such as between a disease and a mutation.
On their own, researchers and scientists would not be able to stay up-to-date on the constantly-evolving landscape of information, including patent filings, internal documents, scientific literature, clinical trial documentation, and competitor intelligence. NaturalText makes it possible to use the latest developments to your advantage and acquire efficiency during throughout the drug discovery process.
  • Works out-of-the-box to save companies and labs valuable time and money—no need to tag, train, and tune models!
  • Produces both results and rationales behind the results in human-readable formats, making it infinitely easier to analyze, understand, and explain
  • Leverages information more effectively through seamless integration of text data, bio-sequences, and other formats, so you can make informed decisions more quickly
  • Enables you to search billions of concepts and entities to identify hidden trends and relationships, and find new information
  • Draws the most value out of existing intellectual property and prior research
PHARMACEUTICALS & LIFE SCIENCES USE CASE (4/10)

Drug Development Safety & Pharmacovigilance

Problem
Rising costs of developing and bringing a new drug to market has underscored the importance of evaluating safety early in the process. The longer safety issues remain unaddressed, the more expensive they become—both in terms of money and reputation. The need to analyze the safety profile of a drug continues even after FDA approval and market release Safety data are plentiful, but buried 
 As is the case with drug discovery research, however, searching massive amounts of information for alternative disease applications poses practical issues. The sheer volume of data and literature available today overwhelms the capabilities of traditional search methods. This means that critical pieces of information are at risk of being lost in the noise. Furthermore, it is not enough just to find literature describing applications that might be relevant—a researcher must spend time reading the whole document, evaluating whether it is relevant, and then reading all other retrieved documents to compare relevance.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
 
Current Solutions
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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NaturalText Advantage
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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PHARMACEUTICALS & LIFE SCIENCES USE CASE (5/10)

Precision Medicine Analytics

Problem
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
 
Current Solutions
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
NaturalText Advantage
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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PHARMACEUTICALS & LIFE SCIENCES USE CASE (6/10)

Real World Evidence Analysis

Problem
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Current Solutions
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
NaturalText Advantage
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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PHARMACEUTICALS & LIFE SCIENCES USE CASE (7/10)

Clinical Trial Analytics

Problem
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
 
Current Solutions
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
NaturalText Advantage
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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PHARMACEUTICALS & LIFE SCIENCES USE CASE (8/10)

Clinical Research Acceleration

Problem
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
 
Current Solutions
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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NaturalText Advantage
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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PHARMACEUTICALS & LIFE SCIENCES USE CASE (9/10)

Regulatory Compliance

Problem
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
 
Current Solutions
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
NaturalText Advantage
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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PHARMACEUTICALS & LIFE SCIENCES USE CASE (10/10)

Risk Assessment

Problem
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  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
 
Current Solutions
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
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NaturalText Advantage
Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa. Cum sociis natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Donec quam felis, ultricies nec, pellentesque eu, pretium quis.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
  • Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Aenean commodo ligula eget dolor. Aenean massa.
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