Discover more, discover faster. High performance, flexible NLP-based text mining for life sciences

Transcription

1 Discover more, discover faster. High performance, flexible NLP-based text mining for life sciences

2 It s not information overload, it s filter failure. Clay Shirky Life Sciences organizations face the challenge of filtering ever-increasing volumes of textual data to gain actionable insights for key decision-making. The volume, variety and velocity of data is increasing exponentially. The big question is, how do we make the best use of these data? Key benefits Save time during R&D with better decision support Reduce resources and experimental costs Generate new opportunities - answer questions that couldn't otherwise be answered Create visual summaries from unstructured text - for rapid understanding and evaluation Gain competitive advantage - reveal weak signals, sentiment and novel relationships

3 Linguamatics agile NLP text mining software, I2E, provides rapid knowledge discovery from unstructured and semi-structured text. Using I2E, knowledge can be extracted from a wide range of content sources such as scientific literature, patents, clinical trials data, electronic health records Linguamatics I2E has been used for many applications in life sciences across the drug discovery-development lifecycle, including biomarker discovery, drug re-purposing, clinical trial analytics, analyzing chemical safety/toxicity signatures, and market intelligence through the analysis of social media. (EHRs), news feeds and proprietary content. This knowledge can then be used to answer high value questions in real time. Linguamatics text mining technology is more effective for knowledge discovery than traditional search and is now well established and proven across the life science industry, including pharmaceuticals, biotechnology, healthcare, consumer products, Anyone considering text mining will find a specialist with unrivalled domain knowledge in Linguamatics Jason Stamper, 451 Research agrochemicals, government and more. Solutions & applications in life sciences Prediscovery Drug discovery Pre-clinical Phase l clinical trials Phase ll clinical trials Phase lll clinical trials Regulatory review Scale up to manufacture Post marketing surveillance Gene-disease mapping Regulatory submission QC Target ID/selection Trial site selection and study design HEOR Toxicity analysis and prediction Safety Pharmacovigilance Mutation/expression analysis SAR Competitive intelligence Biomarker discovery Comparative effectiveness Drug repurposing KOL identification Social media analysis Patent analysis Opportunity scouting Race to patent Race to market Maximise market value Advanced text analytics delivers value along the pipeline

4 Making the most of your information assets These case studies show some of the ways I2E has been used to capture valuable information from life sciences literature, saving time and increasing productivity across the drug discovery pipeline. Targets: identification, validation and selection Selecting the best targets in the drug discovery process is crucial for optimizing return on R&D spend across a portfolio of research projects. Researchers use text mining to establish target ranking based on efficacy and safety. Methods include providing links to biological pathways and processes, and supporting gene expression analysis in specific tissues and At a top-10 global pharmaceutical company, Linguamatics I2E forms part of a standard reusable framework for novel target selection in use for a variety of R&D projects. Our advanced NLP capabilities and intuitive reporting make it simple for scientists to see assertions and drill down to supporting evidence in source documents. species. A variety of pathway databases exist but their scope may be limited to a small number of premier journals. In addition, there is often a lack of contextual information to focus the specific pathway analysis. Text mining approaches complement pathway database searches by providing both target context and access to up-to-date results from a much I2E customers have reported ten fold time savings in this type of literature analysis. For 100 scientists, this is equivalent to savings of 10 FTE years or approximately $1m/year. more comprehensive range of documents.

5 Providing a competitive edge with patent analytics Patent literature often provides the first mention of much critical data for novel chemistry and biology - for example, compound structure, protein target, intended disease area. Access to these valuable data can provide a competitive edge for pharmaceutical researchers. However, patent literature is notoriously hard to search patents can be hundreds or thousands of pages long and contain complex information often written with obfuscation rather than communication in mind. Matching up mentions of chemical structures or gene targets in one part of a document with properties and other information mentioned somewhere else, especially tables, is very challenging. A traditional keyword search/document retrieval approach is time-consuming and tedious as many hundreds or thousands of patents may be retrieved, Because a natural language processing approach involves understanding the meaning of the text, text mining using I2E enables a rapid and deep analysis of patent documents, potentially saving millions of dollars. I2E can search for numerical information, chemicals by name or structure, classes of drug targets or therapeutic area, focus the search on specific regions of the patent documents, or follow claim chains across a patent. A top-10 Pharma company used the chemistry search capability built into I2E, along with sophisticated query strategies and algorithms to pre-process tables, in order to extract detailed numeric and biological information from patent documents. The company was able to perform more rapid freedom-to-operate searches in comparison to standard patent search. particularly for in-depth patent analytics such as opposition searches or patent landscaping. Clinical trial analytics Clinical trials are used to gather safety and efficacy data on new drugs in development or existing drugs tested for new indications. Although some information in published clinical trial reports is well structured and searchable using keywords, much of the key information lies in unstructured text. I2E is essential to extract and synthesize the high value information that is found only in these unstructured regions. This can then be used to: Select trial sites more effectively, and find precedents for study design protocols Gain actionable information about competitors' worldwide clinical development activities, for example monitoring progress of competitors According to our customers: using I2E, the time for site selection can be reduced by over 80%. For patient recruitment, time spent can be reduced by at least 25%. trials, or finding other companies running clinical trials in the same therapeutic area Uncover in-licensing opportunities, by finding sponsors running early-stage clinical trials in particular therapeutic areas

6 Biomarkers: identifying the crucial link between pre-clinical and clinical information Investigating indirect gene-gene relationships between a drug compound, Raptiva, and a disease, Psoriasis, using interaction network visualization. Mechanistic studies of compounds require specific traits to be measured; similarly, clinical studies of patients need to have a biomarker to quantify effects of disease progression and treatments. These biomarkers can take different forms, e.g. enzymes with varying activity, changes in expression levels of particular genes, or the presence or absence of individual metabolites. The flexibility of I2E allows the user to search for any of these data types and to find relationships between items that link therapeutics to phenotypic effects. At a top-10 pharmaceutical company, I2E is used to create a database of candidate biomarkers by mining MEDLINE and full-text articles that can then be queried by scientists. I2E can also scan the literature for specific disease biomarkers on a day-to-day basis, Scientific literature must be in a computationally accessible format to be used for systems biology studies, and custom curation is frequently needed. However, text analytics speeds creation of custom annotation by as much as an order of magnitude, lowering the barrier to accessing the wealth of information available in scientific literature. Library & Information Services, Top-20 Biotech to maintain the currency of the in-house database.

7 Clinical and post-market safety Organizations increasingly require auditable methods to check whether signals indicating adverse or toxicity related events appear in clinical records. If events do occur, companies need to be able to react fast to find out if they are caused by the drug, are side effects of the original disease or are the result of external factors. Text mining can be used to review clinical reports to search for signals of adverse events. For example, Linguamatics I2E has been used to highlight different adverse event profiles at different dosages. Researchers can also search medical records for particular adverse effects, code the effects found and assess for drug associations. The linguistic capabilities of I2E are critical in providing a distinction between new effects, a history of an Once you see what I2E can do, you won't want to go back to wading through irrelevant documents. Associate Director, Safety Assessment, Top-10 Global Pharmaceutical Company effect, the lack of an effect, or the lack of a history of an effect.

8 To fully evaluate the unique and compelling benefits that I2E can bring to your organization, please contact your local Linguamatics representative or us at About Linguamatics Linguamatics is the world leader in deploying innovative natural language processing (NLP)-based text mining for high-value knowledge discovery and decision support. Linguamatics I2E is used by top commercial, academic and government organizations, including 17 of the top 20 global pharmaceutical companies, the US Food and Drug Administration (FDA) and leading US healthcare providers. I2E can be used to mine a wide variety of text resources, such as scientific literature, patents, Electronic Health Records (EHRs), clinical trials data, news feeds, social media and proprietary content. Linguamatics is committed to excellence in healthcare informatics and is a corporate member of AMIA and HIMSS. The company operates globally, with headquarters in Cambridge, UK, and a U.S. office in Westborough, MA. Linguamatics is a winner of the Queen s Award for Enterprise 2014 for International Trade. For further information, visit About I2E I2E is an agile, scalable, high performance text mining system that facilitates discovery and knowledge synthesis from unstructured text in large document collections. I2E has a proven track record in delivering best of breed text mining capabilities across a broad range of application areas. Its agile nature allows tuning of query strategies to deliver the precision and recall needed for specific tasks, but at enterprise scale. There is a choice of ways in which you can connect to I2E s unique capabilities: either by deploying I2E Enterprise in-house, or via I2E OnDemand, our Software-as-a-Service (SaaS) version of I2E. For more information, visit or For more information or a demonstration, please call us on enquiries@linguamatics.com Linguamatics 324 Cambridge Science Park Milton Road Cambridge CB4 0WG UK Tel: +44 (0) Linguamatics 1900 West Park Drive Suite 280 Westborough MA USA Tel: Linguamatics Ltd. The Linguamatics logo is a trademark of Linguamatics Ltd. All rights reserved. All other trademarks mentioned in this document are the property of their respective owners.