Rapid unification of clinical studies
Convert thousands of completed clinical trials into a single format, whether its Real World Evidence (RWE) data or Study Data Tabulation Model (SDTM) for Clinical Data Interchange Standards Consortium (CDISC). This data lake provides scientists and clinicians with highly curated data for various analytic needs and can then be combined with other sources such as biomarker and translational data sources.
Automated schema conversion
Tamr’s machine learning provides automation to reduce the time and cost of study conversion, and the user interface provides subject matter experts (SMEs) full oversight to maintain the expected high level of quality. Local terminologies contain synonyms and misspelled terms that are difficult and costly to aggregate & align. Using SME feedback, Tamr can efficiently review matches to taxonomies such as Medical Dictionary for Regulatory Activities (MedDRA) and the SDTM.
Quickly create a complete view of your supplier base. Tamr enables you to combine all of the supplier data you have throughout your enterprise, enabling a holistic approach to supplier relationship management. Gain the insight you need to design your supply base, optimize pricing and terms, and track your performance by having the data you need accessible.
Biting The Data Management Bullet At GlaxoSmithKline
“There comes a time in the life of almost every large organization when it has to admit that it doesn’t have the data environment it needs to succeed.” That’s how Tom Davenport and Randy Bean’s article in Forbes begins. Their story describes how GSK’s Chief Data Officer has led an effort to transform the company’s data management capabilities to accelerate its digital transformation. Tamr’s machine learning-based enterprise data unification platform has been a core component of GSK’s initiative.
“GSK R&D’s data environment is something that one often hears about in startups, but is rarely found in large enterprises.” – Tom Davenport – Author, Speaker, Advisor
How Amgen Built a Translational Data Platform at Scale
Learn about Amgen’s journey to build a translational data platform at scale through innovation of its data management practices – including the use of human-guided machine learning to automate the incorporation of hundreds of legacy datasets. By reducing the traditional roadblocks to integrating data (cost, complexity, and time), Amgen has been able to exponentially speed up the time it takes to unify data sources across its organization – ultimately leading to expedited R&D decision making and rapid new hypothesis generation.
“Tamr’s machine learning capabilities were the key reason we selected this software to integrate different sources into a bridge based datahub.” – Jackie Fu, Specialist IS Business System Analyst, Amgen