Tamr CDISC Conversion Solution
Tamr’s CDISC Conversion Solution tackles data challenges with a powerful data harmonization process, driven by human-guided machine learning that can replace traditional in-house tools prone to delays and errors.
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Tamr’s CDISC Conversion Solution tackles data challenges with a powerful data harmonization process, driven by human-guided machine learning that can replace traditional in-house tools prone to delays and errors.
In the United States, the FDA requires that every clinical trial or application to market a new drug or biologic be accompanied by clinical study data showing the safety and efficacy of the proposed product. Converting clinical data into the…
Tamr was approached by a multinational biopharmaceutical company to transform the process of preparing its clinical data for analytics. The organization wanted to analyze the trove of unmined clinical trial and biomarker data in order to more effectively guide translational…
Presenting A New Approach to Taming Biomedical Data Variety Tamr Field Engineer Timothy Danford, Ph.D., discusses how Data Variety — the natural, siloed nature of data as it’s created — is creating a bottleneck to biomedical data analytics. Rule-based, deterministic…
For most pharmaceutical companies, submitting clinical study data to the FDA is an expensive and time-consuming process. A study sponsor must collect data from different sources, extract it from proprietary file formats, transform it to conform to CDISC standards, organize…
Clinical Trial Data: Automated, Replicable CDISC Conversion Synopsis + IND and NDA programs necessitate recurrent submission of clinical trial data to regulatory agencies in specific formats. + Trial data is stored in a tangled web of standards, versions, and file…
Watch Now » For most pharmaceutical companies, submitting clinical study data to the FDA is an expensive and time-consuming process. A study sponsor must collect data from different sources, extract it from proprietary file formats, transform it to conform to…
An international pharmaceutical company has a massive problem: critical research data from thousands of scientists in labs spread across the globe is trapped in tens of thousands of spreadsheets. Associates need to quickly find critical data on compounds, assays and…