R&D
Real World Evidence Studies
Use machine learning in pharmaceutical development for prospective evaluations and clinical trial data.
Challenge
- Centralization of unstructured data was an expensive undertaking that resulted in a lag between data collection and analysis.
- Excel was the “gold” standard to collate, clean, analyze and report.
- Security, confidentiality and privacy of data, sources and methods created regulatory and reputational risk.
Solution
- Devron collaborated with rare disease data science/operations team to deploy/train models at the point of data generation across 5 research sights in 2 countries.
- Devron’s encrypted model artifacts and repeated improvements in model accuracy accelerate analytics across all research sites.
- Increases in speed and accuracy helped unlock predictive insights while curating portfolio ops efficiencies.
Outcomes
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Develop Better Treatments for Diseases
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Improve Patient Experiences & Outcomes
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More Data for Analysis
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Reduce Time to Insight
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