AI-Driven Analytics for mRNA Vaccine R&D Acceleration
R&D operations generated large volumes of complex, siloed data across discovery, preclinical, and process development stages. Scientists struggled to access and analyze this data in real time, leading to delays, dependency on technical teams, and limited ability to derive timely insights
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Research workflows are no longer constrained—they are accelerated, data-driven, and efficient
The Challenge
Siloed R&D Data and Limited Real-Time Accessibility for Researchers
R&D data was distributed across multiple systems and databases, making it difficult for scientists to access and analyze information in real time. Heavy reliance on technical teams for data retrieval, combined with complex data structures, led to delays in analysis, reduced productivity, and limited ability to generate timely, actionable insights
Solution
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Deployed DataBot LLM securely on Azure within the client’s VPC
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Enabled natural language querying for intuitive data access
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Integrated data across 90+ PostgreSQL tables for unified analytics
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Implemented explainable AI with automated SQL generation and transparency
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Provided training for researchers to independently navigate and use the platform
Impact
Improved Data Accessibility Driving Speed, Accuracy, and Innovation
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Simplified access to complex R&D data across functions
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Reduced reliance on data analysts and technical teams
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Improved accuracy by minimizing manual data handling errors
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Enabled scientists to focus on insights, innovation, and faster research outcomes
Measurable Impact
95%
reduction in data analysis time
70–80%
reduction in dependency on data teams
2–3x
increase in researcher productivity