Life Sciences Data Engineering Case Studies
See how DataDrill has helped life sciences teams unify fragmented data, modernize cloud infrastructure, automate manual work, and build production-ready AI and software.
Global CRO Market Access Insights Platform Development
Life Sciences / CRO
Challenge
A Global CRO's market access platform relied on manual processes, fragmented data from 40+ countries, and limited real-time capabilities, causing delays in strategic analyses and high operational costs.
Solution
DataDrill designed and implemented a centralized platform with automated data ingestion, real-time analytics, AI-powered features including domain-specific NLP chatbot, advanced search with flexible filters, and interactive modules for cost comparison and scenario analysis.
Technologies Used
M&A to Global CRO: Cloud Migration and Modernization
Life Sciences / Market Access
Challenge
Following a Global CRO's acquisition of M&A, they needed to migrate and modernize a fragmented AWS-based environment (100+ Lambda functions, 2.5TB data, 7 PostgreSQL databases) into their Azure ecosystem without disrupting operations.
Solution
DataDrill executed seamless migration of 2.5TB of data, containerized 100+ backend services, rebuilt CI/CD pipelines, and deployed fully cloud-native infrastructure using Azure Kubernetes Service, Terraform, and GitLab pipelines—all with zero major downtime.
Technologies Used
M&A Acquisition to Global CRO: Infrastructure Modernization
Life Sciences / Market Access
Challenge
Following a Global CRO's acquisition of a regional life sciences company, infrastructure was scattered across AWS, OVH Cloud, and DigitalOcean with no centralized architecture, manual deployments, limited DevOps capacity, and strict corporate security procedures.
Solution
DataDrill consolidated all infrastructure to Microsoft Azure, implemented Terraform-based Infrastructure as Code, built GitLab CI/CD pipelines from scratch, rebuilt legacy systems, and established dev/staging/production environments with proper security controls.
Technologies Used
AI Chatbot for SQL Querying: GenAI and Data Automation
Life Sciences / Pharma Data
Challenge
A Global CRO's existing chatbot was slow, expensive, and limited—built on a narrow 20-column dataset with poor coverage, limited context, and high cost per query. Users needed faster access to 250+ fields across HTA, pricing, reimbursement, regulatory, and clinical trial data.
Solution
Over 21 weeks, DataDrill designed and deployed a domain-specific SQL agent using LangGraph-based orchestration capable of interpreting natural language questions and dynamically generating accurate SQL queries across 250+ curated fields with full observability via LangSmith.
Technologies Used
Pharmaceutical Pricing Calculator Development
Life Sciences / Pharma Data
Challenge
A Global CRO's market access team relied on slow, error-prone Excel models for treatment cost calculations that only one expert could run. They needed to automate pricing analysis across US, Canada, and EU markets with complex FDA dosage schedules.
Solution
DataDrill delivered a full-stack pricing calculator with web dashboard, backend services, AI agent for PDF parsing, and 50 independent crawlers to collect prices. The platform supports configurable scenarios with/without wastage, multi-package combinations, and exports to multiple formats.
Technologies Used
DataLake Analytics Platform Modernization
Enterprise Data Infrastructure / Analytics Platform
Challenge
A mid-sized enterprise operating across multiple departments struggled with fragmented data infrastructure. Data was spread across disconnected systems including ERP, HR, CRM, SharePoint, and document-based sources. The organization relied heavily on manual data preparation and had no unified reporting environment, making it difficult to generate timely and reliable business insights.
Solution
DataDrill designed and implemented a centralized analytics platform built on Microsoft Fabric. The architecture introduced automated data ingestion pipelines, structured transformation layers, and AI-enabled data access. Data from multiple systems was unified into a governed analytics environment optimized for reporting and decision-making. A key innovation was the development of a RAG-based AI assistant capable of answering natural language questions using structured and unstructured internal data. This enabled business teams to retrieve insights without relying on technical teams.
Technologies Used
Typical ROI Timeline
Most DataDrill projects deliver measurable ROI within 12 months through reduced operational costs, faster decision-making, and improved system performance. By combining deep life sciences domain knowledge with strong data engineering and software expertise, we help organizations move from fragmented systems to scalable, reliable solutions that deliver long-term operational and strategic value.
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