Data manager Ratna Jyothi Kommaraju's automation frameworks to handle 3 million biosamples and cut delays by 75% – a benchmark India’s clinical trial industry now looks to follow.
India's clinical trials market was valued at USD 1.42 billion in 2024, accounting for 8.3% of the global activity. Simplified regulatory changes have already reduced approval times by 30-40%, making it an attractive venue for international research. This fast-growth rate, however, has created a serious problem: pharmaceutical firms are storing millions of biological samples in various liquid nitrogen freezers, often with incomplete historical documentation. They are not losing the samples or the liquid nitrogen freezers. They are losing time. When research teams need to identify a specific specimen, they may spend 8-12 months just identifying and shipping samples between various facilities.
Scientists at Sanofi were experiencing these delays when Ratna Jyothi Kommaraju joined as Data Manager through Vivid Soft Global Inc. She and her team streamlined sample processing which cut down the time to 2-3 weeks. At PAREXEL, Ms. Kommaraju automated CTMS (Clinical Trial Management Systems) applications used extensively by different pharmaceutical companies like Novartis, Pfizer, and Boehringer Ingelheim. Ms. Kommaraju describes in more detail her methods for removing bottlenecks, automation methodologies that save months of manual work, and actionable steps that other organizations can take to accelerate research faster.
The Million-Sample Problem at Sanofi
The laboratory freezers at Sanofi held millions of biological samples in liquid nitrogen freezers for years, some dating back decades, samples collected from medical research studies that could hold insight for breakthrough treatment. However, when researchers were searching for specific samples for a critical study about therapeutic potential related to cancer, as well as drugs for life-threatening illnesses, human pathologists faced the frustration of dealing with incomplete – or worse, inaccurate – paperwork created years ago.
"Projects would just sit there while teams wasted months scrambling to figure out what samples they even had," Ms. Kommaraju said. "You’d have researchers calling back and forth between sites, waiting for approvals, getting frustrated because they couldn’t even make progress."
Ms. Kommaraju collaborated with SMEs (Subject Matter Experts) from different departments to build the Benchling application with metadata fields tailored to each specific schema. Working together, they established a framework for proper storage of sample information in Benchling. However, registering older samples hit a major roadblock – Benchling's native template could only handle 100 samples at a time. Ms. Kommaraju and her team developed an innovative solution: a Data Collection Template for each schema that could register anywhere from 1 to 100,000 samples simultaneously. Her breakthrough eliminated the bottleneck that had plagued the system for years.
A template was one thing. Ms. Kommaraju would go on to construct dashboards that flagged missing information before it turned into compliance problems. Companies could retain compliance, instead of being rushed to be compliant, only when inspection was coming.
"You need systems that scale for massive volumes." she says, "But it doesn't matter if you can't trust your data or pass regulatory inspections."
With Sanofi, shipping of samples went from 8-12 months, to 2-3 weeks. The research teams could get the specimens they needed without having to plan around delays.
Tackling Similar Problems at PAREXEL
PAREXEL International, world's largest clinical research organizations and serving more than 1,000 pharmaceutical clients. Managing clinical trials for world class pharmaceutical companies like Novartis, Pfizer, and Boehringer Ingelheim, but there was often inconsistent data reporting limiting the projects.
At PAREXEL Ms. Kommaraju tackled two major challenges. First, during each release cycle, teams had to manually test all features across five different CTMS applications to ensure they functioned correctly after version upgrades, a process that consumed enormous manpower. Ms. Kommaraju automated the Reference application, which served as master data for the entire CTMS, dramatically reducing testing time and resource requirements.
Second, she led the standardization and creation of 150 clinical study reports specifically for Boehringer Ingelheim, coordinating with stakeholders and guiding a validation team to deliver results under tight deadlines. These reports became a foundation for capturing essential trial data and supporting compliance across multiple global studies.
Her automation approach was a significant improvement in terms of using manual testing and shortening time-frame to release products. The validation approach ensured regulatory requirements were still being achieved without slowing their processes.
The Complex Migration at Calyx
At Calyx, we faced a different challenge of moving 54 different integrations to the Azure cloud platform in which we had to maintain data integrity while managing the differences between each of the systems (EDC, SIMS, Site Intelligence, Veeva, etc.).
"Everyone told us that we couldn't do it without losing some data," Ms. Kommaraju explains. "So I built a systematic approach to test one interface at a time before we tie them together. The trick was to realize that each system spoke a different language."
Ms. Kommaraju was successful in this mammoth technical migration without any data loss which allowed our pharmaceutical clients to continue the research without interruptions during the transition.
Building a Repeatable System
No matter how successful you are at a company, it doesn't mean a thing unless it can be reproduced at another company. Ms. Kommaraju built methods that worked no matter what the size of the company or structure of the company.
As a Certified Scrum Product Owner (CSPO) and Certified ScrumMaster (CSM) through Scrum Alliance, she brought in Agile methodologies that improved how teams executed on projects. Holding the Project Management Professional (PMP) certification from the Project Management Institute, a demanding credential requiring a strenuous exam, underscores her profound expertise in managing complex project execution. Additionally, her ISTQB foundation level certification validates her expertise in software testing methodologies.
Recognition for her innovative work came in 2025 when she received the "Best Data Analyst" award from BrainTech Awards, acknowledging her exceptional contributions to data management and automation in pharmaceutical research.
Her automation approaches provided a huge improvement over manual testing and enabled product releases to happen more quickly. The validation approaches ensured that regulatory requirements were still met without slowing processes down.
"Good data management is more than just technology," Ms. Kommaraju puts it. "In order to ensure success, you also must consider the overall business processes, regulations, and how people actually work."
The Future of Pharma Data
Ms. Kommaraju intends to take advantage of artificial intelligence and machine learning to improve clinical trials even more. She is getting an MBA to develop the strategic thinking for the management of digital system projects at scale.
She plans on starting a consultancy to bring companies up to date with their clinical data and compliance systems in the pharmaceutical and biotech sectors.
"Data management is changing rapidly," she says. "Companies that have learned to use smart automation and manage people will outperform those that do not."
Ms. Kommaraju's experience offers solid insights for pharmaceutical companies with data management challenges. Her methods directly address relational problems with disconnected systems, human-in-the-loop processes, and compliance headaches. Companies implementing similar approaches are seeing drastic improvements in efficiency and readiness for regulations. Research is done faster, data integrity improves, and companies that used to have competitive advantages are losing out on potential competitive advantages when compared to new companies.
India's clinical trial market arguably needs roughly these types of improvements to keep growing and compete globally. The better the data management strategies are for each subsequent process, the better industry firms will have everything built on a foundation.
