Global Pharmaceuticals Manufacturer Reclaims 2PB+ of Primary NAS Capacity with Komprise Intelligent Tiering
Biotechnology company with more than 10,000 employees, needed to address 20%+ YOY growth in unstructured data across multiple sites, storage platforms, and file types. Research data was expanding quickly, putting pressure on primary NAS capacity, hardware budgets, and IT operations.
Without a centralized way to classify and analyze growing file data across environments, it was difficult to understand what data existed, who owned it, how old it was, and what should be moved, deleted, confined, or retained. The IT team needed to:
- Reduce pressure to purchase additional hardware
- Identify duplicate, orphaned, stale, and unnecessary files consuming high value NAS capacity
- Support multiple storage environments across on premises and cloud
- Improve visibility into research data, the largest and fastest growing data set
- Strengthen governance for sensitive data and emerging compliance needs
- Provide researchers a single way to search and find across locations and clouds
Read this case study to learn how Komprise gave IT a scalable way to search, classify, and act on billions of files across departments and storage silos.
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FAQs
Why is unstructured data management such a persistent challenge for pharmaceutical, life sciences, and genomics organizations?
Pharmaceutical, life sciences, and genomics organizations produce some of the most data-intensive workloads in any industry. Research files, genomic sequences, clinical imaging, regulatory documentation, and lab instrument output accumulate rapidly, and almost none of it is structured in rows and columns. It lives in file systems and object stores, spread across NAS arrays, cloud buckets, and multi-site environments.
The deeper problem is that most of this data is never classified, never tiered to appropriate storage, and never made available to the AI pipelines that depend on it. That gap drives up primary storage costs, creates compliance exposure around sensitive clinical and patient data, and leaves AI pipelines waiting for the clean, curated datasets they need to produce trustworthy results. Without a centralized way to analyze and act on unstructured data at scale, the data that should be a competitive advantage becomes a cost center and a liability.
According to IDC, 90% of the data generated by organizations in 2022 was unstructured — a volume that is expected to grow 28% year over year. The challenge is not just scale. IDC also found that 55% of organizations report that less than half of their unstructured data is shared among employees or systems, leaving the vast majority of research and operational data dark and inaccessible.
Source: IDC White Paper, sponsored by Box, “Untapped Value: What Every Executive Needs to Know About Unstructured Data,” August 2023, Doc #US51128223
What unstructured data management use cases matter most in pharmaceutical, life sciences, and genomics?
Several use cases recur across pharmaceutical, life sciences, and genomics IT organizations:
- Primary NAS capacity relief: Research data grows faster than storage budgets. Identifying and tiering cold, stale, or duplicate files off primary NAS to lower-cost object storage, without disrupting researcher access, is often the first priority.
- Research data visibility: With data scattered across departments, sites, and storage systems, IT teams often lack a unified view of what exists, who owns it, and what policies apply. A Global Metadatabase that indexes file metadata across all environments enables search, classification, and action without moving data first.
- Sensitive data governance: Clinical trial data, patient records, and proprietary compound research require detection and control. Automated sensitive data detection lets teams identify and act on regulated data before it becomes a compliance problem.
- AI data preparation: Life sciences AI and machine learning pipelines need curated, governed datasets at scale. Smart Data Workflows can automatically classify, tag, and route research data to AI pipelines with full audit trails, without requiring researchers to change how they work.
A typical Phase III clinical trial alone generates more than 3.5 million data points – three times more than a decade ago. Multiply that across an organization’s full research portfolio, and the pressure on storage infrastructure and data governance becomes clear.
Source: WCG Clinical, “Clinical Trial Trends and Insights 2024,” citing Tufts Center for the Study of Drug Development
How did this pharmaceutical manufacturer reclaim 2PB+ of NAS capacity without disrupting researchers?
The core challenge was not just storage cost. The IT team had no centralized way to understand what data existed across departments and sites, how old it was, who owned it, or what should be tiered, deleted, or retained. Without that foundation, any storage initiative risked disrupting active research or missing the files that were actually consuming capacity.
Komprise gave the team a non-disruptive way to index and classify billions of files across existing NAS environments without agents or infrastructure changes. Once the team could see the data, including file ages, owners, types, and access patterns, they could apply tiering policies with confidence. Transparent Move Technology tiered cold files to lower-cost storage while preserving native access paths, so researchers continued working without noticing any change.
The result was 2PB+ of primary NAS capacity reclaimed, with governance and sensitive data controls applied across the environment at the same time. The manufacturer had been managing more than 10,000 employees and 20%+ year-over-year unstructured data growth across multiple sites and storage platforms before deploying Komprise.
Read: Pharmaceutical Manufacturer Reclaims 2PB+ of Primary NAS Capacity with Komprise Intelligent Tiering
What makes Komprise the right choice for pharmaceutical, life sciences, and genomics unstructured data management?
Most storage and data management tools are built for structured data, require disruptive migrations, or solve only one part of the problem. Komprise is purpose-built for unstructured data at petabyte scale, with an architecture designed for the complexity of multi-site, multi-vendor research environments.
A few differentiators stand out for life sciences customers:
- Non-disruptive by design: Transparent Move Technology tiers data without breaking file paths or changing how researchers, instruments, or applications access their files. There is no rip-and-replace, no retraining, and no change management burden.
- Storage agnostic: Komprise works across NAS, object storage, and cloud, from NetApp, Everpure, Dell and HPE to AWS, Azure, and Google Cloud, so organizations are not locked into a single vendor’s storage ecosystem.
- AI-ready from day one: Smart Data Workflows and KAPPA data services enrich, classify, and route unstructured data to AI pipelines automatically, with governance and audit trails built in. Life sciences AI teams get the curated, governed datasets they need without manual data prep.
- Built for compliance: Automated sensitive data detection and Deep Analytics let teams find, flag, and act on regulated data across petabytes, supporting HIPAA, GxP, and broader data governance requirements.
The urgency is real. The AI in life sciences market is projected to grow from $9.8 billion in 2024 to $33.5 billion by 2029, a CAGR of 27.9%. Organizations that cannot govern and deliver their unstructured research data at scale will struggle to compete as AI becomes central to drug discovery and development.
Source: BCC Research, “Artificial Intelligence in Life Sciences Market,” September 2024