case-study

Case Study: Innovative Biotech Achieves Industrial Scale with Sapio LIMS and ELN

Executive Summary

A development-stage biotechnology company focused on personalized cell therapies partnered with Sapio Sciences to manage its exponential data growth and prepare for future scalability. By adopting the Sapio Platform, which incorporates Sapio LIMS and Sapio ELN into a modern, unified informatics platform, the biotech is improving sample tracking, automating dynamic experimental workflows, and integrating diverse data types.

This multi-phase project aims to create a comprehensive, searchable data repository, ensuring readiness for “what comes after terabytes” in their cutting-edge R&D.

The Customer: A Development-Stage Biotechnology Company

Company Overview

This development-stage biotechnology company focused on personalized cell therapies. It combines stem cell biology with the latest artificial intelligence and genomic approaches to investigate patient-specific, restorative treatments.

Background

In 2023, the biotech recognized that its unique R&D capabilities were producing exponential amounts of data. By 2025, it expects to generate about 500 Gigabytes (Gb) of data for each new patient as it quickly accelerates from 250 to 400 Terabytes (Tb) of total data storage. This led to the question, “What comes after Terabytes?”

The Challenge: Managing Exponential Data Growth and Diverse Data Types

As it progresses from startup to mid-size clinical biotech, data types are expanding to include whole genome sequencing, RNA and scRNA sequencing, SNP arrays, multi-omics, histology and wet lab datasets, microscopy, and importation of public datasets.

The primary challenge for the biotech was managing the exponential growth of diverse data types generated by its unique R&D capabilities, anticipating a rapid acceleration from 250 to 400 Terabytes of total data storage by 2025. This necessitated a solution for “what comes after terabytes.”

Specific challenges included:

• Handling massive data volumes (e.g., 500 Gb per new patient by 2025).
• Integrating expanding data types: whole genome sequencing, RNA and scRNA sequencing, SNP arrays, multi-omics, histology and wet lab datasets, microscopy, and public datasets.
• Gaps in the present sample management system.
• Need for a tangible, concise list of key components in a LIMS, including sample and project management, an easy-to-learn and use scientific data repository, data integration from diverse sources (legacy and newly generated), and security for trade secrets.

The Solution: Sapio LIMS & Sapio ELN

Why Sapio Sciences Was Chosen

The project lead crowdsourced input from all stakeholders to understand the gaps in its present sample management system through an effective, albeit low-tech, method of color-coded post-it notes on flip chart pages.

Armed with results of the analysis, the team defined a tangible, concise list of key components they wanted in a LIMS, highlighted by sample and project management, an easy-to-learn-and-use scientific data repository, data integration from diverse sources (legacy and newly generated), and security to keep trade secrets safe.

From this list, the team developed a quantitative assessment scorecard and used it to evaluate the three top competitors in the field. Sapio Sciences outscored the other two by large margins, 50% and 100%, respectively.

Beyond the numbers, the team was impressed that Sapio integrated the laboratory information management system (LIMS), electronic laboratory notebook (ELN), and scientific data management system (SDMS) into a single, unified platform. According to the subject matter expert, “As an autologous cell therapy lab, we are very niche focused, so another important factor was the ease with which our subject matter experts could optimize the system for specific R&D projects.”

Implementation Overview

The biotech adopted the Sapio Platform in 2023 and embarked on a 3-phase integration project to manage its exponential data growth, with the initial phase focused on configuring and automating dynamic experimental workflows, tracking all sample information, and fully integrating data with ELNs.

Key Features

• Sapio Lab Informatics Platform: Incorporating Sapio LIMS and Sapio ELN into a single, configurable system.
• Dynamic Experimental Workflows: Configurable and automatable.
• Sample Tracking: Comprehensive tracking of all sample information.
• Data Integration: From diverse sources, including legacy and newly generated data.
• Scannable Barcodes: For unique identification and reduced human error.
• Hierarchical Cell Line Mapping: For systematic organization.

The Results: Improved Sample Tracking and Efficient Data Management

With Phase 1 implementation completed, the biotech has been able to identify specific sample management improvements. Key outcomes of the Sapio Platform implementation include:

• Improved Sample Management and Workflow Efficiency: Previously, experiments required manual identification and deletion of cells in lot tracking sheets and physical documentation. Now, cells are easily searched in the database, selected for experiments, and automatically removed from storage, and cell line information is automatically populated. Similarly, samples shipped to certified test labs, which were previously tracked manually, are now automatically tracked.

• Enhanced Data Recording and Organization: Before implementation, a great deal of information was entered manually into worksheets and lab notebooks. This was time-consuming, increased the potential for manual data recording errors, and provided no systematic organization of sample information and data. Now, tracking and recording is quick and efficient—unique scannable barcodes reduce human error, data output is automatically linked to samples, and cell lines are mapped hierarchically.

Customer Quotes

“As an autologous cell therapy lab, we are very niche focused, so another important factor was the ease with which our subject matter experts could optimize the system for specific R&D projects.” – Project Lead

“Our terabytes of data will be connected in Sapio, and our scientists will be able to quickly and easily drill down from an experimental result to the raw data for a more complete picture of what happened and why.” – Project Lead

Lessons for Biotech R&D

This biotech’s journey offers critical insights for other organizations navigating rapid growth and complex data challenges:

• Proactive Data Strategy for Exponential Growth: Plan for future data scale (beyond terabytes) by implementing unified informatics platforms that can handle diverse and ever-growing data types.
• Embrace Unified Lab Informatics: Prioritize integrated LIMS, ELN, and SDMS solutions to centralize data, improve searchability, and enhance end-to-end visibility across R&D workflows.
• Invest in Flexible and Adaptable Systems: Select platforms that allow for easy customization and optimization by subject matter experts, ensuring the system can evolve with specific R&D project needs and future technologies.
• Champion Iterative Digital Transformation: Adopt a phased implementation approach to manage complex digital shifts, allowing for continuous refinement, stakeholder alignment, and incremental demonstration of value.
• Optimize Workflows for Efficiency and Accuracy: Leverage automated tracking, barcode integration, and automated data population to reduce manual errors, streamline experimental processes, and improve data integrity.

• Ensure Long-Term Knowledge Retention: Implement systems that provide robust archival data support, enabling scientists to quickly access historical insights for future projects and discoveries.

Next Steps

The biotech’s future digital transformation includes:

• Phase 2: Will enable the translational science department to record and track histology and data types and link them back to the original samples. This phase is crucial for expanding the scope of data integration to support more complex research.
• Phase 3: Will involve uploading legacy data and integrating all sample data, historical assay data, and cell lines. This final phase aims to create a comprehensive, unified data repository, ensuring long-term knowledge retention and accessibility for future scientific inquiries.

Conclusion

This development-stage biotechnology company has successfully embarked on a multi-phase digital transformation with Sapio Sciences, addressing the critical challenge of exponential data growth in personalized cell therapies. By implementing the unified Sapio Platform, they have significantly improved sample tracking and data integration in Phase 1, laying a robust foundation for future data management, historical insights, and continued innovation in their R&D pipeline, ensuring they are prepared for “what comes after terabytes.”

Download the Case Study

FAQ

Q: What problem did the biotech face?
A: Managing 250–400 TB of rapidly growing, multi-modal R&D data across genomics and microscopy.

Q: Why was Sapio selected?
A: It unified LIMS, ELN, and SDMS, and outperformed competitors in configurability and ease of optimization.

Q: What were the Phase 1 results?
A: Improved sample tracking, automated workflows, and integrated historical data with barcode accuracy.

Q: What’s next for the platform?
A: Histology data integration, legacy assay data upload, and a unified repository for knowledge retention.