case-study

Case Study: Oxford BioMedica (OXB) Achieves Enterprise-Wide Lab Informatics Standardization with Sapio Sciences

Executive Summary

Oxford BioMedica (OXB), a leading innovation-led CDMO in cell and gene therapy, sought an enterprise-wide lab informatics platform to standardize data collection, storage, and retrieval across diverse experimental groups. By choosing Sapio Sciences, OXB has gained a truly integrated platform that unifies LIMS, ELN, and SDMS functionalities. 

This solution is enabling OXB to streamline workflows, ensure end-to-end data pipelines, and make data more accessible and valuable for its scientists, ultimately enhancing efficiency and supporting its mission in life-saving therapies.

An interview with Oxford BioMedica’s Prashant Vaidyanathan, Group Lead, Data Architecture, who describes their business and need for an enterprise-wide lab informatics platform, and why they chose Sapio Sciences. Watch the video below.

The Customer: Oxford BioMedica (OXB)

Company Overview

Oxford BioMedica (OXB), based in Oxford, UK, is an innovation-led CDMO (Contract Development and Manufacturing Organization) and a world leader in cell and gene therapy. OXB partners with large pharmaceutical companies to manufacture their products based on their platforms while also developing its own platforms. OXB’s expertise in cell and gene therapy stems from extensive time spent understanding and innovating its processes for both internal use and for customers.

OXB has partnered with Novartis to manufacture the Kymriah therapy, a life-saving cancer therapy for patients suffering from ALL and other types of leukemia. More recently, OXB was also involved in manufacturing the AstraZeneca vaccine.

Background

As a leading innovation-led CDMO, Oxford BioMedica generates significant data from diverse experiments and groups across its various departments. Prashant Vaidyanathan, Group Lead for Data Architecture at OXB, was tasked with ensuring this data was standardized, properly stored, easily retrievable, and accessible to all users, with the ultimate goal of extracting maximum value. This objective highlighted the critical need for an enterprise-wide lab informatics platform that could unify data management despite the varied methods of assay implementation, data collection, and analysis across different departments.

The Challenge: Unifying Data Across Diverse Departments and Workflows

OXB faced the significant challenge of finding a single, enterprise-wide lab informatics platform that could cater to the varied needs of all its departments. Each department implements systems, conducts assays, collects data, and analyzes data quite differently. A key difficulty was finding one platform that could tightly integrate core functionalities like LIMS and ELN, as scientists did not want to navigate separate systems for these closely tied components.

The Solution: Sapio Sciences’ Unified Informatics Platform

Why Sapio Sciences Was Chosen

OXB underwent a thorough evaluation process, including demos and workshops with Sapio. The decision was significantly influenced by positive recommendations from end-users already utilizing Sapio, which validated OXB’s initial beliefs about the platform.

The main reason for choosing Sapio was its nature as a “true platform” that integrates core functionalities. OXB’s approach is to have one platform that does it all. Sapio’s tight integration of LIMS and ELN was a major appreciation point, as these components are integral to a scientist’s daily lab work. OXB chose Sapio because it offered integrated core functionality with tightly integrated LIMS and ELN components, which are essential and closely tied for scientists. It also provided a comprehensive platform with ELN, LIMS, and SDMS modules, along with additional charting, search, and rules engines. Furthermore, it ensured end-to-end data pipelines, ensuring everything happens in one platform and one database, supporting seamless data flow.

Implementation Overview

OXB went through an evaluation process that included demos and workshops. A notable instance of Sapio’s capability was its ability to configure one of OXB’s most complex assays in a single day during evaluations, which was described as “amazing.” As OXB begins implementation, they plan to challenge Sapio further to maximize its capabilities.

Key Features

OXB is leveraging the following features and components within the Sapio platform:

• Integrated ELN, LIMS, and SDMS Modules: Providing core functionality within a single platform.
• Charting, Search, and Rules Engines: Additional features that will play a crucial role in end-to-end data pipelines.
• Protocol Templates: An ease-of-use functionality that will have a significant impact on standardizing diverse assays.
• No-Code/Low-Code Features: Useful for scientists to access and manage data, offering out-of-the-box functionality.
• Rules Engine: Provides advanced functionality that would typically require extensive custom coding.
• Internal Configuration Capability: The ability to configure the system internally is highly valued.
• Plugins, APIs, and Webhooks: Essential for bridging gaps in bespoke workflows, especially for instrument integration and custom data parsing.

The Results: Enhanced Efficiency and Data Utilization

While early in implementation, OXB anticipates significant results and benefits from the Sapio platform:

• Improved Efficiency and End-to-End Workflow Transformation: OXB expects to fundamentally change its operational approach, becoming more efficient and extracting maximum value from its data. The integrated platform ensures end-to-end data pipelines, with all processes occurring within a single platform and database. Voice-to-Text dictation is anticipated to simplify data entry for scientists in the lab, enabling real-time capture of thoughts and notes even when their hands are occupied. Additionally, protocol templates will significantly contribute to standardizing diverse assays, enhancing ease of use across the organization.
• Empowered Scientists, Adaptability, and Usable Data Structures: Sapio’s no-code/low-code features empower scientists with direct access to and management of data. The platform’s internal configuration capability, combined with the flexibility to bridge gaps using Python code, plugins, APIs, and webhooks, supports bespoke workflows and seamless instrument integration. Sapio’s demonstrated ability to quickly configure complex assays (e.g., in a day) highlights its rapid adaptability. Ultimately, Sapio has successfully created a usable interface that stores unstructured data in a structured format, addressing a common and critical challenge for data architects.

Customer Quotes

“When you have an integrated platform like Sapio, there is an opportunity to really change the way you work, make yourselves more efficient, and get the most out of your data.” – Prashant Vaidyanathan, Group Lead, Data Architecture, Oxford BioMedica

“I think the main reason why we chose Sapio is because it is true to its name; it is actually a platform.” – Prashant Vaidyanathan, Group Lead, Data Architecture, Oxford BioMedica

“We gave a pretty complex assay and said, ‘This is one of our most complex assays,’ and Sapio got it configured in a day, which is amazing.” – Prashant Vaidyanathan, Group Lead, Data Architecture, Oxford BioMedica

Lessons for Cell and Gene Therapy CDMOs

Prashant Vaidyanathan’s insights offer critical lessons for other organizations in cell and gene therapy, particularly CDMOs, seeking to optimize their lab informatics:

• Prioritize a Truly Unified Platform: Seek a single platform that integrates core LIMS, ELN, and SDMS functionalities, as these components are intrinsically linked in lab operations. Avoid disparate systems that complicate workflows.
• Demand Configurability and Flexibility: Choose a platform that can cater to the varied needs of all departments, allowing for customization of assays, data collection, and analysis methods without requiring complex coding. Low-code/no-code features are highly beneficial.
• Focus on End-User Usability: The most challenging aspect is creating a usable interface that simplifies data entry and real-time capture for scientists in the lab (e.g., voice-to-text dictation), making complex processes as simple as possible.
• Leverage Advanced Integration Capabilities: Ensure the platform offers robust APIs, plugins, and webhooks to bridge gaps in bespoke workflows, integrate instruments, and enable custom data parsing, especially for complex and unique lab processes.
• Seek a Responsive and Collaborative Vendor: Partner with a vendor that demonstrates responsiveness to challenges and willingness to configure complex assays quickly, indicating a strong commitment to customer success and continuous improvement.
• Standardize Workflows with Templates: Utilize protocol templates to standardize diverse assays, improving ease of use and consistency across the organization.

Next Steps

OXB is evolving the way they handle their workflows, recognizing the opportunity that an integrated platform presents to change how they work, become more efficient, and get the most out of their data. 

Conclusion

Oxford BioMedica’s adoption of the Sapio unified informatics platform marks a strategic move to standardize and optimize its enterprise-wide lab operations. By leveraging Sapio’s integrated LIMS, ELN, and SDMS, OXB is overcoming the challenge of disparate departmental needs, streamlining data management, and enhancing efficiency. This partnership positions OXB to fully realize the value of its vast data, supporting its role as a world leader in cell and gene therapy and its mission to deliver life-saving products.

FAQ

Q: Why did Oxford BioMedica choose Sapio?
A: To unify ELN, LIMS, and SDMS capabilities into a single, integrated platform that supports end-to-end data pipelines across scientific departments.

Q: What benefits did the Sapio platform deliver?
A: Streamlined workflows, improved data accessibility, rapid assay configuration, and enhanced support for scientists managing complex datasets.

Q: What makes the Sapio platform unique for OXB?
A: Its seamless integration of core informatics modules, no-code configurability, real-time search, voice-to-text lab entry, and instrument connectivity via APIs and plugins.Q: What were the early implementation outcomes?
A: Rapid system configuration for complex assays, standardized protocol templates, and an adaptable architecture for scalable, compliant lab informatics.

Interview Transcript

Can you introduce yourself and tell us more about your role?

I’m Prashant Vaidyanathan. I work at Oxford BioMedica, which is in Oxford, UK. So I work as the Group Lead for Data Architecture. Primarily, I’m basically the data architect for OXB.

So my main role is to make sure that, you know, all the data that’s collected—all the data that comes out of different experiments from different groups—they’re standardized. We have a way to store them, retrieve them, make sure that all the users can have access to the data the way they want to, and also make sure that we can get value out of that data as well. So that’s my primary objective. That’s my primary goal.

Can you describe what Oxford Biomedica does?

So a lot of folks might have heard about OXB in the context of them being a leading cell and gene therapy company. But I think the best way to describe OXB is as an innovation-led CDMO.

So we partner with a lot of big companies—with a lot of big pharma as well—to manufacture their products, and to manufacture the products based on the platforms that they have. At the same time, we have our own platforms.

And I think what really makes OXB a world leader in this is the cell and gene therapy part, because we’ve spent a lot of time understanding the process, and we’ve done a lot of innovation there—about how we improve our process in general, and how we can improve it for our customers as well.

Can you give us some examples of OXB’s work?

We’ve partnered with Novartis to manufacture the Kymriah therapy, which is a life-saving cancer therapy that helps with patients who are suffering from ALL and other types of leukemia.

More recently, we were also involved in manufacturing the AstraZeneca vaccine as well.

Why did you choose Sapio Sciences and what do you find most valuable in the Sapio LIMS?

So we’ve gone through this process of evaluating Sapio. We’ve seen Sapio in demos and workshops.

But I think it was really great to see end users who have been using Sapio and the growing recommendation that they’ve been giving about Sapio as well.

So the interesting thing is, I didn’t learn anything alarming or anything negative per se—it was kind of validation about what we believed Sapio as a platform to be.

That’s absolutely amazing, and that’s really important.

Typically, there are many different approaches about how you want to digitize your data, and I think one of the more challenging and complex ones is to have one platform that caters to the needs of all your departments.

Because every department is pretty varied in how they actually implement the system—how they conduct their assays, the way they collect their data, and the way they analyze their data—it’s quite different.

It’s a big challenge to find one platform that can cater to all those needs.

So first, we actually spent a lot of time evaluating a lot of the platforms in the market. And I think the main reason why we chose Sapio is because it is true to its name—it is actually a platform.

It integrates this core functionality. Because if I’m a scientist, at the end of the day, if I go to the lab, the LIMS and the ELN components are pretty much tied in—they’re an integral part.

I don’t necessarily want to go to a separate system to do my LIMS aspect and then have a separate system that does the ELN, because they are tied so closely together.

And I think that’s one of the main things that we really saw in Sapio—that we really appreciated—about how tightly integrated those two core functionalities are.

In general, we have this approach where we want to have one platform that does all of it, and that’s one of the main reasons why we chose Sapio—because we’re getting the ELN and LIMS modules, we’re getting the SDMS modules as well, and the other additional charting and search and rules engines and those really cool features.

And I think that’s going to play a huge, huge role in making sure that our data pipelines are, in fact, end-to-end—to make sure that everything happens in one platform, in one database.

So that’s one of the main reasons why we chose Sapio as well.

What innovations in the Sapio LIMS are the most applicable in your organization’s work?

I think it’s a bit early to tell, but if I had to guess, I think one thing that’s going to be really interesting—if it actually works—is the voice-to-text dictation.

There are a lot of caveats here. We’re really curious to see how Sapio handles, like, let’s say, a lab that has 10 or 20 people who are all talking.

But I think it’s going to have a huge impact.

At the end of the day, I’m a data guy—I work out of a laptop. It’s very easy for me to look at a template and say, “Oh, it’s so easy to enter data.”

But it’s very different for the scientists who are actually in the lab—they’re wearing gloves, they have instruments, they’ve got their hands full—literally, they’ve got their hands full.

And for them to try to enter data as soon as possible, as much as in real time as possible—that’s a challenge.

So for me, it’s my job to make sure that we make that process as simple as possible for them.

And I think the voice-to-text dictation is going to help a lot with that, because I can imagine where, if they’re actually conducting an assay and they have some thoughts in their heads that they want to note down, they can just say, “Okay, create a new text field,” and then they start talking about their thoughts.

And Sapio, I think, will be really, really impressive.

Another part was the protocol templates. This is more from a usability point of view—especially when you have so many different assays, and you want to start standardizing them.

So things like protocol templates are also going to have a huge impact.

But I think that’s more of an ease-of-use functionality.

But to me, one thing I’m really looking forward to is the voice-to-text—I think that’s going to have a huge impact.

From a data perspective, which tools are you looking forward to using within the Sapio platform?

I think there’s two parts here. One is the typical no-code/low-code features that Sapio already has, which I think is really useful for scientists who want to have access to that data.

That’s something that comes out of the box, and I think that’s really interesting.

Even things like the rules engine, for instance—I look at it, and I intuitively know how much code would be required if I had to replicate that functionality by writing some Python code or Java code and using the API endpoints to replicate what’s actually happening there.

But it’s really great to see those features come out of the box.

We’ve seen a lot of presentations from other clients who have really configured Sapio for their use cases as well. And there’s a lot of programming and software development that’s gone into it.

I think that’s great, because the ability to configure the system internally as well is absolutely amazing, and I’m personally pretty excited for that.

I can imagine a lot of workflows—especially with instrument integration—you do want to have some custom parsers that parse your data, put that in the right place in the database, and associate it with the right samples.

It is a complex process. And it’s not just us—this is a universal problem. Every company, every group, every organization—they have their own bespoke workflows.

So the ability to bridge those gaps with Python code, using the plugins, APIs, and webhooks—I think that’s going to be really exciting and interesting.

We’re trying to rethink the way we actually handle our workflows. Because when you have an integrated platform like Sapio, I think there’s an opportunity there to really change the way you work—to make yourselves more efficient and get the most out of your data.

As we start implementing it, we’re going to start challenging Sapio on a lot of these things.

One great thing I’ve seen is Sapio seems to live up to those challenges every day.

I remember, even in our evaluations, we gave a pretty complex assay and said, “This is one of our most complex assays,” and Sapio got it configured in a day, which is amazing.

So we’re going to try to continue pushing those limits and see how much we can do in Sapio.

We’re really excited for that.

And one thing that I tell Sapio is, continue doing what you’re doing.

It’s great to listen to the customers—the end users—and see how they’re actually using it, and making those improvements.

Ultimately, like I said, there are probably 100 different ways in which you can configure a workflow. That’s the easy part.

The challenging part is to make it in such a way that it’s usable for your end users.

Creating a database is easy—I’ve done that so many times. But creating a usable interface that stores your unstructured data in a structured format—that’s the challenge.

I think Sapio has done a great job there. So I’m really looking forward to all the new features and everything else that Sapio comes up with.