BLOG SERIES: Data management in cell and gene therapy manufacturing

In our interactions with professionals in the cell and gene therapy manufacturing field, we witnessed firsthand the struggles with streamlined data management and process analytics. 

This series of articles is MyCellHub’s response to these issues: a practical guide so you can cut through the complexity and effortlessly optimize the most crucial aspects of manufacturing. 

This guide dives into the untapped potential of streamlined data collection, processing, and management as a catalyst for efficiency and agility in the manufacturing process. We describe practical and actionable steps like selective data collection, directly affecting product quality. We also detail the importance of focusing on critical parameters of your production and using the power of analytics for continuous process improvement. 

Find out how to elevate your production process with our insights and innovative strategies for data management in cell and gene therapy manufacturing.

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PART 02:

3 tips for strategic data selection in cell and gene therapy manufacturing

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Our previous article exposed the maze of data management challenges in cell and gene therapy manufacturing. Drawing on our close partnerships with professionals in biopharmaceutical industry, we examined the rising complexity in this field and the exponential growth of data we need to handle.

With this exploration, we identified four main challenges the cell and gene therapy manufacturing industry faces:

1. Increasing complexity of processes.
2. Limited implementation of Quality by Design principles.
3. Increasing time-costs of data-related tasks.
4. Inefficiency caused by lack of standardization.

Keeping these data-related challenges in mind, we'll now delve into ways to overcome them.

Let’s start from the beginning: data selection and collection. 

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‘Too much data’ is a thing

One of the issues we confront in contemporary biopharma manufacturing is the overwhelming quantity of data generated. This leads to the tough task of analyzing, filtering, and interpreting this huge dataset.

But it's essential to remember that collecting all data isn't as important as focusing on the right data. The data that matters is data that can provide valuable insights and enhance the efficiency of your operations.

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If you’re wondering how to choose the most suitable data to support your cell and gene therapy manufacturing, you’ve come to the right place. Follow the advice outlined in this article to refine your data collection strategy and fast-track the introduction of life-changing therapies to the market.

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Which data to collect?

Selecting the right data to collect is a critical aspect of streamlining data management and analytics for cell and gene therapy production. Efficient data selection can be achieved by focusing on meaningful data and minimizing noise. As a result, it improves the overall quality of your manufacturing and the produced therapy itself.

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Focus points for strategic data selection:

1. Focus on essential data for controlling Critical Quality Attributes (CQAs).

Prioritize data that directly affects the quality, potency, safety, and consistency of the product. By focusing on critical data points, you can optimize your production process and better maintain product quality without wasting energy on analyzing redundant data. 

Real-world cases often emphasize the importance of understanding and controlling CQAs, as these attributes directly impact the efficacy and safety of cell and gene therapies [1, 2].

Practical tip 01
‍Avoid duplicated data.

Audit your processes to find any overlapping quality control (QC) tests. Duplicating QC tests may unknowingly provide redundant information by doubling it. Streamlining QC processes with digital workflows lets you supervise them and is one of the best ways to ensure that collected data is of significant value to your operations. 

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2. Minimize noise and variability in collected data.

Use sensitive detection methods, process automation, standardization, and proper monitoring of raw materials during process development to reduce variability and noise in the data. Minimizing noise helps maintain a clear link between critical process parameters (CPPs) and CQAs, enabling better control over the product's quality attributes. In practice, the step of minimizing noise and variability may involve investing in advanced analytical methods, reagents and equipment to ensure accurate and reliable data collection.

Practical tip 02
Fewer steps, more benefits.

A typical way of minimizing variability is to make the process as lean as possible during scale-up from lab scale to clinical manufacturing [3]. By reducing the number of process steps, you simplify the workflow, minimize the potential for errors or deviations, and increase the likelihood of reproducible outcomes. 

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3. Leverage Quality by Design (QbD) tools.

Utilize tools such as Design of Experiment (DOE) and risk assessment to comprehend the relationship between CPPs and CQAs. These tools help identify the minimal data set necessary to actively manage CQAs and enable a better understanding of the production process. 

Practical tip 03
Rank the risks.

Assess the risk of your CQAs using the ranking approach [4]. This strategy is used by some of the most prominent pharma companies. With its help, you’ll easily establish which data to include in your testing plan to optimize your process quality control. 

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Selective data collection will soon be a crucial part of transformative advancements in cell and gene therapy manufacturing. By embracing strategic approaches to data selection early on, your organization can swiftly pave the way to streamlined operations. 

Stay tuned, as in the next part of our Data management in cell and gene therapy manufacturing series, we will explore various strategies and tools to optimize data organization and integration, ultimately leading to more efficient production and highest quality of the manufactured therapies.

Don't miss out on these valuable insights to transform your biotherapeutic manufacturing process. Make sure to follow us on LinkedIn to stay updated and be among the first to read our latest content.

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Ready to try the digital workflows in your gene and cell therapies manufacturing? 

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