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Embracing Data as the Key Deliverable in Biomanufacturing.

Matt Todd, Head of Digital & Data


In today’s biomanufacturing landscape, data is a critical component of process development and optimization. At Ori Biotech, process digitization is something we are strongly advocating for with our partners and customers, as it has the potential to transform manufacturing in the cell and gene space by shortening development times, increasing throughput and lowering costs of goods. In recent articles, the concept of “the data is the deliverable” is starting to become more prominent.

Delivering this future ambition calls for a paradigm shift in how we approach data management and native data capture. At Ori Biotech, we recognize the immense potential of this data, but propose that we can go one step further: by treating data as a core deliverable right from the start, rather than as an afterthought.

In an industry that is evolving so rapidly and dealing with increasingly complex processes, embracing data as the key deliverable in biomanufacturing becomes ever more important. A digital approach – that enables us to capture, store and analyze data – will allow us to refine biomanufacturing processes to improve efficiency and scalability across the manufacturing lifecycle. Better preclinical processes increase the likelihood of clinical success, eventual approval and, ultimately, large-scale manufacturing of cell and gene therapies.

Unleashing the Potential of Data Capture:

Current cell and gene therapy (CGT) biomanufacturing processes are highly manual, with a huge reliance on paper lab notebooks and batch records. However, challenges and limitations with transcription, storage and searchability mean that paper-based data capture is inadequate for capturing the intricacies of modern CGT manufacturing processes. Paper backups and manual data transfer methods, such as copy-and-pasting in excel or USBs, increase the risk of errors, slow down development times, and bottleneck batch release, limiting the number of products that can reach patients. It is clear that manual data capture on paper falls short in meeting the demand for scale that advanced therapies and personalized medicines require.

In order to fully understand the underlying causes of process deviations and differences in batch outcomes, and decipher the underlying reasons for these, we need to interrogate manufacturing processes with advanced analytics. High quality data capture is vital for this.

Leveraging Technology to Gain Data-Driven Insights 

By capturing data directly through instrumentation, we can gain a deeper understanding of the intricacies of manufacturing processes through tracking of real-time, high-resolution data of manufacturing variables. With this data at our disposal, we can:

  • Observe previously “hidden” process information to support ongoing process development and identify and solve problems as they occur 
  • Improve accuracy, minimize human error, and enable proactive monitoring of processes
  • Make informed interventions, to ensure that processes remain consistent within optimal parameters.
  • Move toward adaptive manufacturing through in process controls to standardize outputs 

By embracing digitization from the R&D phase, we enable feedback loops that allow us to continuously improve, develop and optimize our processes more quickly. This shift promotes transparency and observability – enabling us to understand why certain outcomes occur and providing valuable insights for process refinement. When processes are “black boxes”, as is often the case when complex manufacturing processes are recorded on paper, it becomes challenging to make informed decisions and adapt effectively. Data-driven transparency empowers us to make better decisions and reduce the costs and time associated with process optimization.

The Power of Integration and Collaboration

Moving to digitized biomanufacturing processes that don’t rely on paper is no doubt a big challenge. Doing so requires investing, often significant, amounts of time and resources into new tools, technologies and skills. However, the value it can bring – to both a business and its science – is significant.

An integrated approach can break down traditional departmental knowledge silos and enable a more holistic understanding of the manufacturing process. For example, integrating environmental monitoring data alongside process parameters and analytical data allows us to identify correlations and better comprehend the impact of external factors on product quality. By leveraging the expertise and perspectives of professionals from different domains, we can enhance our ability to uncover valuable insights that may have otherwise remained hidden, and ensure that decisions are based on a comprehensive understanding of the entire process.

Trusting and Optimizing Data for Better Decision-Making

While the value of data may be clear, a question often that arises is: how much data is enough? The truth is, we may not always know which data points will be crucial in the future – setting up a process to capture as much data as possible in a structured format, from the outset, is therefore imperative. By collecting data consistently and systematically throughout the manufacturing process, we create a historical record that enables traceability and provides deeper insights for decision-making.

To fully leverage the potential of data, integration and storage play vital roles. A centralized repository serves as a reliable source of truth, facilitating easy access and retrieval of data when needed. Structured data enables effective categorization and organization, making it easier to query, analyze and interpret, while metadata is essential for stitching back together disparate data points and providing valuable context for understanding relationships and patterns.

Embracing Data as the Deliverable

Data is currently unusable, trapped in paper processes. We can’t find the low hanging fruit if we can’t see the tree.

Embracing data as the deliverable is not just a theoretical concept; it has tangible benefits for the biomanufacturing industry. By prioritizing data management and native data capture, we can optimize processes, save time, reduce costs, and ensure that specific standards are met throughout the manufacturing process. Manual labor – including transcription and paper processes – has long been a significant contributor to the cost of goods and high failure rates, but through automated quality assurance and data-driven insights, we can streamline operations and ensure adherence to specific standards.

We know that data has the power to transform biomanufacturing – by prioritizing data as a core deliverable from the start, we can unlock valuable insights, optimize processes, and drive breakthrough innovations in personalized medicine. Embracing digital technologies, fostering transparency, integrating data, and optimizing storage are all critical steps in harnessing the full potential of data. Let us continue to strive for excellence in data management to propel the industry forward and improve patient outcomes.

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