The lessons learned in mastering autologous manufacturing—where precision, flexibility, and data integrity are pushed to their limits—are shaping how biopharma advances efficiency and control across every process.
The innovations happening in the personalized medicine space are some of the most exciting life sciences advancements in the history of humankind. Many of the autologous, patient-specific therapies are using cutting-edge technologies that feel as if they were plucked directly from science fiction.
Process control of these autologous treatments highlights the way technology can dramatically improve life sciences product development pipelines and supply chains, as they are typically the most extreme cases with respect to critical controls and time constraints. Yet, extreme use cases do not necessarily have different regulatory or process control requirements from other therapeutics. For autologous treatments, the frequency and intensity of stages of the development lifecycle may be amplified compared to population-based therapies, but many of the core strategies and concepts for process control and compliance remain the same.
The operational integrity, flexible manufacturing, and real-time release lessons biopharmaceutical companies have learned from the development of autologous therapies can be effectively applied to other life sciences products—as the required tasks for these products can be extremely labor intensive when manufactured using traditional process control strategies. Applying lessons learned from the high-paced, high-criticality, distributed manufacturing world of autologous cell therapy effectively means leveraging the same born-digital, connected software ecosystem that is key to driving speed and efficiency in other areas.
Improving efficiency and traceability
Consider other modern personalized treatments, such as specialized cancer drugs like monoclonal antibodies used in conjunction with radiotherapy, surgery, or chemotherapy as part of a personalized treatment plan. An increasing number of these treatments are not just based on manufacturing and delivering a pharmaceutical or biotech-based therapy. The complete manufacturing process can also include precision molecular diagnostics and delivery devices, resulting in the final product being regulated as a combination product. Such a solution needs to maintain control, history, and traceability throughout the lifecycle of production of both the therapeutic and its associated medical devices, and that traceability needs to stay intact for all the components of the combination product, both upstream and downstream in the supply chain.
Success in development of personalized treatments relies on an organization’s ability to receive information from multiple, often disparate, sources, append it, maintain data integrity, control manufacturing and distribution processes, and publish results to drive the next step—whether that step is supply chain logistics, or a separate manufacturing process for a delivery device or another component of the treatment. All data needs to move with speed, integrity, and traceability. That is where automation software designed as part of a connected ecosystem can drive success.
The manufacturing execution system (MES) and distributed control system (DCS) play a critical role in helping teams maintain efficiency and traceability of personalized medicine development and manufacturing. A seamlessly integrated DCS and MES can help teams ensure they are recording the correct data to the correct batch, at every stage of development, manufacturing, and distribution (Figure 1).
Figure 1: Operations management technology best practices benefit all aspects of life sciences manufacturing.
As an example, many organizations are error-proofing their operations by using real-time enforcement and recording of material usage with MES and DCS implementations that are integrated with enterprise resource planning (ERP) systems. For example, digitally-encoded material labels help to eliminate manual errors during material assessment, usage, and documentation by allowing critical information to be transmitted and captured digitally across multiple steps, all with automated enforcement of process controls and quality requirements.
With this type of an integrated approach, organizations can ensure that every stage of the manufacturing process is executed and recorded consistently and compliantly with respect to critical process steps, materials, equipment, operator activities, sampling and test results, and quality oversight.
Driving optimization
While process control and traceability are core requirements for developing and manufacturing personalized treatments that drive the future of biotechnology, the value of automation software does not end there. Once a team leverages its automation system to show it can produce a therapy consistently, with robust mechanisms in place for traceability and the ability to isolate root causes of deviations to drive continuous improvement, they can then focus on leveraging the same technologies to run end-to-end operations more efficiently.
For organizations ready to optimize even further, real time scheduling (RTS) software uses predictive modeling so teams are empowered to generate schedules, and to ensure well-planned and executed operation. Along with other benefits, RTS software can both visualize constraints and predict the impact of batch timing changes to help teams maintain flexibility and adjust to changes without disruption.
Many life sciences organizations are also implementing process knowledge management (PKM) software to standardize processes and increase flexibility of operation. PKM provides a central data repository where process specifications are defined digitally, facilitating collaboration, and simplifying the technology transfer process for manufacturing.
Seamlessly integrating these technologies provides life sciences organizations with a path to bring development and manufacturing of diagnostics, therapeutics, and delivery devices into a synchronized production solution. That synchronicity leads to faster delivery of critical medicines and simplified inventory management for raw materials, intermediates, and final products.
A foundation for success
When an organization can reliably trace equipment, materials, people, critical process steps, samples, and more across the entire production lifecycle, the result is a therapeutic (potentially inclusive of the diagnostic and delivery device) with full traceability and a comprehensive batch record. That batch record, or combination of linked batch records, provides the traceability and history of the manufacturing steps—including the materials, equipment, processes, and other parameters—affirming that all products followed good manufacturing practice standards.
Christian Berg
Moreover, the same consistent records make it easy to trace anything that goes wrong in the process back to its root cause. Modern automation platforms built on seamlessly integrated software create that foundation, making it possible to efficiently and effectively deliver the personalized biopharmaceuticals and therapies that will shape the coming decades of life sciences innovation.
All figures courtesy of Emerson
About the author: Christian Berg is a solutions architect consultant for Emerson with over 25 years of life sciences industry experience. Prior to joining Emerson, he was Director of Manufacturing for oncology pilot plant operations at Invitae (formerly ArcherDX) where he implemented operations management standards and initiated digital transformation to enable Personalized Cancer Monitoring (PCM) production. Christian also served in multiple operations management roles at Johnson & Johnson, Genentech, and Amgen. Christian holds a BS in Biophysics and an MS in Organizational Leadership. He also has black belt certifications in Six Sigma methodology and Lean transformation.
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