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    Expert's Opinion

    Elevating Process Engineering to Improve Predictability, Reliability & Productivity

    It is past time for drug makers to shift from a document- and compliance-centered paradigm to one focused on science and engineering

    Elevating Process Engineering to Improve Predictability, Reliability & Productivity
    Cathal Strain, President, Neo PLM03.18.20
    Chemical engineering tends to be the predominant discipline in process manufacturing organizations, and the life sciences space is no exception. In fact, a chemical engineer can find a home in myriad areas across a pharmaceutical manufacturing organization, and at all levels of management. That includes roles spanning the product lifecycle, from process development and engineering to production supervision, process control and automation, quality management—and even finance.

    With its prevalence of engineers, one might expect pharma to rank among the top industries for manufacturing innovation, productivity, efficiency and reliability. On the contrary, life sciences lags other sectors significantly in these areas. Today’s pharma process engineers spend vast amounts of time dotting i’s and crossing t’s on compliance-related documents rather than applying their scientific expertise. It is past time for drug makers to shift from a document- and compliance-centered paradigm to one focused on science and engineering—particularly if they hope to unlock the possibilities of Pharma 4.0.

    There are many factors to assess when considering what has led the industry to its current state. Perhaps a few basic business realities offer the simplest explanation. A pharma company’s financial success is driven first and foremost by its R&D department’s ability to discover innovative new drug therapies and bring them to market. Secondly, the company must market those products effectively. Pharma is not particularly sensitive to manufacturing costs, which can impact profits substantially in industries that provide commodity products. When it comes to the manufacturing supply chain, pharma companies are mainly concerned with having quality product delivered on time. That mindset has bred a defensive mentality that fundamentally discourages innovative thinking. In short, change equals risk—so avoid it.

    Another factor that can draw focus and resources away from engineering is the scale of pharmaceutical manufacturing. Relative to other industries, quantities of drugs manufactured are quite small. That means manufacturing facilities are also relatively small; in most cases, a plant will produce a number of different products with many changeovers in between. Pharma companies may trivialize the engineering complexities this environment presents. However, small-scale batch production in a flexible, multi-product plant is at least as challenging as large-scale continuous process manufacturing.

    At many pharma companies, the net impact is that process engineers must operate within stifling constraints. An engineer’s natural instinct is to seek ongoing productivity improvements, maximize asset utilization and relentlessly drive cost reduction. Achieving these objectives requires continuous change, which can be a challenge in pharma manufacturing.

    Adding to the challenge are distributed and disjointed engineering assets. True engineering begins in process R&D, typically culminating with tech transfer to manufacturing. The plant’s process and production teams then turn their attention to bringing manufacturing online. From that point forward, all efforts are locally focused as engineers concentrate on making and releasing product.

    Batch records at most plants are completely paper-based, providing almost no visibility into real production data to support advanced analytics. Process engineers are thus stripped of a critical responsibility—driving continuous improvement. Outsourcing production to contract manufacturers can exacerbate that knowledge gap. And even at plants that are well equipped with process automation and instrumentation technology, analysis is primarily aimed at supporting batch release.

    This despite the industry’s ongoing discussion of process analytics, beginning with PAT initiatives nearly two decades ago. Now, with the focus on Pharma 4.0, the conversation has turned to cloud services, data lakes and IIoT. These technologies have the potential to empower process engineers like never before. But if life sciences companies are to participate in Industry 4.0, pharma must reimagine the way it is structured to fully leverage the abundance of engineering talent at its disposal:

    •    The critical first step is adopting an enterprise lifecycle approach to product and process engineering. The use of spreadsheets and other documents to support tech transfer must become a thing of the past.
    •    Discrete manufacturers place digital product engineering at the core of their business operations through CAD and CAE technologies. Pharma must embrace the same model, arming process engineers with modeling and simulation capabilities that maintain a digital design thread as products move from process R&D through the full manufacturing cycle.
    •    Manufacturing plants must upgrade their shop floor technologies with modern process automation and measurement solutions to enable paperless manufacturing.

    These strategies are foundational to unlocking the promise of Pharma 4.0—providing access to data and process knowledge across the enterprise, while opening the door to advanced capabilities such as AI and machine learning.

    It all begins by elevating process engineering to a central role, with organizations managing the product and process definition digitally and maintaining complete traceability as production moves from one location to another. Pharma companies must empower their engineers to modernize manufacturing facilities with leading-edge shop floor technologies. At last, engineers focused on process analytics will gain the substrate needed to troubleshoot and find ways to increase productivity, reliability and asset utilization.

    The quality assurance function, currently mired in a document- and paper-based approach to compliance, must move out of the way. After all, quality is ultimately a by-product of process engineering excellence.
     

    Cathal Strain is CEO of Neo PLM, the company that pioneered digital design-based Process PLM. Cathal founded Neo in 2011 with the vision of bringing third-millennium PLM capabilities to pharmaceutical companies and other process manufacturers. Today, leading pharmaceutical manufacturers are deploying Neo’s technology at sites around the world. Cathal previously spent over 30 years at Pfizer, where he led the design, development and implementation of the world’s first integrated PLM solution for process manufacturing.
     
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