Company insight

Transform with smart manufacturing

A new paradigm is needed to achieve the optimal productivity levels required to meet the challenges being faced at all segments of the market, regarding global demand for scaling Covid-19 vaccine production, the shift from small molecules to biologics and personalised medicine, and pressure from patent cliffs, generics and drug payers. John Vitalie, CEO of Aizon, explains how his company can help enterprises transform manufacturing with smart technologies.

What Industry 4.0 use cases for bio/pharma manufacturing are showing a clear ROI? John Vitalie: At Aizon, we have incredible experiences, such as: ■

Yield optimisation to reduce COGS: Yield improvements have been achieved across a number of manufacturing processes and steps with significant impact on product line profitability, in some instances with an ROI of up to 100x, and in a time frame of less than two months. This is amplified when solutions are deployed across the manufacturing process and scaled up to multiple sites. ■

Process robustness improvement: In one of our use cases, our platform was applied for root cause analysis (RCA) and development of a real-time AI predictive model, which enabled the identification of optimal operational set points, and resulted in significant cycle time improvements and a reduction in product loss. In this case, our customer achieved a 4x ROI and a payback in less than three months.

Beyond these examples, there are more use cases generating significant, tangible business value – predictive maintenance, deviation root cause analysis and raw materials pooling strategy.

What are the key components of a successful smart manufacturing initiative? In the simplest terms, we see successful, sustainable smart manufacturing initiatives when there is a mandate in place for process improvement, and expectations are defined by attainable and stretch goals. Time to value is a key factor to drive prioritisation, which depends on the specific use case.

Ultimately, the pathway to achieve Pharma 4.0 capabilities goes through the expansion of successful use cases across sites and manufacturing processes until fully covering manufacturing operations end-to-end. The point of action is to introduce controlled changes with precision in order to improve operational efficiency in regulated processes, which forces any successful initiative to be executed in a GxP compliant way. Thus, the winning approach is to start with a GxP-ready digital framework. This ultimately requires the use of qualified AI algorithms and validated models in the manufacturing process. Aizon has brought to market an AI GxP platform and applications suite, developed to satisfy this need and enable the smart technologies to transform manufacturing for pharma and biotech. We recognise that every customer is at a different stage of a digital transformation journey, so we have tailored our platform and applications (standardised use cases) to meet the customer where they are and help them identify the areas of focus to achieve value in the shortest time frame. But I can’t underscore enough that the prioritisation and cross-departmental execution must be driven by a senior executive sponsor in order to overcome organisational friction and inertia. The visibility, understanding, and knowledge generated from an aligned organisation on digital transformation are strategic, and differentiating for pharma and biotech companies, and their contract manufacturers. These capabilities are essential to remaining competitive in today’s fast-changing world.

How can AI be translated to the bio/pharma industry?

Aizon has taken a leading role in defining how to ‘industrialise’ AI and make the

World Pharmaceutical Frontiers /

insights actionable for regulated processes. For example, we published a procedure on AI algorithm qualification for use in industrialised, regulated contexts to boost the use of AI as the multivariable tool to manage the inherent variability in pharma and biotech manufacturing. We are also leading the path and methodology to make continued process verification (CPV) a reality. These are the kind of initiatives that the industry is demanding these days – everyone recognises the value of AI, but how can it be implemented in GxP environments? Our main goal is to serve our customers in their missions of improving the quality, safety and efficacy of drugs to serve patients. At our core, we do this by answering this fundamental question around the application of AI in GxP contexts. Our unique platform enables customers and partners to manage all the data and AI elements embedded in the life cycle for their use in GxP regulated environments.

How can the industry leverage the impacts of Covid-19 to become more robust going forward?

Covid-19 showed all of us the importance of accelerating time to market. Of course, as we have seen, there are many critical bottlenecks in the vaccine value chain. However, one of the most critical is the speed to transfer the process of production of the vaccine to different sites around the globe, as quickly as possible, while meeting the required quality and regulatory requirements. We are fully committed and focused on improving these processes, and providing the solutions within a highly elastic and sustainable system so continuous manufacturing becomes a reality. ● 43

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