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Implementing Manufacturing Workflow Automation

Written by markitects on . Posted in Blog, Expert Blog.

Accelerating Digital Transformation in Life Sciences:
Unlocking Efficiency and Compliance (as seen in MasterControl)

By Anthony DeBiase, Director, Digital PD & Clinical Manufacturing

The life sciences industry faces increasing pressure to streamline operations, ensure compliance, and maintain product quality. Digital transformation in life sciences manufacturing provides an opportunity to address these challenges head on. In a business environment where artificial intelligence (AI) dominates conversation, the life sciences industry cannot take advantage of this transformational technology without implementing core digital systems. Adopting digital systems empowers life sciences organizations to:

  • Improve production efficiency
  • Meet regulatory standards
  • Enhance data integrity

Streamline Workflows, Reduce Errors, and Accelerate Production With Process Automation

Implementing digital systems that provide manufacturing workflow automation can significantly improve production efficiency through the entire production lifecycle for supervisors, operators on the floor, and quality teams.

Life sciences manufacturing takes place in highly controlled process areas where minimizing the number of personnel is a strategy to reduce contamination. This limits the supervisor’s ability to gain real-time insight into manufacturing outside of traditional equipment sensor data. Supervisors must rely on the data that is generated by the manufacturing records, logs, and equipment to understand how well the manufacturing process is running. This data is received after the processing is complete, not allowing for prevention of any issues that arise. For example, in cell therapies, single-use bioprocessing systems are critical to prevent patient cells cross contamination. These systems provide limited online sensor data compared to that of traditional stainless systems. Traditional stainless-steel systems are highly automated with processes that capture all process actions such as when a valve opens and how long a pump is running. This data can be stored in a historian and trended, while most of the manual interactions such as welding tubing, sampling, and solution transfers aren’t captured automatically. If the data from these events is not captured and reviewed in an efficient way supervisors will have limited insight into their plant operations.

Utilizing manufacturing workflow automation allows supervisors to improve product efficiency through the following steps:

  1. Collect Data: Aggregate all activities (“online” machine automation and “offline” manual procedures)
  2. Track and Trend: Visualize your personnel and facility constraints in real time
  3. Control: Debottleneck the process, optimize your production activities, and schedule and reduce downtime
  4. Maintain: Understand the implications of changes in your manufacturing process

These systems can also provide dashboards that improve operational awareness for operators on the production floor. Operators can leverage data to make informed decisions or navigate complicated processes. A frequent challenge in this space is varying raw or starting patient material quality. Starting cell density or cell growth can vary drastically, causing uncertainty in processing actions to take. Manufacturing workflow automation such as flexible, electronic batch records can build quality and efficiency into the process by guiding operators through these challenges. A digital solution that directly links batch records and work instructions to information such as standard operating procedures (SOPs) and other documents found in a quality management system (QMS) gives operators access to everything they need to successfully execute batches.

Cell therapy processes are very manual and require significant scale out to meet patient demand. Scaling out further exacerbates the challenges of the operations. In addition, labor-intensive paper processes add to the workload of already overburdened operators. Every page of records can have multiple opportunities for human error including incorrect entries, miscalculations, and executing steps out of order. Implementing manufacturing workflow automation such as an electronic batch record in a manufacturing execution system (MES) can eliminate these opportunities for error.

With the appropriate insight into the production floor utilizing manufacturing workflow automation solutions, life sciences manufacturers can move from being reactive to proactive. These tools also allow operators to make guided decisions for complex processes. This provides some key benefits:

  • Maintain quality
  • Maximize uptime
  • Improve throughput
  • Reduce waste
  • Effectively scale up or out

Implementing Digital Systems to Improve Quality Oversight, Maintain Regulatory Compliance, and Improve Audit Readiness

Maintaining life sciences regulatory compliance is a critical focus for manufacturers in the industry. Digital transformation in life science manufacturing not only helps supervisors and operators increase operational efficiency, but it enhances the capability of quality assurance teams to build and maintain regulatory compliant business processes. Digital systems do this by giving quality teams the data and information they need in a timely and structured manner. Examples include:

  • Reducing the risk of manual errors and inconsistencies by enforcing rules that must be followed
  • Capturing, investigating, and resolving deviations
  • Saving significant review time by preventing simple but consistent good documentation practice (GDP) mistakes such as significant figures
  • Reducing review cycles with review by exception
  • Tracking corrective action/preventive action (CAPA) effectiveness
  • Facilitating continuous process verification (CPV)

Meeting Regulators’ Data Integrity Expectations

In recent years, regulatory agencies have increasingly observed current good manufacturing practice (cGMP) violations involving data integrity during inspections. Upholding data integrity is an important component to ensure the safety, efficacy, and quality of drugs. Maintaining accurate and complete documentation is essential for regulatory audits and inspections.

Manufacturing workflow automation can provide solutions for compliance with 21 CFR Parts 210, 211, and 212, which set forth the following data integrity requirements:

  • “backup data are exact and complete,” and “secure from alteration, inadvertent erasures, or loss”
  • data be “stored to prevent deterioration or loss”
  • certain activities be “documented at the time of performance”
  • records be retained as “original records,” “true copies,” or other “accurate reproductions of the original records”
  • requiring “complete information,” “complete data derived from all tests,” “complete record of all data,” and “complete records of all tests performed”

Additional Benefits Digital Systems Provide

Other opportunities for companies seeking to maintain life sciences regulatory compliance utilizing digital systems include:

  • Facilitate better collaboration and communication across departments and with external partners, including regulatory agencies
  • Easily reviewed regularly and updated to reflect the latest regulatory requirements or to meet regulatory requirements in a specific geographic location
  • Centralized platform for storing, managing, and accessing data that ensures all data and information is organized, accessible, and secure
  • Enable compliant workforce growth by managing employee training records and qualification statuses

By embracing digital transformation in life sciences manufacturing organizations can not only enhance overall operational efficiency but also ensure compliance with regulatory requirements. This holistic approach supports sustained growth and competitiveness in a highly regulated environment. Building this foundation will allow for scalability and ultimately the ability to leverage new and transformational technologies such as AI.

Now that you understand the benefits of implementing digital systems to your manufacturing workflow, please reach out to me with your comments or to start a dialog.

Continua at IFPAC® 2025

Written by markitects on . Posted in Blog, News & Events.

Join Paul Brodbeck, Chief Technologist, and Our Team of Experts on Tuesday Afternoon, March 4th, in the Forest Glen Conference Room

Topic: Real-time Deployment of AI in Industrial Processes

Abstract:
Continua will discuss its experience with the deployment of mechanistic, APC optimization, and machine learning algorithms in real-time. We will discuss the challenges of building models from historical process data and deploying the models in a stable and manageable ML platform including GMP. A full stack solution called MLO will be presented that demonstrates a seamless method of collecting data through to predictions including OT gateway/data connectors, data brokers, DataOps, and MLOps (AI deployment platform).

Biography:
Paul Brodbeck is the Chief Technologist and co-founder of Continua Process Systems. Continua helps companies optimize manufacturing operations through the application of emerging and advanced technologies including Machine Learning, Process Analytical Technology (PAT), Digital Twins, Digital Transformation, IIoT, and Industry 4.0. The goal is to embed AI and Machine Learning models to fuel predictive analytics and proactive decision-making—optimizing operations and maximizing quality, production, and yield. Continua has developed a working Process Digital Twin for a bioprocess that executes mechanistic models and machine learning models (NN, MPCA, MPLS) at the Edge with an open-standard MLOps deployment platform. The MLOps platform has a Cloud component for training Python ML algorithms.

An exciting new technology is emerging for Industry 4.0 digital transformation that is based on MQTT data brokers. Digital transformation efforts based on traditional technology such as OPC and vertical integration stacks fail as they try to scale. MQTT is a lightweight, report-by-exception, open-platform that scales efficiently to enterprise-wide networks.

REGISTER FOR IFPAC 2025

Continua Sponsors PAT & Real Time Quality Summit

Written by markitects on . Posted in News & Events.

Join us December 11-12 in Philadelphia!

Continua is a proud sponsor of the 3rd Annual PAT conference: Successfully Implement PAT Across the Drug Development Lifecycle to Increase Automation and Drive Cost Efficiency. This conference is designed exclusively for the Pharmaceutical and Biopharmaceutical community. Join 100+ leading PAT scientists, engineers, process development, CMC, MSAT and quality experts and discover interactive workshops addressing crucial challenges across regulatory requirements and implementing automation.

The maturity of PAT tools and the development of sophisticated software and chemometrics now provide the perfect opportunity to revolutionize traditional quality and analytical approaches, achieving the digital manufacturing maturity necessary for the future. With drug developers and manufacturers facing closer scrutiny on product quality than ever before, it’s time to make the most of evolving process analytical technology (PAT) to design robust and cost-effective control strategies to understand more about your biopharmaceutical products. 

Connect ground-breaking technologies with real-world manufacturing investment decisions to:

  • Explore cutting-edge data-driven case studies
  • Engage in dynamic roundtables
  • Deep dive into KOL-led panel debates
VIEW EVENT & REGISTER

The Next Step in Your Digital Strategy

Written by markitects on . Posted in Expert Blog.

How to Assess and Build Your DX Strategy With
a Digital Transformation Maturity Assessment

By Paul Brodbeck, Chief Technologist

One method to facilitate the creation of a Digital Strategy and a Roadmap to begin the journey, is to start with a Digital Transformation Maturity Assessment (DTMA). A DTMA is a comprehensive evaluation process used to determine an organization’s current level of digital maturity. This assessment helps organizations understand where they stand with digital transformation and identifies areas for improvement. It creates a client’s specific roadmap for starting or continuing their digital transformation journey—including current state, future state, basic architecture, risks and first steps. 

Our deliverable is a final report that includes the evaluation, assessment, road map and maturity score. Key outputs are a digital strategy, a recommended basic architecture & technology, and a recommended proof-of-concept project to demonstrate the technology. Below is a graph depicting excerpts from an actual DTMA performed for one of our clients.

These suggested actions are representative of some of the potential benefits of taking the first steps toward adopting a corporate-wide digital strategy and ensuring your plants are on board. Please reach out to me to schedule your DTMA.

The Ideal Architecture for Digital Transformation

Written by markitects on . Posted in Expert Blog.

Know the ‘Current State’ of Your Business AND
‘Future State’ of Your Business in Real Time.

By Paul Brodbeck, Chief Technologist

As covered in my last article, the first steps toward a digital transformation are to develop a strategy, get buy-in, and create a roadmap aligned with the business. Now, you’re ready to select a proof-of-concept pilot project. Typically, the pilot should be small enough to be completed over a 3-4 month period and use an Agile project management approach. An Agile approach promotes flexibility, collaboration, and continuous improvement throughout the project lifecycle—which is particularly important for the introduction of a new technology. In addition, smaller projects are more easily funded and quick wins can help justify bigger capital investments as the scope grows.

The Data Conundrum

The process of digital transformation and the implementation of advanced technologies, such as Machine Learning (ML) and Artificial Intelligence (AI), require vast amounts of data. This data is not useful unless it can be interpreted in a meaningful way. Context adds meaning to raw data and transforms it into actionable information. We’ve all heard about the failures of Big Data projects due to lack of data contextualization.

The ability to transmit and contextualize large amounts of data throughout the enterprise requires rethinking how OT networks are architected. Traditionally, the main focus has been to protect the data behind firewalls, the argument being that opening ports in the firewalls begins to compromise the integrity of existing cybersecurity systems. The most common OT network architecture is the vertically stacked Purdue model, where hardware and software solutions are siloed, and vendor locked. In this scenario, unlocking the data requires custom protocols and licenses—not exactly a viable approach. Therefore, a new architecture has emerged, that is better suited for large amounts of data and enterprise-wide data buses, called the Hub/Spoke model.

The Emerging Hub/Spoke Model With UNS

A Hub/Spoke architecture uses: a low-bandwidth protocol called MQTT, an efficient data transmission method called publish/subscribe (or pub/sub), and data brokers that scale to high traffic volumes and provide redundancy. This network structure can communicate seamlessly with cloud applications because they are already standardized on MQTT. A framework, called the Unified Namespace (UNS), is superimposed on top of the Hub/Spoke network to further extend its capability as an enterprise-wide data hub. The combination—a Hub/Spoke network and UNS—forms the ideal infrastructure for an enterprise-wide data hub to support Industry 4.0 and predictive analytics, like ML and AI. Hub/Spoke is the backbone; MQTT data brokers provide the ability to transport large amounts of data; and the UNS provides a contextualized framework for interoperability and seamless data access.

Ultimately everything and everyone is plugged into the network. As a single source of truth, your UNS is a virtual representation of the business in real time which forms the basis for predictive analytics and actionable decisions. This real-time data is used to collect and analyze data/information to leverage ML/AI. ML predicts future outcomes based on past patterns and the current state. The layers of the business are integrated and operate based on data and information from all layers—in real time. Stakeholders know the ‘current state’ of the business in real time and stakeholders know the ‘future state’ of the business in real time.

Now that you’ve been exposed to Hub/Spoke and UNS, you probably have some questions about your selection of a proof-of-concept pilot. Please reach out to me to start a dialog.

The Business Case for Digital Transformation

Written by markitects on . Posted in Expert Blog.

Unlock New Revenue Streams. Innovate Product Offerings.
Build Resilience Against Market Disruptions.

By Paul Brodbeck, Chief Technologist

There are numerous white papers and surveys indicating that most CEOs believe data-driven transformation is crucial to their companies’ futures. Furthermore, the popularity of generative AI (ChatGPT, LLM, ML) allows us to believe that this technology is within practical reach. At the very least, manufacturers know they need to start investing in generative AI technologies in order to stay competitive.

The end-goal is that embedded AI and Machine Learning models will fuel predictive analytics and proactive decision-making—optimizing operations and maximizing quality, production, and yield.

We see and hear that companies do not have enough visibility into plant operations. For strategic planning and flexibility, a company needs to know the current state of its operations. Digital transformation empowers companies to optimize operations, enhance decision-making, and improve customer experiences through data-driven insights and automation. It enables companies to stay competitive in rapidly evolving markets by reducing costs, increasing efficiency, and accelerating time-to-market for new products and services. By leveraging advanced technologies, like AI and Machine Learning, businesses can unlock new revenue streams, innovate their product offerings, and build resilience against market disruptions.

Digital Transformation can unlock significant value across the entire supply chain and throughout the factory network.

Where to Start Your Digital Transformation Investments

Your first actions should be to invest in a clear strategy and vision aligned with your business and to secure executive sponsorship. Companies need a digital strategy to provide a clear roadmap for leveraging technology to achieve their business goals, ensuring alignment between digital initiatives and overall company objectives.

A well-defined digital strategy helps businesses navigate the complexities of digital transformation, prioritize investments, and address potential challenges like data security, integration, and change management. It enables companies to stay competitive by adapting to market trends, enhancing customer engagement, and continuously improving operational efficiency in an increasingly digital world.

Steps to Creating a Digital Transformation Strategy for a Sample OT Facility

Now that you understand the essentials to getting started on your Digital Transformation journey, I’ll next explain the ideal architecture needed for digital transformation to occur. In the meantime, please reach out to me with your comments or to start a dialog.

Paul Brodbeck to Present at Continuous Manufacturing Forum

Written by markitects on . Posted in News & Events.

September 17-19 | Princeton, NJ

Join us at the Continuous Manufacturing Forum, where Continua’s Paul Brodbeck will be speaking on Advances in Technology.

The Continuous Manufacturing Forum serves as a catalyst for compelling conversations, bringing together key opinion leaders in biotech and pharma. It unites executive leadership, directors, senior scientists, consultants, and a closely-knit network of CDMOs, academic leaders, and equipment providers.

Paul Brodbeck
Chief Technologist
Continua

VIEW AGENDA & REGISTER

Augmenting an MES

Written by markitects on . Posted in Insights & Stories.

This pharmaceutical customer has a large amount of data that needs to be contextualized and brought into their MES, but that’s not what an MES does best. Our project entails bringing that data into a Unified Namespace (UNS) ecosystem and then back into the MES, once contextualized. If you want to use your data outside of the MES, for instance in an ERP or other business systems, then the number of links in and out can grow exponentially. Our eventual goal is to get away from proprietary software solutions that sit in the middle of your stack. When you move to a UNS, you can use any software and it’s easy to upgrade or switch, as well as much more flexible. Contrary to what many people may think, security is better too. Each layer has a firewall and the data is well-protected; if you open more ports, there’s inherently more risk. By the nature of the way a UNS works, getting IOT data out is less risky because you’re publishing out with no need to open inbound ports. In fact, Gartner is now recommending this architecture in lieu of the traditional Purdue model.

Integrating Lab Automation Systems

Written by markitects on . Posted in Insights & Stories.

Every pharmaceutical company uses manual laboratory automation systems, like the Nova FLEX cell culture analyzer, and frequently they need to perform calculations based on the results. Continua worked with this company to integrate their Nova FLEX data with their plant control system to automate the required actions based on the analysis results and to publish this data into the UNS for visibility across the business area.