Agenda
Our education program offers cutting-edge technical sessions, shedding light on the latest advancements in the pharma industry.
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Pharma 4.0 Case Studies and Lessons Learned
Wed, 11 Dec
1045 – 1115
Pharma 4.0 Case Studies and Lessons Learned
Rolf Traut, Takeda Pharmaceuticals
Sergio Torralbo Jimenez, Takeda Pharmaceutical Co Ltd
The rapid advancements in Industry 4.0 requires robust, scalable, and integrated digital data platforms to harness the full potential of manufacturing data. The corporate data platform aims to unify disparate data sources (PLCs, SCADAs, IPC equipment, etc.), enabling seamless data contextualization, processing and analysis. By leveraging cloud-based technologies, it allows the use of manufacturing data (historical and real-time) for advanced analytics, predictive maintenance and machine learning algorithms. It supports a wide array of data types, including IIoT sensor data, process time series data and alarm and events, ensuring a holistic availability of manufacturing process information. The emphasis lies on scalability and easy access to the platform for end users in the sites. Beyond the initial installation of the platform in our the sites, it is obvious that the value of the program is delivered through site use cases implementation. For this purpose, a comprehensive integration tool and several standards have been developed to support the platform use cases creation in the sites, facilitating an easy integration with legacy and new manufacturing systems and third-party applications. Security and data integrity are as well prioritized through state-of-the-art encryption and compliance with industry standards. By transforming raw manufacturing data into actionable intelligence, this digital data platform not only will allow the continuous production optimization but will also enable innovation and competitive advantage in our manufacturing landscape.
1115 – 1145
Pharma 4.0 Case Studies and Lessons Learned
Lukas Markwalder, Capgemini
Hans Otto Weinhold, AVEVA GmbH
Bernd Sessler, Roche
Global Industrial Data Hub for rapid Pharma 4.0 Manufacturing Transformation.
The Roche Lighthouse Project showcases the benefits of a joint approach by Pharma (Roche), Software Vendor (AVEVA) and Consulting Company (Capgemini) to seamlessly integrate a new Cloud Data Hub integrating global Manufacturing Data pipelines and rapidly develop scalable Visualization and Analytics Solutions within less than 6 months. The primary business objectives of this Lighthouse engagement were to align the new cloud based industrial data hub with Roche’s business needs, focusing on 3 key use cases:
1.Data Mesh: seamless integration of global data sources on the injection side and various fit for purpose visualization and analytics tools on the consumption side. This makes data widely available to enterprise consumers via tools like Aveva Advanced Analytics, Seeq, Dataiku via Snowflake (Enterprise Datahub), etc.
2.Digital Maintenance – use analytics to reduce downtime and make maintenance more condition based and cost efficient.
3.Net production time: analysis to showcase optimized equipment utilization and operational efficiency.
The Roche Lighthouse Project showcases the benefits of a joint approach by Pharma (Roche), Software Vendor (AVEVA) and Consulting Company (Capgemini) to seamlessly integrate a new Cloud Data Hub integrating global Manufacturing Data pipelines and rapidly develop scalable Visualization and Analytics Solutions within less than 6 months. The primary business objectives of this Lighthouse engagement were to align the new cloud based industrial data hub with Roche’s business needs, focusing on 3 key use cases:
1.Data Mesh: seamless integration of global data sources on the injection side and various fit for purpose visualization and analytics tools on the consumption side. This makes data widely available to enterprise consumers via tools like Aveva Advanced Analytics, Seeq, Dataiku via Snowflake (Enterprise Datahub), etc.
2.Digital Maintenance – use analytics to reduce downtime and make maintenance more condition based and cost efficient.
3.Net production time: analysis to showcase optimized equipment utilization and operational efficiency.
1145 – 1215
Pharma 4.0 Case Studies and Lessons Learned
Michelle Vuolo, Tulip Interfaces
Pharma has not yet fully experienced the paradigm changes that most other industries have gone through, and it shows. Imagine the impact of deploying digital solutions in your operations — enabling you to experience an order-of-magnitude increase in quality levels while also decreasing the Cost of Quality.
This session will tell the story of how NextPharma adopted a frontline operations platform as their digital solution for maintaining compliance and quality in their processes. Throughout their digital transformation journey, NextPharma learned that digital solutions should not be focused solely on automation but could also be used to augment their human workforce. By building simple digital apps that provided operators with step-by-step guidance for completing each process, they were able to increase quality, and provide information more readily to the necessary pharmacists. This new method resolved the compliance need for pharmacists to be in close proximity to the process, providing a digital twin of the process that is visible from anywhere in the facility with rich data. The digital solution, which can be easily scalable across NextPharma’s sites, supports the human workforce in achieving better quality and control of processes, helping to maintain patient safety.
This session will tell the story of how NextPharma adopted a frontline operations platform as their digital solution for maintaining compliance and quality in their processes. Throughout their digital transformation journey, NextPharma learned that digital solutions should not be focused solely on automation but could also be used to augment their human workforce. By building simple digital apps that provided operators with step-by-step guidance for completing each process, they were able to increase quality, and provide information more readily to the necessary pharmacists. This new method resolved the compliance need for pharmacists to be in close proximity to the process, providing a digital twin of the process that is visible from anywhere in the facility with rich data. The digital solution, which can be easily scalable across NextPharma’s sites, supports the human workforce in achieving better quality and control of processes, helping to maintain patient safety.
1345 – 1415
Pharma 4.0 Case Studies and Lessons Learned
Michelangelo Canzoneri, Merck KGaA Darmstadt, Germany
Giuseppe Menin, Ing. Punzenberger COPA-DATA GmbH
Speeding up and Simplifying Modular Equipment Connectivity in Labs/Production
Merck KGaA has discovered a key success factor in modular production through the implementation of the Module Type Package (MTP) standard (VDI/VDE/NAMUR 2658). MTP is an innovative approach that enables seamless communication across all equipment within a central control system, overcoming the challenges posed by a fragmented hardware and software landscape.
By encapsulating individual work steps into modules, researchers can quickly and repeatedly assemble these into new applications and processes using graphical tools, without needing programming expertise. This concept of "Plug & Produce" is further enhanced by the introduction of a central software platform known as the Process Orchestration Layer (POL), which automatically integrates all instrument functions as MTP modules (Process Equipment Assembly - PEA).
Key benefits include:
•Automation of Operations: The primary role of the workforce in labs and operations is emphasized, allowing them to focus on their tasks rather on than the manual integration of devices or transferring experiment data into flat Excel files.
•Paperless Operations: Process values, measurements, deviations, and execution logs are stored electronically, eliminating the need for manual records.
•Fast Reconfiguration and Tech Transfer: Scaling up processes from laboratory to commercial manufacturing is streamlined, requiring no manual adjustments.
The presentation will provide an overview of the project timeline, from the pilot phase to the full automation of 600 modules according to the MTP standard. We will also showcase a video demonstrating the steps a laboratory engineer takes to reconfigure an experiment setup, from integrating "MTP ready" modules to process orchestration and control application generation to execution. This will offer a clear understanding of the practical application and benefits of this technology.
Merck KGaA has discovered a key success factor in modular production through the implementation of the Module Type Package (MTP) standard (VDI/VDE/NAMUR 2658). MTP is an innovative approach that enables seamless communication across all equipment within a central control system, overcoming the challenges posed by a fragmented hardware and software landscape.
By encapsulating individual work steps into modules, researchers can quickly and repeatedly assemble these into new applications and processes using graphical tools, without needing programming expertise. This concept of "Plug & Produce" is further enhanced by the introduction of a central software platform known as the Process Orchestration Layer (POL), which automatically integrates all instrument functions as MTP modules (Process Equipment Assembly - PEA).
Key benefits include:
•Automation of Operations: The primary role of the workforce in labs and operations is emphasized, allowing them to focus on their tasks rather on than the manual integration of devices or transferring experiment data into flat Excel files.
•Paperless Operations: Process values, measurements, deviations, and execution logs are stored electronically, eliminating the need for manual records.
•Fast Reconfiguration and Tech Transfer: Scaling up processes from laboratory to commercial manufacturing is streamlined, requiring no manual adjustments.
The presentation will provide an overview of the project timeline, from the pilot phase to the full automation of 600 modules according to the MTP standard. We will also showcase a video demonstrating the steps a laboratory engineer takes to reconfigure an experiment setup, from integrating "MTP ready" modules to process orchestration and control application generation to execution. This will offer a clear understanding of the practical application and benefits of this technology.
1415 – 1445
Pharma 4.0 Case Studies and Lessons Learned
Marcel Kraft, Bayer
A rapid and resource-efficient synthesis of new drug candidates in chemical-pharmaceutical research is of crucial importance for the successful development of new drugs.
By specifically adapting the reaction conditions can be enabled or yields can be optimized. The search for optimal reaction conditions is the task of catalyst screening labs, which today already work in a highly parallel and automated manner with high-throughput experimentation in all research-based pharmaceutical companies. However, there is still significant optimization potential in the area of digitization of workflows, from campaign planning to the control of robot systems to the automated evaluation of the screens and the seamless integration of modern AI methods for predicting optimal conditions. Based on the ongoing works in the Catalyst Screening Lab in the Bayer R&D Center in Wuppertal, this work presents a comprehensive investigation of the possible uses and limitations of automated workflows in chemical research, especially but not limited to the context of HTE in catalyst screening. The collected data and analyses of these provide several key insights into the following questions:
- How can historical laboratory data be prepared for machine learning and what value does it represent?
- What might be a pragmatic approach to integrating AI into an automated laboratory?
- What problems exist with AI models and how can they be overcome with an interdisciplinary approach (Engineering perspective)?
- How much effort is involved in holistic digitization of HTE laboratory workflows and what are the benefits?
- How ca engineering make in impact in R&D workflows?
By specifically adapting the reaction conditions can be enabled or yields can be optimized. The search for optimal reaction conditions is the task of catalyst screening labs, which today already work in a highly parallel and automated manner with high-throughput experimentation in all research-based pharmaceutical companies. However, there is still significant optimization potential in the area of digitization of workflows, from campaign planning to the control of robot systems to the automated evaluation of the screens and the seamless integration of modern AI methods for predicting optimal conditions. Based on the ongoing works in the Catalyst Screening Lab in the Bayer R&D Center in Wuppertal, this work presents a comprehensive investigation of the possible uses and limitations of automated workflows in chemical research, especially but not limited to the context of HTE in catalyst screening. The collected data and analyses of these provide several key insights into the following questions:
- How can historical laboratory data be prepared for machine learning and what value does it represent?
- What might be a pragmatic approach to integrating AI into an automated laboratory?
- What problems exist with AI models and how can they be overcome with an interdisciplinary approach (Engineering perspective)?
- How much effort is involved in holistic digitization of HTE laboratory workflows and what are the benefits?
- How ca engineering make in impact in R&D workflows?
1445 – 1515
Pharma 4.0 Case Studies and Lessons Learned
Lasse Harloff-Helleberg, NovoNordisk
Bjarke Primdal-Bengtson, Novo Nordisk
In the pharmaceutical industry, the release of batches is a critical step in ensuring product quality and compliance with regulatory requirements. However, this process can be time-consuming, error-prone, and fragmented across multiple departments and systems.
To address these challenges, Novo Nordisk has implemented a global digital solution that enables the display of batch-related data and facilitates the evaluation, identification, and conclusion of any needed actions by QA.
This session will focus on key features, benefits, and implementation considerations of this digital solution for batch release, which has been crucial for optimization of the batch release process to our patients.
To address these challenges, Novo Nordisk has implemented a global digital solution that enables the display of batch-related data and facilitates the evaluation, identification, and conclusion of any needed actions by QA.
This session will focus on key features, benefits, and implementation considerations of this digital solution for batch release, which has been crucial for optimization of the batch release process to our patients.
Hear From Top Industry Thought Leaders on the Challenges and Solutions Impacting the Pharmaceutical Industry
Speaker Qualifications
Speakers selected to present at ISPE events are leading professionals in their fields. However, it may be necessary to make substitutions. Every possible effort will be made to substitute a speaker with comparable qualifications. Every precaution is taken to ensure accuracy. ISPE does not assume responsibility for information distributed or contained in these events, or for any opinion expressed.
Agenda Changes
Agenda is subject to change. Last minute changes due to functional, private, or organizational needs may be necessary. The event organizer accepts no liability for any additional costs caused by a change of the agenda.