(164c) Enhancing Human Performance with Human-Centric Hmis in mRNA Manufacturing

The integration of digital twin technology in the biopharmaceutical sector, especially mRNA manufacturing, is revolutionizing manufacturing processes by offering insights into real-time operations and enabling predictive modeling (Scheper et al., 2021). However, this advancement also introduces significant complexities for human operators, who play a critical role in monitoring and intervening in the manufacturing process. These operators are further tasked with upholding the stringent quality and safety standards mandated by Good Manufacturing Practices (GMP). Human errors account for approximately 50% of all quality incidents (Wilson et al., 2015) and related problems within the pharmaceutical industry. Often, these errors are linked to complex automation strategies that overload operators with information and use sophisticated Human-Machine Interfaces (HMIs) beyond their capacity, complicating their understanding of processes (Nazir et al., 2014). Therefore, it became imperative to enhance human performance in biopharma manufacturing (Wismer et al., 2021). This work aims to develop a human-centric HMI for the continuous mRNA process, based on human factors principles, to significantly improve operator performance. By doing so, we intend to address the dual challenges of system complexity and human error.

The development of the human-centric HMI employs a multifaceted strategy, aligned with human factors principles to optimize the operator's interaction with the technology. First, we identify the operator's tasks and cognitive workflows in the continuous mRNA process to identify areas where digital twin technology can most effectively reduce cognitive load and enhance decision-making. This involves mapping out the entire mRNA process (including upstream and downstream processes) to pinpoint where real-time data and predictive analytics can provide significant benefits. Subsequently, we design an intuitive Human-Machine Interface (HMI) that serves as the primary interaction point between operators and the digital twin. This HMI is designed to present data in an accessible and understandable format, utilizing visual aids, simplified dashboards, and actionable alerts that guide operators through the decision-making process. The interface design adheres to established ergonomic and cognitive engineering principles. By integrating these strategies, the proposed human-centric HMI aims to minimize the risk of human error while maximizing operational efficiency and adherence to GMP standards. Moreover, it can serve as a testbed for future human factors research in biopharma and a tool for operator training (Wismer et al., 2021).

Keywords: mRNA, human error, biopharma, human-machine interface, digital twin

Acknowledgments: This research was supported by the U.S. Food and Drug Administration under the FDA BAA-22-00123 program, Award Number 75F40122C00200.

References

Scheper, T., Beutel, S., McGuinness, N., Heiden, S., Oldiges, M., Lammers, F., & Reardon, K. F. (2021). Digitalization and bioprocessing: Promises and challenges. Digital Twins: Tools and Concepts for Smart Biomanufacturing, 57-69.

Herwig, C., Pörtner, R., & Möller, J. (Eds.). (2021). Digital Twins: tools and concepts for smart biomanufacturing. Cham: Springer International Publishing.

Wilson, A., Moedler, M., & McAuley, G. (2015). Changing the Performance Paradigm in Pharma/Biotech: Integrating Human Performance in Global Organizations. PDA Journal of Pharmaceutical Science and Technology, 69(5), 658-665.

Wismer, P., Lopez Cordoba, A., Baceviciute, S., Clauson-Kaas, F., & Sommer, M. O. A. (2021). Immersive virtual reality as a competitive training strategy for the biopharma industry. Nature Biotechnology, 39(1), 116-119.