Model-based systems engineering for life-sciences instrumentation development

Patou, François and Dimaki, Maria and Maier, Anja and Svendsen, Winnie E. and Madsen, Jan (2019) Model-based systems engineering for life-sciences instrumentation development. Systems Engineering, 22 (2). pp. 98-113. ISSN 1520-6858 (https://doi.org/10.1002/sys.21429)

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Abstract

Next‐generation genome sequencing machines and Point‐of‐Care (PoC) in vitro diagnostics devices are precursors of an emerging class of Cyber‐Physical Systems (CPS), one that harnesses biomolecular‐scale mechanisms to enable novel "wet‐technology" applications in medicine, biotechnology, and environmental science. Although many such applications exist, testifying the importance of innovative life‐sciences instrumentation, recent events have highlighted the difficulties that designing organizations face in their attempt to guarantee safety, reliability, and performance of this special class of CPS. New regulations and increasing competition pressure innovators to rethink their design and engineering practices, and to better address the above challenges. The pace of innovation will be determined by how organizations manage to ensure the satisfaction of aforementioned constraints while also streamlining product development, maintaining high cost‐efficiency and shortening time‐to‐market. Model‐Based Systems Engineering provides a valuable framework for addressing these challenges. In this paper, we demonstrate that existing and readily available model‐based development frameworks can be adopted early in the life‐sciences instrumentation design process. Such frameworks are specifically helpful in describing and characterizing CPS including elements of a biological nature both at the architectural and performance level. We present the SysML model of a smartphone‐based PoC diagnostics system designed for detecting a particular molecular marker. By modeling components and behaviors spanning across the biological, physical‐nonbiological, and computational domains, we were able to characterize the important systemic relations involved in the specification of our system's Limit of Detection. Our results illustrate the suitability of such an approach and call for further work toward formalisms enabling the formal verification of systems including biomolecular components.

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