Model-based systems engineering for life-sciences instrumentation development

Research output: Contribution to journalJournal articleResearchpeer-review

294 Downloads (Pure)

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.

Original languageEnglish
JournalSystems Engineering
Volume22
Issue number2
Pages (from-to)98-113
Number of pages16
ISSN1098-1241
DOIs
Publication statusPublished - 2019

Keywords

  • Cyber-Physical Systems
  • Life-sciences
  • Model-based systems engineering
  • Model-based systemsdesign
  • Sensitivity analysis
  • SysML

Cite this

@article{5565e7e632af4e089bb2554d9b445d17,
title = "Model-based systems engineering for life-sciences instrumentation development",
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.",
keywords = "Cyber-Physical Systems, Life-sciences, Model-based systems engineering, Model-based systemsdesign, Sensitivity analysis, SysML",
author = "Fran{\cc}ois Patou and Maria Dimaki and Anja Maier and Svendsen, {Winnie Edith} and Jan Madsen",
year = "2019",
doi = "10.1002/sys.21429",
language = "English",
volume = "22",
pages = "98--113",
journal = "Systems Engineering",
issn = "1098-1241",
publisher = "JohnWiley & Sons, Inc.",
number = "2",

}

Model-based systems engineering for life-sciences instrumentation development. / Patou, François; Dimaki, Maria; Maier, Anja; Svendsen, Winnie Edith; Madsen, Jan.

In: Systems Engineering, Vol. 22, No. 2, 2019, p. 98-113.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Model-based systems engineering for life-sciences instrumentation development

AU - Patou, François

AU - Dimaki, Maria

AU - Maier, Anja

AU - Svendsen, Winnie Edith

AU - Madsen, Jan

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Cyber-Physical Systems

KW - Life-sciences

KW - Model-based systems engineering

KW - Model-based systemsdesign

KW - Sensitivity analysis

KW - SysML

U2 - 10.1002/sys.21429

DO - 10.1002/sys.21429

M3 - Journal article

VL - 22

SP - 98

EP - 113

JO - Systems Engineering

JF - Systems Engineering

SN - 1098-1241

IS - 2

ER -