Semin Respir Crit Care Med 2022; 43(03): 335-345
DOI: 10.1055/s-0042-1744446
Review Article

Modeling Mechanical Ventilation In Silico—Potential and Pitfalls

David M. Hannon
1   Anesthesia and Intensive Care Medicine, School of Medicine, NUI Galway, Ireland
,
Sonal Mistry
2   School of Engineering, University of Warwick, Coventry, United Kingdom
,
Anup Das
2   School of Engineering, University of Warwick, Coventry, United Kingdom
,
Sina Saffaran
3   Faculty of Engineering Science, University College London, London, United Kingdom
,
John G. Laffey
1   Anesthesia and Intensive Care Medicine, School of Medicine, NUI Galway, Ireland
,
Bindi S. Brook
4   School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom
,
Jonathan G. Hardman
5   Anesthesia and Critical Care, Injury Inflammation and Recovery Sciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
6   Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
,
Declan G. Bates
2   School of Engineering, University of Warwick, Coventry, United Kingdom
› Institutsangaben

Funding D.M.H. has received support through the College of Anesthesiologists of Ireland (CAI) Research Fellowship 2021, funded by Abbvie. D.G.B. and J.G.H. acknowledge funding from Engineering and Physical Sciences Research Council (EPSRC) (EP/P023444/1 and EP/V014455/1).
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Abstract

Computer simulation offers a fresh approach to traditional medical research that is particularly well suited to investigating issues related to mechanical ventilation. Patients receiving mechanical ventilation are routinely monitored in great detail, providing extensive high-quality data-streams for model design and configuration. Models based on such data can incorporate very complex system dynamics that can be validated against patient responses for use as investigational surrogates. Crucially, simulation offers the potential to “look inside” the patient, allowing unimpeded access to all variables of interest. In contrast to trials on both animal models and human patients, in silico models are completely configurable and reproducible; for example, different ventilator settings can be applied to an identical virtual patient, or the same settings applied to different patients, to understand their mode of action and quantitatively compare their effectiveness. Here, we review progress on the mathematical modeling and computer simulation of human anatomy, physiology, and pathophysiology in the context of mechanical ventilation, with an emphasis on the clinical applications of this approach in various disease states. We present new results highlighting the link between model complexity and predictive capability, using data on the responses of individual patients with acute respiratory distress syndrome to changes in multiple ventilator settings. The current limitations and potential of in silico modeling are discussed from a clinical perspective, and future challenges and research directions highlighted.

#Equal contributions.




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Artikel online veröffentlicht:
21. April 2022

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