Can computer simulators accurately represent the pathophysiology of individual COPD patients?

Wenfei Wang, Anup Das, Tayyba Ali, Oanna Cole, Marc Chikhani, Mainul Haque, Jonathan G Hardman, Declan G Bates

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Abstract

Background - Computer simulation models could play a key role in developing novel therapeutic strategies for patients with chronic obstructive pulmonary disease (COPD) if they can be shown to accurately represent the pathophysiological characteristics of individual patients.

Methods - We evaluated the capability of a computational simulator to reproduce the heterogeneous effects of COPD on alveolar mechanics as captured in a number of different patient datasets.

Results - Our results show that accurately representing the pathophysiology of individual COPD patients necessitates the use of simulation models with large numbers (up to 200) of compartments for gas exchange. The tuning of such complex simulation models ‘by hand’ to match patient data is not feasible, and thus we present an automated approach based on the use of global optimization algorithms and high-performance computing. Using this approach, we are able to achieve extremely close matches between the simulator and a range of patient data including PaO2, PaCO2, pulmonary deadspace fraction, pulmonary shunt fraction, and ventilation/perfusion (V̇/Q) curves. Using the simulator, we computed combinations of ventilator settings that optimally manage the trade-off between ensuring adequate gas exchange and minimizing the risk of ventilator-associated lung injury for an individual COPD patient.

Conclusions - Our results significantly strengthen the credibility of computer simulation models as research tools for the development of novel management protocols in COPD and other pulmonary disease states.
Original languageEnglish
Article number23
JournalIntensive Care Medicine Experimental
Volume2
Issue number1
DOIs
Publication statusPublished - 20 Sep 2014

Keywords

  • RCUK
  • EPSRC
  • MRC
  • EP/F057016/2
  • EP/F057059/1
  • EP/1036680/2
  • G1002017
  • MR/K019783

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