In silico clinical trials (ISCTs) may reduce risks of automated ventilation by evaluating performance across physiologic variability with traceable model credibility. We present a case study using a patient–device model (PDM) to assess an automated weaning function in ICU patients. The workflow defines the question of interest, context of use, cohort/scenario generation, sampling, execution, and analysis. A virtual ICU cohort captures variability in demographics and pathophysiology (ARDS, COPD, postoperative, neuromuscular, cardiopulmonary) using literature-based parameters. Nine scenarios test robustness, including elastance/resistance steps, drive shifts, shunt/dead-space increases, and sedation taper. Primary endpoints are time in target for tidal volume (VT), respiratory rate (RR), and end-tidal CO2 (etCO?), excursion durations, and overshoot. Respiratory rate and etCO? remained ?80% in target, while VT only remained in target range about 50 % due to narrow protective bounds. This compact ISCT provides a credibility-aware framework for evaluation of automated protocols, shown here as an example for weaning.
Hennigs et al. (Tue,) studied this question.