Dr Sina Saffaran - University of Warwick

In an intensive care unit (ICU) environment the protocols used to manage patients on mechanical ventilators are based on large-scale clinical trials. Managing these requires periodic adjustments by clinicians, who are increasingly overloaded. To truly personalise care, swift, and frequent interventions need to be made as the patient’s condition evolves. This is a task that is impacted by the constraints of ICU care, such as clinician’s workload. For instance, recent studies reveal that vital targets for oxygen saturation in ventilated neonatal patients are met only 40% of the time.

Engineers recognise the transformative power of automation in improving system performance, enhancing safety, and reducing operator workload, for example in aircraft autopilots. By introducing automated systems capable of undertaking certain aspects of clinical workload, clinicians can focus on questions of higher-level treatment while enabling faster, personalised interventions for patients.

Dr Sina Saffaran’s Research Fellowship with the Academy gives him the opportunity to collaborate with a distinguished team of ICU professionals and engineers. Working with the University of Warwick, they aim to harness recent advancements in high-fidelity computational modelling, real-time lung measurement technologies, artificial intelligence, data analytics, and feedback control theory, to develop in silico demonstrators that compellingly illustrate the potential of advanced automation systems in revolutionising critical care across various clinical settings.