Merryn Tawhai, Ph.D.


TawhaiMerryn Tawhai, Ph.D. is Professor of Bioengineering at the University of Auckland, New Zealand. She is Deputy Director of the University’s Auckland Bioengineering Institute (ABI), Deputy Director of the Medical Technologies Centre of Research Excellence, and an Associate Deputy Vice Chancellor (Research). At the ABI, Professor Tawhai has established a world-leading research programme in applied computational physiology of the lung. Her research is focused on the development of integrative computational models of the pulmonary system and their application in understanding structure-function interactions in normal physiology and in the pathophysiology of pulmonary disease. Her research has established novel methods for predictive modeling of structure-function relationships in the lung. These methods have been used to study individual patient response to thrombotic pulmonary embolism, to force development across the bronchial airways during bronchoconstriction, patient-specific response to respiratory support therapies, and the influence of older age on lung function.

Patient-specific model-based assessment of lung function in the clinical setting

Abstract: Mechanical ventilation (MV) is a primary therapy for intensive care unit (ICU) patients, providing external support to assist with breathing when the patient is at risk of airway or tissue closure or collapse, or when the drive to breathe is compromised. Up to ~60% of all ICU patients require MV, and this patient group stays 50-100% longer in the ICU. When MV-associated damage to the lung develops, this further increases the ICU stay, complicates patient management, and has long term consequences for patient quality of life. Patient-specific characteristics and distribution of injury and/or underlying disease means that MV patient response to therapy is highly variable, and thus a “one size fits all” protocol to standardise care is not appropriate. Current clinical practice relies heavily on subjective assessment of the patient (“clinician experience”), and less on objective assessment of patient data. So, while therapy is specific to each patient, the care itself is not ‘patient-specific’ and often doesn’t take  account of the individual, transient needs of the patient, nor their respiratory status as it evolves in response to injury and treatment. What is needed is the ability to quantify and monitor the patient-specific state of the lung with regard to MV care, and the ability to do so at every breath so that the clinical team can be alerted to changes in patient response as soon as they occur. We are developing and validating new patient-specific model-based technologies that are aimed at minimising lung damage in MV, identifying patients who are at risk of developing lung injury, and titrating ventilation protocols for individual patients to optimise desired clinical endpoints. To this end, we are integrating advanced biophysically-based computational models of patient-specific lung function with clinical decision-support software. This presentation will explain the role of these computational models in optimising MV therapy, as well as other areas of clinically-relevant application.