title: Phenotype, endotype and patient-specific computational modelling for optimal treatment design in asthma.
abstract: Understanding and treatment of asthma is significantly complicated by the heterogeneous spectrum of phenotypes associated with the disease. Recent advances in phenotype classification promise more targeted therapies, but these categories are based on constellations of largely external measurements and are not necessarily indicative of underlying pathophysiology. We propose that computational modelling is a valuable tool that allows the disease spectrum to be decomposed not into phenotypes but rather into groups organized by underlying dysfunction, referred to by some authors as endotypes. By breaking down the asthmatic spectrum in this way, therapies can be targeted more directly to the underlying defects. This would be not only an important improvement in its own right, but also an important step toward the ultimate goal of patient-specific modelling.
authors.affiliation: Department of Mathematics, University of Auckland, Auckland 1142, New Zealand.
authors.forename: Graham M
authors.initials: GM
authors.lastname: Donovan
authors.affiliation: Auckland Bioengineering Institute, University of Auckland, Auckland 1142, New Zealand.
authors.forename: Merryn H
authors.initials: MH
authors.lastname: Tawhai
keywords: airway hyper responsiveness; multiscale modelling