Personalized Respiratory Medicine: Exploring the Horizon, Addressing the Issues. Summary of a BRN-AJRCCM Workshop Held in Barcelona on June 12, 2014

Abstract

This Pulmonary Perspective summarizes the content and main conclusions of an international workshop on personalized respiratory medicine coorganized by the Barcelona Respiratory Network (www.brn.cat) and the AJRCCM in June 2014. It discusses (1) its definition and historical, social, legal, and ethical aspects; (2) the view from different disciplines, including basic science,

Ashtma-Chronic obstructive pulmonary disease overlap syndrome (ACOS): current evidence and future research directions

“…In recent years, we have identified several phenotypes, which are subgroups of patients defined by different clinical characteristics, which have different prognosis or respond differently to treatments. More importantly, we have managed to divide some of these phenotypes to endotypes by identifying the underlying molecular pathways (typical example -a1 antitrypsin deficiency) [29,30]. Recently Agusti et al proposed a new holistic approach to the assessment and management of chronic airway disease, which is based exclusively on treatable traits in each patient [26].…”

A good asthma catch by professional fishing

“…I think not. These data represent the first steps in getting some grip on the biological complexities of asthma, which are no longer hidden now we are able to measure them [2,5]. Indeed, the inter-and perhaps even intra-subject variability is much larger than we would have liked, but let us be pleased: there is a lot of new signal amongst the inevitable noise!…”

“…The answer is clearly "yes". It requires carefully defining the concepts [5] and the high-throughput "omics" methodologies [6]. Has it been embraced generally yet?…”

Personalised medicine: are we ready?

“…In addition, static measurements ("omics") are certainly not sufficient to understand the underlying dynamics of interactions that occur with varying time and spatial scales: at some point modelling tools are required since relations are mostly nonlinear, making straight inferences hazardous. Addressing this complexity is what systems or networks biology and medicine try to do, using bioinformatic tools and knowledge engineering to transform data into understanding and ultimately gain the ability to modulate individual target mechanisms to treat each patient more effectively, which is one fundamental goal of personalised medicine [12][13][14].…”