Drug therapies in severe asthma - the era of stratified medicine

Difficult-to-treat asthma affects up to 20% of patients with asthma and is associated with significant healthcare cost. It is an umbrella term that defines a heterogeneous clinical problem including incorrect diagnosis, comorbid conditions and treatment non-adherence; when these are effectively addressed, good symptom control is frequently achieved. However, in 3–5% of adults with difficult-to-treat asthma, the problem is severe disease that is unresponsive to currently available treatments. Current treatment guidelines advise the ‘stepwise’ increase of corticosteroids, but it is now recognised that many aspects of asthma are not corticosteroid responsive, and that this ‘one size fits all’ approach does not deliver clinical benefit in many patients and can also lead to side effects. The future of management of severe asthma will involve optimisation with currently available treatments, particularly corticosteroids, including addressing non-adherence and defining an ‘optimised’ corticosteroid dose, allied with the use of ‘add-on’ target-specific novel treatments. This review examines the current status of novel treatments and research efforts to identify novel targets in the era of stratified medicines in severe asthma.

A compendium of modelling techniques

This Integration Insight provides a brief overview of the most popular modelling techniques used to analyse complex real-world problems, as well as some less popular but highly relevant techniques. The modelling methods are divided into three categories, with each encompassing a number of methods, as follows: 1) Qualitative Aggregate Models (Soft Systems Methodology, Concept Maps and Mind Mapping, Scenario Planning, Causal (Loop) Diagrams), 2) Quantitative Aggregate Models (Function fitting and Regression, Bayesian Nets, System of differential equations / Dynamical systems, System Dynamics, Evolutionary Algorithms) and 3) Individual Oriented Models (Cellular Automata, Microsimulation, Agent Based Models, Discrete Event Simulation, Social Network
Analysis). Each technique is broadly described with example uses, key attributes and reference material.