Azithromycin for Chronic Obstructive Pulmonary Disease: A Patient-tailored Prescription

Azithromycin, a macrolide antibiotic with well documented antiinflammatory

properties, is recommended as a second-line treatment

in COPD-patients with frequent acute exacerbations. It is often used

in clinical practice and it has proven to significantly reduce

exacerbation rate and increase the inter-exacerbation interval. Yet,

not all patients seem to equally benefit and there are safety concerns

with its long-term use, like cardiotoxicity, ototoxicity and the induction

of macrolide resistance. It is currently unclear, which patient traits are

most decisive to determine treatment success or treatment failure.

Aided by state-of-the-art machine learning algorithms, we aim to

predict which COPD patients are most likely to respond to

azithromycin treatment, and uncover the biological mechanisms that

drive this response. Due to azithromycin’s pleiotropic actions, this will

provide valuable insights for further differentiation of distinct COPD

phenotypes. Most importantly however, it will have a direct clinical

impact by avoiding unnecessary exposure of a vulnerable patient

population to azithromycin’s adverse effects, while also strengthening

confidence in its prescription for patients that truly benefit.