Pirfenidone for Idiopathic Pulmonary Fibrosis and Beyond

Abstract

Pirfenidone (PFD) slows the progression of idiopathic pulmonary fibrosis (IPF) by inhibiting the exaggerated fibrotic response and possibly through additional mechanisms, such as anti-inflammatory effects. PFD has also been evaluated in other fibrosing lung diseases. Myocardial fibrosis is a common feature of several heart diseases and the progressive deposition of extracellular matrix due to a persistent injury to cardiomyocytes may trigger a vicious cycle that leads to persistent structural and functional alterations of the myocardium. No primarily antifibrotic medications are used to treat patients with heart failure. There is some evidence that PFD has antifibrotic actions in various animal models of cardiac disease and a phase II trial on patients with heart failure and preserved ejection fraction has yielded positive results. This review summarises the evidence about the possible mechanisms of IPF and modulation by PFD, the main results about IPF or non-IPF interstitial pneumonias and also data about PFD as a potential protective cardiac drug.

Left-sided heart failure burden and mortality in idiopathic pulmonary fibrosis: a population-based study

“…As antifibrotics are prescribed in tertiary care, we did not have access to antifibrotic use data in CPRD Aurum and therefore were unable to explore this potential association. Interestingly however, antifibrotics have been shown to have cardioprotective properties within the context of HFpEF, albeit this has not been explored specifically in the context of comorbid IPF and HF [ 28 , 29 ]. To lend further support to a possible association between the use of antifibrotics and the modest reduction left-sided HF incidence noted in this study, pirfenidone was licensed in the UK by NICE (National Institute of Clinical Excellence) in 2013 and nintedanib in 2016 and it is interesting to note in our data that it is more from 2017 onwards that a sustained reduction in the left-sided HF incidence rate is noted (Fig.…”

“…Based on our estimates, left-sided HF prevalence is approximately 30-fold higher and incidence is almost 12-fold higher in IPF patients than in the general UK population [ 12 ]. Comparison of HF prevalence estimates between IPF and COPD patients is more challenging due to heterogeneity in published estimates, with estimates ranging between 5 and 41% in different COPD cohorts [ 28 ]. Assuming that estimates for community-based populations lie towards the lower end of this range, left-sided HF prevalence may be considerably higher in IPF than COPD patients.…”

“…Given the rising incidence of IPF both in the UK and globally as well as the rising absolute burden of HF in the UK population over time, understanding the scale of the problem in IPF is important to guide appropriate allocation of healthcare resources to address the management of co-morbidities, with this having been shown to be key to optimising IPF survival [ 13 , 27 ]. Furthermore, the treatment landscape of IPF has changed considerably in the last decade, including the introduction of antifibrotic therapies such as pirfenidone and nintedanib in 2013 and 2016 in the UK, respectively, which have been shown to have some cardioprotective properties outside the context of IPF [ 28 , 29 ] and the discontinuation of long-term use of medications with a cardiovascular risk profile such as steroids following deleterious outcomes in the PANTHER-IPF trial in 2012 [ 30 ]. In the absence of any temporal data on the burden of left -sided HF in IPF patients, it is unknown whether this has changed over time in response to changing treatment patterns.…”

De Novo Prediction of Drug Targets and Candidates by Chemical Similarity-Guided Network-Based Inference

“…As an example, we generated target predictions for nintedanib and pirfenidone, two drugs with antifibrotic properties, which are used to treat idiopathic pulmonary fibrosis [ 50 , 51 ]. Predictions were generated with SimSpread against our complete ChEMBL28 dataset (1815 drugs & clinical candidates; 1069 targets), and neither drug was included in the prediction network.…”

“…Nintedanib is a tyrosine kinase inhibitor, and several of its known pharmacological targets were identified by SimSpread ( Table S22 ): Vascular endothelial growth factor receptor (VEGFR-1, -2, and -3), fibroblast growth factor receptor (FGFR1, -2 and -3), platelet-derived growth factor receptor (PDGFR- and - ), receptor tyrosine kinase FLT-3 and non-receptor tyrosine kinases Lck, Lyn, and Src [ 50 ]. The precise molecular targets of pirfenidone are not known [ 51 ], and we include the top-15 predictions for interest ( Table S22 ).…”