The CRONIC-PPF Faculty

	Florian SINGER Ass.-Prof. Priv.-Doz. Dr. med. univ., PhD Children at risk of fibrotic lung disease – a prospective observational cohort study involving public
Associate Professor, Deputy Head, Senior Consultant Division of Paediatric Pulmonology and Allergology, Department of Paediatrics and Adolescent Medicine, Medical University of Graz, Auenbruggerplatz 34/2, 8036 Graz Phone: +43-316-385 12612, ✉ e-mail WWW: Forschungsportal Med Uni Graz ORCID: 0000-0003-0518-9079 PubMed: PubMed (nih.gov)
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Florian Singer is a clinician scientist trained in Paediatric Pulmonology and Allergology, Epidemiology and Public Health. His research focusses on development, validation, and application of lung physiology biomarkers for the identification of treatable traits. He has recently shown that in vivo measurement of ventilation inhomogeneity, a biomarker of small airway disease, predicts survival in people with muco-obstructive and restrictive lung disease. Currently, he is setting up a trial using ventilation inhomogeneity to tailor treatment approaches.

Project

Research interests

1. Ventilation inhomogeneity is a hallmark of small airways disease, characterizing early stages of chronic progressive lung diseases. We were involved in the development and validation of multiple-breath washout (MBW) systems (Singer et al., 2011 [↗]; Singer et al., 2013 [↗]) and contributed to current MBW measurement protocols. Recently, our group demonstrated, that increased ventilation inhomogeneity is (i) a feature of fibrotic lung disease (Nyilas et al., 2018 [↗]) (ii) pulmonary exacerbations (Singer et al., 2021 [↗]) and (iii) is a risk factor of premature death in people with muco-obstructive lung disease (Kurz et al., 2022 [↗]) Ventilation inhomogeneity measured by MBW and functional magnetic resonance imaging (fMRI) (Nyilas et al., 2022 [↗]) remains to be explored as early biomarker in children at risk of fibrotic lung disease.
2. Latent class analysis (LCA) is a novel yet powerful statistical finite mixture model which infers unobserved, or “latent”, groups from patterns of the observed variables or “indicators” used in the modelling. Currently we apply LCA to integrate complex biomarkers sampled both at single point in time and across several observations. (Schaffer et al., 2024 [↗];
3. Public Patient Involvement (PPI) is increasingly acknowledged by the society as research deliverables should be tailored to the individuals' needs. In 2025, we are establishing a PPI program cluster including experts and caregivers of children with muco-obstructive lung disease and submitted a literature review.

04.04.2026 CRONIC-PPF · Doctoral Programme “Clinical & Research Oriented Network for Innovative Classification of Progressive Pulmonary Fibrosis”