The value of imaging and clinical outcomes in a phase II clinical trial of a lysophosphatidic acid receptor antagonist in idiopathic pulmonary fibrosis

Pulmonary Fibrosis and Diabetes Mellitus: Two coins with the same face

Idiopathic pulmonary fibrosis (IPF) constitutes a long-term disease with a complex pathophysiology composed of multiple molecular actors that lead to the deposition of extracellular matrix, the loss of pulmonary function and ultimately the patient's death. Despite the approval of pirfenidone and nintedanib for the treatment of the disease, lung transplant is the only long-term solution to fully recover the respiratory capacity and gain quality of life. One of the risk factors for the development of IPF is the pre-existing condition of diabetes mellitus. Both, IPF and diabetes mellitus, share similar pathological damage mechanisms, including inflammation, endoplasmic reticulum stress, mitochondrial failure, oxidative stress, senescence and signaling from glycated proteins through receptors. In this critical review article, we provide information about this interrelationship, examining molecular mediators that play an essential role in both diseases and identify targets of interest for the development of potential drugs. We review the findings of clinical trials examining the progression of IPF and how novel molecules may be used to stop this process. The results highlight the importance of early detection and addressing multiple therapeutic targets simultaneously to achieve better therapeutic efficacy and potentially reverse lung fibrosis.

Meaningful Endpoints for Idiopathic Pulmonary Fibrosis (IPF) Clinical Trials: Emphasis on 'Feels, Functions, Survives'. Report of a Collaborative Discussion in a Symposium with Direct Engagement from Representatives of Patients, Investigators, the National Institutes of Health, a Patient Advocacy Organization, and a Regulatory Agency

Background: Idiopathic pulmonary fibrosis (IPF) carries significant mortality and unpredictable progression, with limited therapeutic options. Designing trials with patient-meaningful endpoints, enhancing the reliability and interpretability of results, and streamlining the regulatory approval process are of critical importance to advancing clinical care in IPF. Methods: A landmark in-person symposium in June 2023 assembled 43 participants from the US and internationally, including patients with IPF, investigators, and regulatory representatives, to discuss the immediate future of IPF clinical trial endpoints. Patient advocates were central to discussions, which evaluated endpoints according to regulatory standards and the FDA's 'feels, functions, survives' criteria. Results: Three themes emerged: 1) consensus on endpoints mirroring the lived experiences of patients with IPF; 2) consideration of replacing forced vital capacity (FVC) as the primary endpoint, potentially by composite endpoints that include 'feels, functions, survives' measures or FVC as components; 3) support for simplified, user-friendly patient-reported outcomes (PROs) as either components of primary composite endpoints or key secondary endpoints, supplemented by functional tests as secondary endpoints and novel biomarkers as supportive measures (FDA Guidance for Industry (Multiple Endpoints in Clinical Trials) available at: https://www.fda.gov/media/162416/download). Conclusions: This report, detailing the proceedings of this pivotal symposium, suggests a potential turning point in designing future IPF clinical trials more attuned to outcomes meaningful to patients, and documents the collective agreement across multidisciplinary stakeholders on the importance of anchoring IPF trial endpoints on real patient experiences-namely, how they feel, function, and survive. There is considerable optimism that clinical care in IPF will progress through trials focused on patient-centric insights, ultimately guiding transformative treatment strategies to enhance patients' quality of life and survival.

Pulmonary Fibrosis Stakeholder Summit: A Joint NHLBI, Three Lakes Foundation, and Pulmonary Fibrosis Foundation Workshop Report

Despite progress in elucidation of disease mechanisms, identification of risk factors, biomarker discovery, and the approval of two medications to slow lung function decline in idiopathic pulmonary fibrosis and one medication to slow lung function decline in progressive pulmonary fibrosis, pulmonary fibrosis remains a disease with a high morbidity and mortality. In recognition of the need to catalyze ongoing advances and collaboration in the field of pulmonary fibrosis, the NHLBI, the Three Lakes Foundation, and the Pulmonary Fibrosis Foundation hosted the Pulmonary Fibrosis Stakeholder Summit on November 8-9, 2022. This workshop was held virtually and was organized into three topic areas: 1) novel models and research tools to better study pulmonary fibrosis and uncover new therapies, 2) early disease risk factors and methods to improve diagnosis, and 3) innovative approaches toward clinical trial design for pulmonary fibrosis. In this workshop report, we summarize the content of the presentations and discussions, enumerating research opportunities for advancing our understanding of the pathogenesis, treatment, and outcomes of pulmonary fibrosis.

The potential role of artificial intelligence in the clinical practice of interstitial lung disease

Artificial intelligence (AI) is being widely applied in the field of medicine, in areas such as drug discovery, diagnostic support, and assistance with medical practice. Among these, medical imaging is an area where AI is expected to make a significant contribution. In Japan, as of November 2022, 23 AI medical devices have received regulatory approval; all these devices are related to image analysis. In interstitial lung diseases, technologies have been developed that use AI to analyze high-resolution computed tomography and pathological images, and gene expression patterns in tissue taken from transbronchial lung biopsies to assist in the diagnosis of idiopathic pulmonary fibrosis. Some of these technologies are already being used in clinical practice in the United States. AI is expected to reduce the burden on physicians, improve reproducibility, and advance personalized medicine. Obtaining sufficient data for diseases with a small number of patients is difficult. Additionally, certain issues must be addressed in order for AI to be applied in healthcare. These issues include taking responsibility for the AI results output, updating software after the launch of technology, and adapting to new imaging technologies. Establishing research infrastructures such as large-scale databases and common platforms is important for the development of AI technology: their use requires an understanding of the characteristics and limitations of the systems. CLINICAL TRIAL REGISTRATION: Not applicable.

Quantitative Imaging Metrics for the Assessment of Pulmonary Pathophysiology: An Official American Thoracic Society and Fleischner Society Joint Workshop Report

Multiple thoracic imaging modalities have been developed to link structure to function in the diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders three-dimensional maps of lung structures and may be combined with positron emission tomography (PET) to obtain dynamic physiological data. Magnetic resonance imaging (MRI) using ultrashort-echo time (UTE) sequences has improved signal detection from lung parenchyma; contrast agents are used to deduce airway function, ventilation-perfusion-diffusion, and mechanics. Proton MRI can measure regional ventilation-perfusion ratio. Quantitative imaging (QI)-derived endpoints have been developed to identify structure-function phenotypes, including air-blood-tissue volume partition, bronchovascular remodeling, emphysema, fibrosis, and textural patterns indicating architectural alteration. Coregistered landmarks on paired images obtained at different lung volumes are used to infer airway caliber, air trapping, gas and blood transport, compliance, and deformation. This document summarizes fundamental "good practice" stereological principles in QI study design and analysis; evaluates technical capabilities and limitations of common imaging modalities; and assesses major QI endpoints regarding underlying assumptions and limitations, ability to detect and stratify heterogeneous, overlapping pathophysiology, and monitor disease progression and therapeutic response, correlated with and complementary to, functional indices. The goal is to promote unbiased quantification and interpretation of in vivo imaging data, compare metrics obtained using different QI modalities to ensure accurate and reproducible metric derivation, and avoid misrepresentation of inferred physiological processes. The role of imaging-based computational modeling in advancing these goals is emphasized. Fundamental principles outlined herein are critical for all forms of QI irrespective of acquisition modality or disease entity.

Machine learning in radiology: the new frontier in interstitial lung diseases

Challenges for the effective management of interstitial lung diseases (ILDs) include difficulties with the early detection of disease, accurate prognostication with baseline data, and accurate and precise response to therapy. The purpose of this Review is to describe the clinical and research gaps in the diagnosis and prognosis of ILD, and how machine learning can be applied to image biomarker research to close these gaps. Machine-learning algorithms can identify ILD in at-risk populations, predict the extent of lung fibrosis, correlate radiological abnormalities with lung function decline, and be used as endpoints in treatment trials, exemplifying how this technology can be used in care for people with ILD. Advances in image processing and analysis provide further opportunities to use machine learning that incorporates deep-learning-based image analysis and radiomics. Collaboration and consistency are required to develop optimal algorithms, and candidate radiological biomarkers should be validated against appropriate predictors of disease outcomes.

LPA1 antagonist BMS-986020 changes collagen dynamics and exerts antifibrotic effects in vitro and in patients with idiopathic pulmonary fibrosis

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a debilitating lung disease with limited treatment options. A phase 2 trial (NCT01766817) showed that twice-daily treatment with BMS-986020, a lysophosphatidic acid receptor 1 (LPA₁) antagonist, significantly decreased the slope of forced vital capacity (FVC) decline over 26 weeks compared with placebo in patients with IPF. This analysis aimed to better understand the impact of LPA₁ antagonism on extracellular matrix (ECM)-neoepitope biomarkers and lung function through a post hoc analysis of the phase 2 study, along with an in vitro fibrogenesis model.

METHODS

Serum levels of nine ECM-neoepitope biomarkers were measured in patients with IPF. The association of biomarkers with baseline and change from baseline FVC and quantitative lung fibrosis as measured with high-resolution computed tomography, and differences between treatment arms using linear mixed models, were assessed. The Scar-in-a-Jar in vitro fibrogenesis model was used to further elucidate the antifibrotic mechanism of BMS-986020.

RESULTS

In 140 patients with IPF, baseline ECM-neoepitope biomarker levels did not predict FVC progression but was significantly correlated with baseline FVC and lung fibrosis measurements. Most serum ECM-neoepitope biomarker levels were significantly reduced following BMS-986020 treatment compared with placebo, and several of the reductions correlated with FVC and/or lung fibrosis improvement. In the Scar-in-a-Jar in vitro model, BMS-986020 potently inhibited LPA₁-induced fibrogenesis.

CONCLUSIONS

BMS-986020 reduced serum ECM-neoepitope biomarkers, which were previously associated with IPF prognosis. In vitro, LPA promoted fibrogenesis, which was LPA₁ dependent and inhibited by BMS-986020. Together these data elucidate a novel antifibrotic mechanism of action for pharmacological LPA₁ blockade. Trial registration ClinicalTrials.gov identifier: NCT01766817; First posted: January 11, 2013; https://clinicaltrials.gov/ct2/show/NCT01766817 .

Idiopathic pulmonary fibrosis: Current and future treatment

Objectives

Idiopathic pulmonary fibrosis (IPF) is a chronic fibrotic lung disease characterized by dry cough, fatigue, and progressive exertional dyspnea. Lung parenchyma and architecture is destroyed, compliance is lost, and gas exchange is compromised in this debilitating condition that leads inexorably to respiratory failure and death within 3–5 years of diagnosis. This review discusses treatment approaches to IPF in current use and those that appear promising for future development.

Data Source

The data were obtained from the Randomized Controlled Trials and scientific studies published in English literature. We used search terms related to IPF, antifibrotic treatment, lung transplant, and management.

Results

Etiopathogenesis of IPF is not fully understood, and treatment options are limited. Pathological features of IPF include extracellular matrix remodeling, fibroblast activation and proliferation, immune dysregulation, cell senescence, and presence of aberrant basaloid cells. The mainstay therapies are the oral antifibrotic drugs pirfenidone and nintedanib, which can improve quality of life, attenuate symptoms, and slow disease progression. Unilateral or bilateral lung transplantation is the only treatment for IPF shown to increase life expectancy.

Conclusion

Clearly, there is an unmet need for accelerated research into IPF mechanisms so that progress can be made in therapeutics toward the goals of increasing life expectancy, alleviating symptoms, and improving well‐being.