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Biomarkers for Idiopathic Pulmonary Fibrosis
Lessons learned from combining novel approaches in clinical research
Hassan Bencheqroun, MD, FCCP, Senior Medical Director and Strategy Lead, Respiratory and Allergy Center Of Excellence (COE), IQVIA
Apr 03, 2024
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Idiopathic pulmonary fibrosis (IPF) is a deadly disease with a poor prognosis,1 involving disabling symptoms and progressive loss of lung function.2 IPF affects around 100,000 people in the US, and millions worldwide.2 Incidence and prevalence are rising globally, a trend that predates COVID-19.3 The two U.S. Food and Drug Administration (FDA)-approved treatments slow IPF disease progression but do not stop or reverse lung fibrosis, and are poorly tolerated by a substantial number of patients.2 This leaves a pressing need for improved therapies, and for novel approaches to demonstrate their value. Biomarkers have potential to improve clinical trials by enabling tracking of outcomes of most importance to patients, as well as by identifying subpopulations that may respond differently to therapies (Sidebar 1) Biomarkers for IPF are related to processes including alveolar epithelial cell dysfunction, immune dysregulation, fibroproliferation, fibrogenesis, and extracellular matrix remodeling4 (Sidebar 2).

Sidebar 1
Biomarkers: A definition
Biomarkers are defined as characteristics that are objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes or pharmacologic responses to a therapeutic intervention. (4)

Sidebar 2

Idiopathic Pulmonary Fibrosis (IPF) biomarkers

Based on published data5, the Prognostic Lung Fibrosis Consortium (PROLIFIC) has selected 12 potential prognostic, blood-based protein biomarkers to help predict which pulmonary fibrosis patients might respond to a particular therapy. These include markers of:

  • Epithelial damage (CYFRA 21-1, SP-D, CA-19-9, KL-6)
  • Fibrosis (MMP-7, tenascin C, periostin)
  • Inflammation (CCL18, CXCL13, slCAM1)
  • Thrombosis (PAI-1)

Biomarkers are essential tools for personalized patient management in IPF, such as early detection, diagnosis, prognosis, therapy selection, and research outcomes. IPF biomarker research would aim to identify patients at risk of developing IPF, classify the disease subtype and severity, the subpopulation that may respond differently to therapies, predict the disease course and progression, select the most suitable therapeutic modality, monitor its response, and identify novel treatment targets that can improve the quality of life and survival of IPF patients. Biomarkers once validated would serve as clinical endpoints in clinical trials, some of which must be of meaningful clinical importance to patients. Patient surveys are a helpful source of information on clinical trial outcomes that matter most. For example, for IPF patients, control of chronic cough may of more clinical significance than the FVC decline which is currently the main outcome in trial. Equally, the ability to walk further (as measured by the six-minute walk test) may need to focus on clinically meaningful . Patients are also keen to understand their prognosis, and how likely they are to respond to medications. Efforts can then be made to align outcome metrics with this patient feedback.

Three key learnings on the potential role of biomarkers

Based on IPF studies to date, lessons learned fall into three categories:

  1. Validating outcomes:This a vital step for IPF clinical trials, ensuring that the metrics used accurately reflect the desired outcome. For example, an outcome measured may be report of tiredness, yet rather than being negative, may in fact indicate that the patient is still functional. Leveraging partnerships with key opinion leaders (KOLs) helps ensure that outcomes measure what they are intended to measure. End-points are typically validated in a sample population before using in larger clinical trials, and validating it in other population. For biomarkers, validation and showing a correlation with a clinical outcome are major steps, together with gaining patient feedback on usability and practicality of methods of tracking biomarkers, such as devices. The reproducibility of biomarkers should be validated in a variety of populations and settings, at various times. This data is then presented to regulators to gain input on their acceptability for use in trials; one initial option may be to use a biomarker as an exploratory outcome for a preplanned trial to gain enough data to justify its ultimate use as a secondary or even primary outcome measure.
  2. Ethical considerations: These include the possibility of inadvertent downstream consequences for clinical trial participants who are found to carry a particular biomarker. These might include potential discrimination such as refusal of coverage by health or life insurance companies. While biomarkers may offer diagnostic and therapeutic benefits, efforts must be made to anticipate the risk landscape for patients and provide all possible protections. This includes balancing the need for research collaboration, and potential sharing of deidentified data, with the study participant’s right to privacy under the Health Insurance Portability and Accountability Act (HIPAA). Anonymizing biomarkers and creating digital fences around them during collaborative research are steps towards addressing these concerns. In the meantime, various task forces involving regulators, patient advocacy groups and researchers are debating the best way forward in addressing ethical considerations linked to biomarkers. IQVIA positions itself as a partner in committees and consortia to provide data and input for such vital discussions.
  3. Need for data on patient-centric outcomes: Data is a core element of any clinical trial, and patient-centric outcomes must go hand-in-hand with biomarker discovery. Keeping patient perspectives at the forefront of study design can help ensure that trials are able to demonstrate the impact of potential therapies on these high priority outcomes. Digital biomarkers are also being investigated for IPF, with the aim of capturing outcomes during the natural progression of the disease. In one potential project, the distance walked by patients is being tracked using actigraphy as a potential alternative to the six-minute walk test (6MWT). Initially, both digital tracking and the 6MWT are being used to monitor movement, enabling comparison of the two methods in the same patients. However, use of a device may add to patient burden in this vulnerable and frail study population, as well as increasing site burden. Issues for patients include the need for continuous internet access to avoid missing data that might lead to bias in the study results. Patients may also need to troubleshoot the digital technology, while for sites, the devices must be seamlessly connected to the electronic data capture system while protecting privacy in compliance with HIPAA.

Exciting advances are taking place in IPF clinical research, with multiple resources being combined in clinical trials, including digital technologies, various imaging modalities, and genetic testing. With patient needs firmly at the center of decision-making, these resources hold promise to help solve the puzzle of this poorly understood yet devastating disease.

References

1 Du K, Zhu Y, Mao R. et al. Medium-long term prognosis prediction for idiopathic pulmonary fibrosis patients based on quantitative analysis of fibrotic lung volume, Respir Res 23, 372 (2022).

2 Podolanczuk AJ, Richeldi L, Martinez FJ. The Future of Clinical Trials in Idiopathic Pulmonary Fibrosis, JAMA. 2023;329(18):1554–1555. doi:10.1001/jama.2022.23955

3 Pergolizzi JV Jr, LeQuang JA, Varrassi M, Breve F, Magnusson P, Varrassi G. What Do We Need to Know About Rising Rates of Idiopathic Pulmonary Fibrosis? A Narrative Review and Update. Adv Ther. 2023 Apr;40(4):1334-1346. doi: 10.1007/s12325-022-02395-9. Epub 2023 Jan 24. PMID: 36692679; PMCID: PMC9872080.

4 Biomarkers Definitions Working Group.. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001 Mar;69(3):89-95. doi: 10.1067/mcp.2001.113989. PMID: 11240971. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8230407

5 https://www.pulmonaryfibrosis.org/prolific/about-us

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