Clinical Research Directory

Partitioned Training of Patients With Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a lung disease that limits the ability to breathe enough for a good workout. One way to improve the exercise training is to reduce the number of muscles being trained together. By training one leg at a time, the patient does not have to breathe as much allowing each leg a better workout. Our groundwork suggests it may work in patients with IPF. This study will help decide whether one-legged exercise training is better at improving a patient's exercise endurance compared to the usual way of exercising with both legs at the same time.

BPF Genetics of ILD Study

The investigators aim to examine the genetic determinants of interstitial lung disease in a cohort of subjects with regular exposure to pigeons, a known cause of one form of interstitial lung disease known as hypersensitivity pneumonitis. In addition we will examine immunological causes for hypersensitivity pneumonitis in this group. We anticipate our work will provide insights of use to clinicians and patients with hypersensitivity pneumonitis and other interstitial lung diseases.

A Study to Evaluate Safety, Tolerability and Pharmacokinetics of RSN0402 in Healthy Volunteers

This is a phase 1, randomized, First in Human (FIH), double-blinded, placebo-controlled study to assess the safety, tolerability, and PK of RSN0402 in healthy volunteers. A total of about 72 participants are expected to be enrolled.

Deep Learning Diagnostic and Risk-stratification for IPF and COPD

Idiopathic pulmonary fibrosis (IPF), non-specific interstitial pneumonia (NSIP), and chronic obstructive pulmonary disease (COPD) are severe, progressive, irreversibly incapacitating pulmonary disorders with modest response to therapeutic interventions and poor prognosis. Prompt and accurate diagnosis is important to enable patients to receive appropriate care at the earliest possible stage to delay disease progression and prolong survival. Artificial intelligence (AI)-assisted digital lung auscultation could constitute an alternative to conventional subjective operator-related auscultation to accurately and earlier diagnose these diseases. Moreover, lung ultrasound (LUS), a relevant gold standard for lung pathology, could also benefit from automation by deep learning.