Yuliya Karpievitch
AI and Data Analytics Lead, Respiratory Research
PhD, MS, BS
yuliya.karpievitch@telethonkids.org.au
+61 8 6319 1356
https://www.linkedin.com/in/yuliya-karpievitch-6525253/Yuliya Karpievitch is an Artificial Intelligence and Data Scientist. Her research focuses on computational models in respiratory conditions such as cystic fibrosis, bronchiectasis and asthma. Yuliya uses long-read Nanopore sequencing to obtain a picture of the lung microbiome and patient’s response to the microbiome and uses artificial intelligence (AI) to decipher the complex microbiome-microbiome-host interactions.
Yuliya is leading an AI and Data Science team in drug screening and computed tomography (CT) scan analyses automation using AI. Her Data Science part of the team is leading Bayesian analyses of clinical trials and provides statistical support to the Australian Respiratory Early Surveillance Team for Cystic Fibrosis (AREST CF) and Airway Epithelial Research Team (EPIC) teams.
Projects
Western Australia Paediatric Bronchiectasis Cohort
Bronchiectasis is a chronic lung disease that impairs quality of life and reduces life expectancy.
SYNERGY CF: Getting the best start to life - preventing early cystic fibrosis lung disease by solving the host-inflammation infection conundrum
Cystic Fibrosis Early Surveillance Program
Researchers are able to track the progress of lung disease through a comprehensive longitudinal set of biological samples, images and data archives.
Published research
A phase I clinical trial assessing the safety, tolerability, and pharmacokinetics of inhaled ethanol in humans as a potential treatment for respiratory tract infections
Current treatments for respiratory infections are severely limited. Ethanol's unique properties including antimicrobial, immunomodulatory, and surfactant-like activity make it a promising candidate treatment for respiratory infections if it can be delivered safely to the airway by inhalation. Here, we explore the safety, tolerability, and pharmacokinetics of inhaled ethanol in a phase I clinical trial.
Thoracic electrical impedance tomography identifies heterogeneity in lungs associated with respiratory disease in cattle. A pilot study
Respiratory disease in cattle is a significant global concern, yet current diagnostic methods are limited, and there is a lack of crush-side tests for detecting active disease. To address this gap, we propose utilizing electrical impedance tomography (EIT), a non-invasive imaging technique that provides real-time visualization of lung ventilation dynamics.
Interferon β-1a ring prophylaxis to reduce household transmission of SARS-CoV-2: a cluster randomised clinical trial
Accumulating evidence indicates that an early, robust type 1 interferon (IFN) response to SARS-CoV-2 is important in determining COVID-19 outcomes, with an inadequate IFN response associated with disease severity. Our objective was to examine the prophylactic potential of IFN administration to limit viral transmission.
Lipopolysaccharide-induced interferon response networks at birth are predictive of severe viral lower respiratory infections in the first year of life
Appropriate innate immune function is essential to limit pathogenesis and severity of severe lower respiratory infections (sLRI) during infancy, a leading cause of hospitalization and risk factor for subsequent asthma in this age group.
AI-Driven Cell Tracking to Enable High-Throughput Drug Screening Targeting Airway Epithelial Repair for Children with Asthma
The airway epithelium of children with asthma is characterized by aberrant repair that may be therapeutically modifiable. The development of epithelial-targeting therapeutics that enhance airway repair could provide a novel treatment avenue for childhood asthma.
Education and Qualifications
- PhD - Medical University of South Carolina
- MS - College of Charleston
- BS - College of Charleston