Episode 30 Overview, Guest Bio & Additional Resources
Dr. Meraj Khan on Bringing AI Into Real-World Asthma Care
In this episode of Beyond the Wheeze, I’m joined by Dr. Meraj Khan, co-founder and CEO of DigiBiomics, to explore whether artificial intelligence is truly ready for real-world asthma care. Dr. Khan shares how his work bridges clinical research, AI development, and frontline healthcare — and why the biggest barrier today is not the technology itself, but how we translate it into everyday practice.
We discuss the gap between AI innovation and clinical adoption, from workflow integration challenges to limited real-world validation and reimbursement hurdles. Dr. Khan explains how AI can support continuous monitoring, risk stratification, early screening, and decision-making — not by replacing clinicians, but by empowering them with clearer, actionable insights.
This conversation offers practical insight for patients, caregivers, healthcare providers, and system leaders alike — highlighting how transparency, data governance, bias mitigation, and real-world testing will determine whether AI meaningfully improves asthma outcomes across Canada and beyond.
Bridging AI Innovation and Real-World Asthma Care
Dr. Meraj Khan is co-founder and CEO of DigiBiomics, where he works at the intersection of artificial intelligence, clinical research, and respiratory medicine. His work focuses on translating advanced AI models into tools that function inside real healthcare environments. Rather than building technology for theory, Dr. Khan prioritizes workflow integration, real-world validation, and measurable clinical impact. Through his leadership, he is helping move AI in asthma care from research settings into hospital systems, long-term care, and remote monitoring environments.
Building Trustworthy AI That Supports, Not Replaces, Clinicians
Dr. Khan’s approach centers on responsible implementation. He emphasizes that AI should empower clinicians and patients, not replace human judgment. By focusing on transparency, explainability, diverse real-world data, and ongoing auditing, his work addresses concerns around bias, data governance, and trust. Through platforms like Lung Sense, his team is demonstrating how AI can support earlier intervention, clearer risk stratification, and more proactive asthma management — helping move respiratory care from reactive treatment toward preventative, data-informed decision-making.