Med-Talk Podcast - AI Biomarkers and the Effects of Treating Lung Disease with Susan Wood, PhD

Ian Bolland, acting group editor of life sciences at Rapid News Group, was recently joined by Susan Wood, PhD, president and CEO of VIDA.

They discuss the spotlight that has been put upon respiratory disease amid the COVID-19 pandemic, challenges faced in respiratory clinical trials, the crucial role data can play, and the focus that needs to be put upon treating lung disease to bring down mortality rates.  Listen to the entire 25 minute discussion here.  Highlights below:

Tell me about your background

Susan: "I did my PhD at Johns Hopkins and there I discovered the lung and all its complexity. I focused on using imaging--primarily CT--to measure the lung with great precision, both structurally and functionally; a change in lung structure leads to a change in function. With imaging you have this great degree of precision in which you can measure and find disease, differentially diagnose disease, guide therapeutics, and measure response at a level of precision far greater than what was and is available with conventional methods." 

How big is the issue of lung disease?

Susan: "The major metrics of lung disease (incidence, prevalence, mortality, and global economic burden) are all going in the wrong direction. We are faced with a global crisis of the lung that pre-dates COVID-19.  Those with underlying respiratory disease certainly tended to have poorer outcome from COVID.  COVID has brought this global lung crisis to the forefront. Now, long COVID is affecting 250m people at least 6 months post-infection, so this is yet another group of patients that are going to enter the health care system and many of those long COVID patients have respiratory symptoms, so it's a bad problem."

How can retrospective data help pharma companies?

Susan: "There are some trials that have imaging cohorts that were collected. Often, those scans were read visually without much other analysis.  These datasets are a treasure trove of information that you could go analyze for new indicators or new biomarkers of response that weren't identified earlier."