There are unique considerations to factor in treating COVID-19 in children and pregnant women. While COVID-19 disease among children have been less severe than those in adults, the youngest appear to be the most at risk of severe disease. Because their symptoms are mild, children may be contributing to the rapid spread of COVID-19 and could be a key factor in stemming the pandemic. And while data on pregnant women is limited on COVID-19, we know that they can experience significant morbidity with some respiratory infections. Currently, the totality of data that would support meaningful dosing guidance as well as long-term safety experience is lacking (Barrett et al., 2018), especially for special populations such as children and pregnant women.
For COVID-19 and the next outbreaks, it is imperative that we build tools and processes to help tailor therapies for special populations. Electronic health records have the potential to generate meaningful real-world data in children and pregnant women by creating and connecting the relevant outcome data and decision support systems to become a part of the practice of medicine and not just a reference. Likewise, modeling and simulation (M&S) approaches such as physiologically-based pharmacokinetics (PBPK) can be used to simulate exposures and predict relevant doses in children and pregnant women.