Adverse outcome pathways (AOP) capture sequences of key events (KE) relating toxicant exposures to adverse outcomes (AO) observed in exposed populations. Quantitative AOPs (qAOP) enable AO risk assessment based on KE quantification and modeling of their relationships. This work aimed to develop a qAOP model for AOP 411 “Oxidative Stress Leading to Decreased Lung Function”. As a proof-of-concept, the model was applied to predict the medium-term lung function evolution after switching from combustible cigarettes (CC) to heated tobacco products (HTPs). The qAOP model enables the evaluation of the HTP “risk reduction potential” in the absence of epidemiological evidence.We designed our qAOP to evaluate the relative change (RC) of the AO risk for HTP switching compared to either continuing or quitting CC consumption. Using publicly available data for KE quantification, we developed both data- and physiology-based KE relationship (KER) models.We used the resulting qAOP to evaluate the effects of switching from CC smoking to HTPs in terms of the RC of the AO “Decreased Lung Function”. To support the acceptance of our approach, we followed “best practice” recommendations for building and reporting the three KER models. We also examined several scenarios for an optimal combination of in vitro testing and in silico predictions in quantifying AOP 411.In summary, qAOP provides a multiscale mechanistic approach to evaluate medium-term lung function changes when switching from CC smoking to HTPs. It demonstrates how in vitro and in silico approaches can be combined for a pragmatic and scientifically sound risk assessment.