Quantitative modeling of in vitro data using an adverse outcome pathway for the risk assessment of decreased lung function in humans.

In the absence of epidemiological data, there is a need to develop computational models that convert in vitro findings to human disease risk predictions following toxicant exposure. In such efforts, in vitro data can be evaluated in the context of adverse outcome pathways (AOPs) that organize mechanistic knowledge based on empirical evidence into a sequence of molecular-, cellular-, tissue-, and organ-level key events that precede an adverse outcome (AO). Here we combined data from advanced in vitro organotypic airway models exposed to combustible cigarette (CC) smoke or Tobacco Heating System (THS) aerosol with an AOP for increased oxidative stress leads to decreased lung function. The mathematical modeling predicted reduced risk of decreased ciliary beating frequency (CBF) based on oxidative stress measurements and reduced risk of decreased mucociliary clearance (MCC) based on CBF measurements in THS aerosol- compared with CC smoke-exposed cultures. To extend the predictions to the AO of decreased lung function, we leveraged human MCC data from current smokers, nonsmokers, former smokers, and users of heated tobacco products. This approach provided a plausible prediction of diminished reduction in lung function in response to THS use compared with continued smoking. The current approach may also present a basis for an integrated approach to testing and assessment of tobacco products for future regulatory decision-making.

Deconvolution of Systemic Pharmacokinetics Predicts Inhaled Aerosol Dosimetry of Nicotine.

Absorption of inhaled compounds can occur from multiple sites based on upper and lower respiratory tract deposition, and clearance mechanisms leading to differential local and systemic pharmacokinetics. Deriving inhaled aerosol dosimetry and local tissue concentrations for nose-only exposure in rodents and inhaled products in humans is challenging. In this study we use inhaled nicotine as an example to identify regional respiratory tract deposition, absorption fractions, and their contribution toward systemic pharmacokinetics in rodents and humans. A physiologically based pharmacokinetic (PBPK) model was constructed to describe the disposition of nicotine and its major metabolite, cotinine. The model description for the lungs was simplified to include an upper respiratory tract region with active mucociliary clearance and a lower respiratory tract region. The PBPK model parameters such as rate of oral absorption, metabolism and clearance were fitted to the published nicotine and cotinine plasma concentrations post systemic administration and oral dosing. The fractional deposition of inhaled aerosol in the upper and lower respiratory tract regions was estimated by fitting the plasma concentrations. The model predicted upper respiratory tract deposition was 63.9% for nose-only exposure to nicotine containing nebulized aqueous aerosol in rats and 60.2% for orally inhaled electronic vapor product in humans. A marked absorption of nicotine from the upper respiratory tract and the gastrointestinal tract for inhaled aqueous aerosol contributed to the differential systemic pharmacokinetics in rats and humans. The PBPK model derived dosimetry shows that the current aerosol dosimetry models with their posteriori application using independent aerosol physicochemical characterization to predict aerosol deposition are insufficient and will need to consider complex interplay of inhaled aerosol evolutionary process. While the study highlights the needs for future research, it provides a preliminary framework for interpreting pharmacokinetics of inhaled aerosols to facilitate the analysis of in vivo exposure-responses for pharmacological and toxicological assessments.

Toxicological Assessment of Flavor Ingredients in E-Vapor Products.

Many flavor ingredients are often used in potentially reduced-risk tobacco products (such as e-vapor products). Although most are "generally recognized as safe (GRAS)" when used in food, there is limited information available on their long-term health effects when delivered by inhalation. While obtaining route-of-exposure-specific toxicological data on flavor ingredients is critical to product evaluation, the large number of individual flavor ingredients available and their potential combinations render classical toxicological assessment approaches impractical, as they may require years of preclinical investigations and thousands of laboratory animals. Therefore, we propose a pragmatic approach in which flavor ingredients are initially assigned to groups of structurally related compounds (Flavor Groups), from which flavor group representatives (FGR) are then selected and tested individually and as a mixture in vitro and in vivo. The premise is that structurally related compounds would have comparable metabolic and biological activity and that the data generated using FGRs could support the toxicological assessment of other structurally related flavor ingredients of their respective Flavor Groups. This approach is explained in a step-wise manner and exemplified by a case study, along with its strengths, limitations as well as recommendations for further confirmatory testing. Once completed, this FGR approach could significantly reduce the time and resources required for filling the data gap in understanding the health risks of many flavor ingredients while also minimizing the need for laboratory animals.

Systems biology approach highlights mechanistic differences between Crohn's disease and ulcerative colitis.

The molecular mechanisms of IBD have been the subject of intensive exploration. We, therefore, assembled the available information into a suite of causal biological network models, which offer comprehensive visualization of the processes underlying IBD. Scientific text was curated by using Biological Expression Language (BEL) and compiled with OpenBEL 3.0.0. Network properties were analysed by Cytoscape. Network perturbation amplitudes were computed to score the network models with transcriptomic data from public data repositories. The IBD network model suite consists of three independent models that represent signalling pathways that contribute to IBD. In the "intestinal permeability" model, programmed cell death factors were downregulated in CD and upregulated in UC. In the "inflammation" model, PPARG, IL6, and IFN-associated pathways were prominent regulatory factors in both diseases. In the "wound healing" model, factors promoting wound healing were upregulated in CD and downregulated in UC. Scoring of publicly available transcriptomic datasets onto these network models demonstrated that the IBD models capture the perturbation in each dataset accurately. The IBD network model suite can provide better mechanistic insights of the transcriptional changes in IBD and constitutes a valuable tool in personalized medicine to further understand individual drug responses in IBD.