Simulated pharmacokinetics of inhaled caffeine and melatonin from existing products indicate the lack of dosimetric considerations.

Numerous commercially available inhalable products claim to improve sleep-wake cycle-related target indications by delivering a wide variety of chemicals like caffeine and melatonin. The resulting exposure-responses from inhaling different doses are unknown and obtaining early understanding of resulting pharmacokinetics is beneficial. This study applied a physiologically based pharmacokinetic modeling approach to predict the inhalation pharmacokinetics of caffeine and melatonin for different target indications related to the sleep-wake cycle. The model predicted rapid systemic delivery of caffeine and melatonin based on airway regional deposition of inhaled aerosol. A low inhaled dose of 1 mg of caffeine resulted in a 72.3-times lower plasma maximal concentration and was predicted to not improve cognitive performance task outcomes compared to oral consumption of coffee containing 80 mg of caffeine. Conversely, 2-mg oral and inhaled doses of melatonin under recommended directions of use result in more than 25.1- and 645-times higher plasma concentrations compared to endogenous melatonin, respectively. The recommended doses for inhalation products for potential improvement in the target indications vary widely. Additional research is needed to evaluate the human pharmacokinetics, efficacy, and safety of inhaled products. Given the lack of assessments, inhaled caffeine and melatonin must be consumed with caution as the toxicological concerns are not known and could outweigh the potential beneficial effects.

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.

Pulmonary Delivery of Aerosolized Chloroquine and Hydroxychloroquine to Treat COVID-19: In Vitro Experimentation to Human Dosing Predictions.

In vitro screening for pharmacological activity of existing drugs showed chloroquine and hydroxychloroquine to be effective against severe acute respiratory syndrome coronavirus 2. Oral administration of these compounds to obtain desired pulmonary exposures resulted in dose-limiting systemic toxicity in humans. However, pulmonary drug delivery enables direct and rapid administration to obtain higher local tissue concentrations in target tissue. In this work, inhalable formulations for thermal aerosolization of chloroquine and hydroxychloroquine were developed, and their physicochemical properties were characterized. Thermal aerosolization of 40 mg/mL chloroquine and 100 mg/mL hydroxychloroquine formulations delivered respirable aerosol particle sizes with 0.15 and 0.33 mg per 55 mL puff, respectively. In vitro toxicity was evaluated by exposing primary human bronchial epithelial cells to aerosol generated from Vitrocell. An in vitro exposure to 7.24 µg of chloroquine or 7.99 µg hydroxychloroquine showed no significant changes in cilia beating, transepithelial electrical resistance, and cell viability. The pharmacokinetics of inhaled aerosols was predicted by developing a physiologically based pharmacokinetic model that included a detailed species-specific respiratory tract physiology and lysosomal trapping. Based on the model predictions, inhaling emitted doses comprising 1.5 mg of chloroquine or 3.3 mg hydroxychloroquine three times a day may yield therapeutically effective concentrations in the lung. Inhalation of higher doses further increased effective concentrations in the lung while maintaining lower systemic concentrations. Given the theoretically favorable risk/benefit ratio, the clinical significance for pulmonary delivery of aerosolized chloroquine and hydroxychloroquine to treat COVID-19 needs to be established in rigorous safety and efficacy studies. Graphical abstract.

Translational Modeling of Chloroquine and Hydroxychloroquine Dosimetry in Human Airways for Treating Viral Respiratory Infections.

PURPOSE: Chloroquine and hydroxychloroquine are effective against respiratory viruses in vitro. However, they lack antiviral efficacy upon oral administration. Translation of in vitro to in vivo exposure is necessary for understanding the disconnect between the two to develop effective therapeutic strategies. METHODS: We employed an in vitro ion-trapping kinetic model to predict the changes in the cytosolic and lysosomal concentrations of chloroquine and hydroxychloroquine in cell lines and primary human airway cultures. A physiologically based pharmacokinetic model with detailed respiratory physiology was used to predict regional airway exposure and optimize dosing regimens. RESULTS: At their reported in vitro effective concentrations in cell lines, chloroquine and hydroxychloroquine cause a significant increase in their cytosolic and lysosomal concentrations by altering the lysosomal pH. Higher concentrations of the compounds are required to achieve similar levels of cytosolic and lysosomal changes in primary human airway cells in vitro. The predicted cellular and lysosomal concentrations in the respiratory tract for in vivo oral doses are lower than the in vitro effective levels. Pulmonary administration of aerosolized chloroquine or hydroxychloroquine is predicted to achieve high bound in vitro-effective concentrations in the respiratory tract, with low systemic exposure. Achieving effective cytosolic concentrations for activating immunomodulatory effects and adequate lysosomal levels for inhibiting viral replication could be key drivers for treating viral respiratory infections. CONCLUSION: Our analysis provides a framework for extrapolating in vitro effective concentrations of chloroquine and hydroxychloroquine to in vivo dosing regimens for treating viral respiratory infections.

AI-driven laboratory workflows enable operation in the age of social distancing.

The COVID-19 (Coronavirus disease 2019) global pandemic has upended the normal pace of society at multiple levels-from daily activities in personal and professional lives to the way the sciences operate. Many laboratories have reported shortage in vital supplies, change in standard operating protocols, suspension of operations because of social distancing and stay-at-home guidelines during the pandemic. This global crisis has opened opportunities to leverage internet of things, connectivity, and artificial intelligence (AI) to build a connected laboratory automation platform. However, laboratory operations involve complex, multicomponent systems. It is unrealistic to completely automate the entire diversity of laboratories and processes. Recently, AI technology, particularly, game simulation has made significant strides in modeling and learning complex, multicomponent systems. Here, we present a cloud-based laboratory management and automation platform which combines multilayer information on a simulation-driven inference engine to plan and optimize laboratory operations under various constraints of COVID-19 and risk scenarios. The platform was used to assess the execution of two cell-based assays with distinct parameters in a real-life high-content screening laboratory scenario. The results show that the platform can provide a systematic framework for assessing laboratory operation scenarios under different conditions, quantifying tradeoffs, and determining the performance impact of specific resources or constraints, thereby enabling decision-making in a cost-effective manner. We envisage the laboratory management and automation platform to be further expanded by connecting it with sensors, robotic equipment, and other components of scientific operations to provide an integrated, end-to-end platform for scientific laboratory automation.

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.