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.