In vitro - in vivo - in silico approach in the development of inhaled drug products: Nanocrystal-based formulations with budesonide as a model drug

This study aims to understand the absorption patterns of three different kinds of inhaled formulations via in silico modeling using budesonide(BUD)as a model drug.The formulations investigated in this study are:(i)commercially available micronized BUD mixed with lactose(BUD-PT),(ii)BUD nanocrystal suspension(BUD-NC),(iii)BUD nanocrystals embedded hyaluronic acid microparticles(BUD-NEM).The deposition patterns of the three inhaled formulations in the rats’lungs were determined in vivo and in silico predicted,which were used as inputs in GastroPlus TM software to predict drug absorption following aerosolization of the tested formulations.BUD pharmacokinetics,estimated based on intravenous data in rats,was used to establish a drug-specific in silico absorption model.The BUD-specific in silico model revealed that drug pulmonary solubility and absorption rate constant were the key factors affecting pulmonary absorption of BUD-NC and BUD-NEM,respectively.In the case of BUD-PT,the in silico model revealed significant gastrointestinal absorption of BUD,which could be overlooked by traditional in vivo experimental observation.This study demonstrated that in vitro-in vivo-in silico approach was able to identify the key factors that influence the absorption of different inhaled formulations,which may facilitate the development of orally inhaled formulations with different drug release/absorption rates.

On the Origin of the Apparent Volume of Distribution and Its Significance in Pharmacokinetics

The apparent volume of distribution was defined for the first time as the phase volume that can hold the total amount of a substance at the measured phase substance concentration, in a system composed of two immiscible media that are in contact under conditions of constant phase volumes, at equilibrium. Its value is not affected by the total system solute mass and it only depends on the total system volume, the phase volumes and the affinity of the solute for the two phases in the system. Using this new concept of the apparent volume of distribution, we were able to demonstrate that under certain conditions compartment volumes in multi-compartment and multi-phasic pharmacokinetic models represent the actual physiological volumes of body fluids accessible by drugs. The classical pharmacokinetic models are now fully explained and can be used to provide accurate estimation of the pharmacokinetic parameters for hydrophilic drugs. In contrast, in the absence of tissue-plasma partition coefficients, lipophilic drugs that do not follow a one-compartment model are unlikely to be adequately described with classical multi-compartment pharmacokinetic models.

Advancing Toxicity Predictions:A Review on in Vitro to in Vivo Extrapolation in Next-Generation Risk Assessment

As a key step in next-generation risk assessment(NGRA),in vitro to in vivo extrapolation(IVIVE)aims to mobilize a mechanism-based understanding of toxicology to translate bioactive chemical concentrations obtained from in vitro assays to corresponding exposures likely to induce bioactivity in vivo.This conversion can be achieved via physiologically-based toxicokinetic(PBTK)models and machine learning(ML)algorithms.The last 5 years have witnessed a period of rapid development in IVIVE,with the number of IVIVE-related publications increasing annually.This Review aims to(1)provide a comprehensive overview of the origin of IVIVE and initiatives undertaken by multiple national agencies to promote its development;(2)compile and sort out IVIVE-related publications and perform a clustering analysis of their high-frequency keywords to capture key research hotspots;(3)comprehensively review PBTK and ML model-based IVIVE studies published in the last 5 years to understand the research directions and methodology developments;and(4)propose future perspectives for IVIVE from two aspects:expanding the scope of application and integrating new technologies.The former includes focusing on metabolite toxicity,conducting IVIVE studies on susceptible populations,advancing ML-based quantitative IVIVE models,and extending research to ecological effects.The latter includes combining systems biology,multiomics,and adverse outcome networks with IVIVE,aiming at a more microscopic,mechanistic,and comprehensive toxicity prediction.This Review highlights the important value of IVIVE in NGRA,with the goal of providing confidence for its routine use in chemical prioritization,hazard assessment,and regulatory decision making.