Innate immune activation by inhaled lipopolysaccharide, independent of oxidative stress, exacerbates silica-induced pulmonary fibrosis in mice

Acute exacerbations of pulmonary fibrosis are characterized by rapid decrements in lung function. Environmental factors that may contribute to acute exacerbations remain poorly understood. We have previously demonstrated that exposure to inhaled lipopolysaccharide (LPS) induces expression of genes associated with fibrosis. To address whether exposure to LPS could exacerbate fibrosis, we exposed male C57BL/6 mice to crystalline silica, or vehicle, followed 28 days later by LPS or saline inhalation. We observed that mice receiving both silica and LPS had significantly more total inflammatory cells, more whole lung lavage MCP-1, MIP-2, KC and IL-1β, more evidence of oxidative stress and more total lung hydroxyproline than mice receiving either LPS alone, or silica alone. Blocking oxidative stress with N-acetylcysteine attenuated whole lung inflammation but had no effect on total lung hydroxyproline. These observations suggest that exposure to innate immune stimuli, such as LPS in the environment, may exacerbate stable pulmonary fibrosis via mechanisms that are independent of inflammation and oxidative stress. © 2012 Brass et al

Machine learning methods for prediction of food effects on bioavailability: A comparison of Support Vector Machines and Artificial Neural Networks

Despite countless advances in recent decades across various in vitro, in vivo and in silico tools, anticipation of whether a drug will show a human food effect (FE) remains challenging. One means to predict potential FE involves probing any dependence between FE and drug properties. Accordingly, this study explored the potential for two machine learning (ML) algorithms to predict likely FE. Using a collated database of drugs licensed from 2016-2020, drugs were classified into three groups; positive, negative or no FE. Greater than 250 drug properties were predicted for each drug which were used to train predictive models using Support Vector Machine (SVM) and Artificial Neural Network (ANN) algorithms. When compared, ANN outperformed SVM for FE classification upon training (82%, 72%) and testing (72%, 69%). Both models demonstrated higher FE prediction accuracy than the Biopharmaceutics Classification System (BCS) (46%). This exploratory work provided new insights into the connection between FE and drug properties as the Octanol Water Partition Coefficient (S+logP), Number of Hydrogen Bond Donors (HBD), Topological Polar Surface Area (T_PSA) and Dose (mg) were all significant for prediction. Overall, this study demonstrated the utility of ML to facilitate early anticipation of likely FE in pre-clinical development using four well-known drug properties

A retrospective biopharmaceutical analysis of >800 approved oral drug products: Are drug properties of solid dispersions and lipid-based formulations distinctive?

Increasing numbers of poorly water soluble drugs in development has intensified need for bio-enabling formulations including Lipid-Based Formulations (LBF) and Solid Dispersions (SD). Resultantly, a data-driven approach is required to increase formulation development efficiency. This review provides a retrospective analysis of molecular and biopharmaceutical properties of drugs commercialised as LBFs or SDs. A comprehensive stepwise statistical analysis of LBF and SD drug properties was conducted and compared to drugs not commercialised via either technology (Others), aiming to identify key predictors of successful formulation development. This review demonstrates LBF and SD drugs differ significantly in molecular weight, polar surface area, rotatable bonds and hydrogen bond acceptor count. Meanwhile, LBF and SD drugs display significantly different aqueous solubility, lipophilicity, size, molecular flexibility, hydrogen bonding capacity and rule-of-5 violations versus Others. LBF and SDs were 3 and 5 times more likely to display >1 rule-of-5 violation versus Others, over 55% of LBF drugs exceeded the reported melting point guide of 10 Hydrogen Bond Acceptors. Overall, by focusing on successfully commercialised drugs, this review provides improved understanding of links between drug properties and successful SD/LBF approaches, providing a framework for guiding pharmaceutical development on formulation approaches

Applying computational predictions of biorelevant solubility ratio upon self-emulsifying lipid-based formulations dispersion to predict dose number

Computational approaches are increasingly utilised in development of bio-enabling formulations, including self-emulsifying drug delivery systems (SEDDS), facilitating early indicators of success. This study investigated if in silico predictions of drug solubility gain i.e. solubility ratios (SR), after dispersion of a SEDDS in biorelevant media could be predicted from drug properties. Apparent solubility upon dispersion of two SEDDS in FaSSIF was measured for 30 structurally diverse poorly water soluble drugs. Increased drug solubility upon SEDDS dispersion was observed in all cases, with higher SRs observed for cationic and neutral versus anionic drugs at pH 6.5. Molecular descriptors and solid-state properties were used as inputs during partial least squares (PLS) modelling resulting in predictive models for SRMC (r2 = 0.81) and SRLC (r2 = 0.77). Multiple linear regression (MLR) facilitated generation of simplified SR equations with high predictivity (SRMC r2 = 0.74; SRLC r2 = 0.69), requiring only three drug properties; partition coefficient at pH 6.5 (logD6.5), melting point (Tm) and aromatic bonds as fraction of total bonds (FArom_B). Through using the equations to inform drug developability classifications (DCS) for drugs that have already been licensed as lipid based formulations, merits for development with SEDDS was predicted for 2/3 drugs

Exploring porcine gastric and intestinal fluids using microscopic and solubility estimates: Impact of placebo self-emulsifying drug delivery system administration to inform bio-predictive in vitro tools

Validation and characterisation of in vitro and pre-clinical animal models to support bio-enabling formulation development is of paramount importance. In this work, post-mortem gastric and small intestinal fluids were collected in the fasted, fed state and at five sample-points post administration of a placebo Self-Emulsifying Drug Delivery System (SEDDS) in the fasted state to pigs. Cryo-TEM and Negative Stain-TEM were used for ultrastructure characterisation. Ex vivo solubility of fenofibrate was determined in the fasted-state, fed-state and post-SEDDS administration. Highest observed ex vivo drug solubility in intestinal fluids after SEDDS administration was used for optimising the biorelevant in vitro conditions to determine maximum solubility. Under microscopic evaluation, fasted, fed and SEDDS fluids resulted in different colloidal structures. Drug solubility appeared highest 1 hour post SEDDS administration, corresponding with presence of SEDDS lipid droplets. A 1:200 dispersion of SEDDS in biorelevant media matched the highest observed ex vivo solubility upon SEDDS administration. Overall, impacts of this study include increasing evidence for the pig preclinical model to mimic drug solubility in humans, observations that SEDDS administration may poorly mimic colloidal structures observed under fed state, while microscopic and solubility porcine assessments provided a framework for increasingly bio-predictive in vitro tools

Epidemiologic and clinical updates on impulse control disorders: a critical review

The article reviews the current knowledge about the impulse control disorders (ICDs) with specific emphasis on epidemiological and pharmacological advances. In addition to the traditional ICDs present in the DSM-IV—pathological gambling, trichotillomania, kleptomania, pyromania and intermittent explosive disorder—a brief description of the new proposed ICDs—compulsive–impulsive (C–I) Internet usage disorder, C–I sexual behaviors, C–I skin picking and C–I shopping—is provided. Specifically, the article summarizes the phenomenology, epidemiology and comorbidity of the ICDs. Particular attention is paid to the relationship between ICDs and obsessive–compulsive disorder (OCD). Finally, current pharmacological options for treating ICDs are presented and discussed

Cationic Host Defence Peptides:Potential as Antiviral Therapeutics

There is a pressing need to develop new antiviral treatments; of the 60 drugs currently available, half are aimed at HIV-1 and the remainder target only a further six viruses. This demand has led to the emergence of possible peptide therapies, with 15 currently in clinical trials. Advancements in understanding the antiviral potential of naturally occurring host defence peptides highlights the potential of a whole new class of molecules to be considered as antiviral therapeutics. Cationic host defence peptides, such as defensins and cathelicidins, are important components of innate immunity with antimicrobial and immunomodulatory capabilities. In recent years they have also been shown to be natural, broad-spectrum antivirals against both enveloped and non-enveloped viruses, including HIV-1, influenza virus, respiratory syncytial virus and herpes simplex virus. Here we review the antiviral properties of several families of these host peptides and their potential to inform the design of novel therapeutics