Physiologically based pharmacokinetic modelling in drug delivery

The application of pharmacokinetic modelling within the drug development field essentially allows one to develop a quantitative description of the temporal behaviour of a compound of interest at a tissue/organ level, by identifying and defining relationships between a dose of a drug and dependent variables. In order to understand and characterise the pharmacokinetics of a drug, it is often helpful to employ pharmacokinetic modelling using empirical or mechanistic approaches. Pharmacokinetic models can be developed within mathematical and statistical commercial software such as MATLAB using traditional mathematical and computation coding, or by using the Simbiology Toolbox available within MATLAB for a graphical user interface approach to developing pharmacokinetic (PBPK) models. For formulations dosed orally, a prerequisite for clinical activity is the entry of the drug into the systemic circulation.

Enhancement of a novel gene therapy approach for Sandhoff disease through complimentary drug therapy

GM2 gangliosidoses is a family of severe, neurodegenerative disorders resulting from a deficiency in the β-hexosaminidase A (Hex A) enzyme. This disorder is typically caused by a mutation to either the HEXA gene, causing Tay Sachs disease, or a mutation to the HEXB gene, causing Sandhoff disease. The HEXA and HEXB genes are required to produce the α and β subunits of the Hex A enzyme respectively. Using a Sandhoff disease (SD) mouse model (Hexb-/-) we tested the potential of a low dose of systemically delivered single stranded adeno-associated virus 9 (ssAAV9) expressing human HEXB and human HEXA cDNA under the control of a single promoter through the use of a bicistronic vector design with a P2A linker to correct the neurological phenotype. Neonatal mice were injected with either this ssAAV9-HexB-P2A-HexA vector (HexB-HexA) or a vehicle solution via the superficial temporal vein. HexB-HexA treatment alone conferred an increase in survival of 56% compared to vehicle-injected controls and biochemical analysis of the brain tissue and serum revealed an increase in HexA activity and a decrease in brain GM2 ganglioside buildup. Additionally, treatments with the non-steroidal anti-inflammatory drug indomethacin (Indo), the histone deactylase inhibitor ITF2357 (ITF) and the pharmacological chaperone pyrimethamine (Pyr) were tested. The anti-inflammatory treatments of Indo and ITF conferred an increase in survival of 12% and 8% respectively while causing no alteration in the HexA activity or GM2 ganglioside buildup. Pyr had no observable effect on disease progression. Lastly HexB-HexA treatment was tested in conjunction with Indo, ITF and Pyr individually. Additive increases in survival and behavioural testing results were observed with Indo and ITF treatments while no additional benefit to HexA activity or GM2 ganglioside levels in the brain tissue was observed. This indicates the two treatments slowed the progression of the disease through a different mechanism than the reduction of the GM2 ganglioside substrate. Pyr treatment was shown to have no effect when combined with HexB-HexA treatment. This study demonstrates the potential amelioration of SD with a novel AAV9 gene therapy approach as well as helped to identify the additive potential of anti-inflammatory treatments in gene therapy of GM2 gangliosidoses.

Characterizing bupropion metabolism, pharmacokinetics and drug-drug interaction liability

Thesis (Ph.D.)--University of Washington, 2016-06

Dose-Adjusted Beta-Lactam Antibiotic-Induced Encephalopathy in a Patient with End-Stage Renal Impairment: A Case Report

Introduction: Despite adherence to current guidelines regarding dose adjustment and drug-level monitoring, beta-lactam-induced encephalopathy can still occur in the setting of chronic renal impairment. Case Report: We report what we believe is the first case of piperacillin- and tazobactam-induced encephalopathy in a patient with pre-existing cefepime-induced encephalopathy in the context of end-stage kidney disease despite adequate dose adjustment for renal impairment.

Low dose gemcitabine-loaded lipid nanocapsules target monocytic myeloid-derived suppressor cells and potentiate cancer immunotherapy

International audience

Biochemical and epidemiological investigations of non-steroidal anti-inflammatory drug usage and related side effects in equids

Non-steroidal anti-inflammatory drugs (NSAIDs) are widely used in equine veterinary practice. These drugs exert their effect by inhibiting cyclooxygenase (COX) enzymes, which control prostaglandin production, a major regulator of tissue perfusion. Two isoforms of COX enzymes exist: COX-1 is physiologically present in tissues, while COX-2 is up-regulated during inflammation and has been indicated as responsible for the negative effects of an inflammatory response. Evidence suggests that NSAIDs that inhibit only COX-2, preserving the physiological function of COX-1 might have a safer profile. Studies that evaluate the effect of NSAIDs on COX enzymes are all performed under experimental conditions and none uses actual clinical patients. The biochemical investigations in this work focus on describing the effect on COX enzymes activity of flunixin meglumine and phenylbutazone, two non-selective COX inhibitors and firocoxib, a COX-2 selective inhibitor, in clinical patients undergoing elective surgery. A separate epidemiological investigation was aimed at describing the impact that the findings of biochemical data have on a large population of equids. Electronic medical records (EMRs) from 454,153 equids were obtained from practices in the United Kingdom, United States of America and Canada. Information on prevalence and indications for NSAIDs use was extracted from the EMRs via a text mining technique, improved from the literature and described and validated within this Thesis. Further the prevalence of a clinical sign compatible with NSAID toxicity, such as diarrhoea, is reported along with analysis evaluating NSAID administration in light of concurrent administration of other drugs and comorbidities. This work confirms findings from experimental settings that NSAIDs firocoxib is COX-2 selective and that flunixin meglumine and phenylbutazone are non-selective COX inhibitors and therefore their administration carries a greater risk of toxicity. However the impact of this finding needs to be interpreted with caution as epidemiological data suggest that the prevalence of toxicity is in fact small and the use of these drugs at the labelled dose is quite safe.

Nanopartículas hibrídas para sistemas de drug delivery inteligentes

A nanotecnologia é uma ciência multidisciplinar que consiste na otimização das propriedades da matéria permitindo assim o desenvolvimento de sistemas com um tamanho manométrico. A aplicação da nanotecnologia na medicina surge como um campo de pesquisa que esta a gerar um grande interesse, principalmente em sistemas de libertação controlada de fármacos. A nanotecnologia, e a sua aplicação na área da nanomedicina, em particular em drug delivery systems, tem sido alvo de um desenvolvimento acentuado. A administração de fármacos ocorre sobretudo por via oral ou por injeção direta no organismo. O percurso destes fármacos desde do local de entrada no organismo até ao tecido-alvo obriga que estes entrem em contato com os outros tecidos podendo interagir com eles. Deste modo, esta interação química pode produzir efeitos indesejáveis no organismo e reduzir a capacidade de ação do fármaco. Tem-se verificado, nas últimas décadas, um grande desenvolvimento de sistemas que contornam estes problemas, tais como a quantidade e o período de administração do fármaco bem como o seu local de libertação e atuação específicos. Este estudo surge com esta necessidade de se desenvolver sistemas de libertação controlada de fármacos. O objetivo destes sistemas inteligentes é controlar a libertação de fármacos por um dado período de tempo, a dose, a diminuição da toxidade, o aumento da permanência em circulação e o aumento da eficácia terapêutica através da libertação progressiva e controlada do fármaco por administrações menos frequentes. Além de todas estas vantagens, a administração destes sistemas possibilita a libertação dos fármacos em locais específicos, tais como em tumores e, assim, minimizar os efeitos colaterais indesejados dos fármacos em outros tecidos. O presente trabalho visa o desenvolvimento de novos biomateriais utilizando nanopartículas mesoporosas de sílica (MSN) e nanopartículas (NPs) metálicas de ouro para a aplicação a sistemas de libertação controlada de fármacos. Para isto, estudou-se a libertação de doxorrubicina (DOX) encapsulada em NPs e nanocápsulas mesoporosas de sílica tanto em solução como em superfícies como em vidro. Os resultados obtidos mostraram que as NPs apresentam uma grande capacidade de encapsulação com 36 ng DOX/mg partícula. O tempo de libertação em superfície (vidro) foi estimado em 50 horas enquanto que em solução obteve-se um período inferior a 10 horas. Em relação as NPs de ouro pode-se observar como estas promovem a libertação do fármaco ao serem irradiadas mediante um laser. Deste modo, estas NPs podem ser úteis para sistemas de libertação controlada de fármacos e para várias aplicações na nanomedicina.

Applied evolution: An integrated approach to studying life history traits in response to drug selection

The use of chemical control measures to reduce the impact of parasite and pest species has frequently resulted in the development of resistance. Thus, resistance management has become a key concern in human and veterinary medicine, and in agricultural production. Although it is known that factors such as gene flow between susceptible and resistant populations, drug type, application methods, and costs of resistance can affect the rate of resistance evolution, less is known about the impacts of density-dependent eco-evolutionary processes that could be altered by drug-induced mortality. The overall aim of this thesis was to take an experimental evolution approach to assess how life history traits respond to drug selection, using a free-living dioecious worm (Caenorhabditis remanei) as a model. In Chapter 2, I defined the relationship between C. remanei survival and Ivermectin dose over a range of concentrations, in order to control the intensity of selection used in the selection experiment described in Chapter 4. The dose-response data were also used to appraise curve-fitting methods, using Akaike Information Criterion (AIC) model selection to compare a series of nonlinear models. The type of model fitted to the dose response data had a significant effect on the estimates of LD50 and LD99, suggesting that failure to fit an appropriate model could give misleading estimates of resistance status. In addition, simulated data were used to establish that a potential cost of resistance could be predicted by comparing survival at the upper asymptote of dose-response curves for resistant and susceptible populations, even when differences were as low as 4%. This approach to dose-response modeling ensures that the maximum amount of useful information relating to resistance is gathered in one study. In Chapter 3, I asked how simulations could be used to inform important design choices used in selection experiments. Specifically, I focused on the effects of both within- and between-line variation on estimated power, when detecting small, medium and large effect sizes. Using mixed-effect models on simulated data, I demonstrated that commonly used designs with realistic levels of variation could be underpowered for substantial effect sizes. Thus, use of simulation-based power analysis provides an effective way to avoid under or overpowering a study designs incorporating variation due to random effects. In Chapter 4, I 3 investigated how Ivermectin dosage and changes in population density affect the rate of resistance evolution. I exposed replicate lines of C. remanei to two doses of Ivermectin (high and low) to assess relative survival of lines selected in drug-treated environments compared to untreated controls over 10 generations. Additionally, I maintained lines where mortality was imposed randomly to control for differences in density between drug treatments and to distinguish between the evolutionary consequences of drug treatment versus ecological processes affected by changes in density-dependent feedback. Intriguingly, both drug-selected and random-mortality lines showed an increase in survivorship when challenged with Ivermectin; the magnitude of this increase varied with the intensity of selection and life-history stage. The results suggest that interactions between density-dependent processes and life history may mediate evolved changes in susceptibility to control measures, which could result in misleading conclusions about the evolution of heritable resistance following drug treatment. In Chapter 5, I investigated whether the apparent changes in drug susceptibility found in Chapter 4 were related to evolved changes in life-history of C. remanei populations after selection in drug-treated and random-mortality environments. Rapid passage of lines in the drug-free environment had no effect on the measured life-history traits. In the drug-free environment, adult size and fecundity of drug-selected lines increased compared to the controls but drug selection did not affect lifespan. In the treated environment, drug-selected lines showed increased lifespan and fecundity relative to controls. Adult size of randomly culled lines responded in a similar way to drug-selected lines in the drug-free environment, but no change in fecundity or lifespan was observed in either environment. The results suggest that life histories of nematodes can respond to selection as a result of the application of control measures. Failure to take these responses into account when applying control measures could result in adverse outcomes, such as larger and more fecund parasites, as well as over-estimation of the development of genetically controlled resistance. In conclusion, my thesis shows that there may be a complex relationship between drug selection, density-dependent regulatory processes and life history of populations challenged with control measures. This relationship could have implications for how resistance is monitored and managed if life histories of parasitic species show such eco-evolutionary responses to drug application.

Bioadhesive drug delivery system of diltiazem hydrochloride for improved bioavailability in cardiac therapy

Purpose: To prepare and evaluate bioadhesive buccal films of diltiazem hydrochloride (a L-type calcium channel blocker) for overcoming the limitations of frequent dosing, low bioavailability and gastrointestinal discomfort of oral delivery. Methods: Buccal films were prepared by solvent casting technique using sodium carboxymethylcellulose, polyvinyl pyrrolidone K-30 and polyvinyl alcohol. The films were evaluated for weight, thickness, surface pH, swelling index, in vitro residence time, folding endurance, in vitro release, ex-vivo permeation (across porcine buccal mucosa) and drug content uniformity. Results: The drug content of the formulations was uniform with a range of 18.94 ± 0.066 (F2) to 20.08 ± 0.07 mg per unit film (F1). The films exhibited controlled release ranging from 58.76 ± 1.62 to 91.45 ± 1.02 % over a period > 6 h. The films containing 20 mg diltiazem hydrochloride, polyvinyl alcohol (10 %) and polyvinyl pyrrolidone (1 % w/v) i.e. formulation F5, showed moderate swelling, convenient residence time and promising drug release, and thus can be selected for further development of a buccal film for potential therapeutic uses. Conclusion: The developed formulation is a potential bioadhesive buccal system for delivering diltiazem directly to systemic circulation, circumventing first-pass metabolism, avoiding gastric discomfort and improving bioavailability at a minimal dose.

Network analysis and machine learning assist drug repurposing and safety assessment in neurological diseases

In recent decades, two prominent trends have influenced the data modeling field, namely network analysis and machine learning. This thesis explores the practical applications of these techniques within the domain of drug research, unveiling their multifaceted potential for advancing our comprehension of complex biological systems. The research undertaken during this PhD program is situated at the intersection of network theory, computational methods, and drug research. Across six projects presented herein, there is a gradual increase in model complexity. These projects traverse a diverse range of topics, with a specific emphasis on drug repurposing and safety in the context of neurological diseases. The aim of these projects is to leverage existing biomedical knowledge to develop innovative approaches that bolster drug research. The investigations have produced practical solutions, not only providing insights into the intricacies of biological systems, but also allowing the creation of valuable tools for their analysis. In short, the achievements are: • A novel computational algorithm to identify adverse events specific to fixed-dose drug combinations. • A web application that tracks the clinical drug research response to SARS-CoV-2. • A Python package for differential gene expression analysis and the identification of key regulatory "switch genes". • The identification of pivotal events causing drug-induced impulse control disorders linked to specific medications. • An automated pipeline for discovering potential drug repurposing opportunities. • The creation of a comprehensive knowledge graph and development of a graph machine learning model for predictions. Collectively, these projects illustrate diverse applications of data science and network-based methodologies, highlighting the profound impact they can have in supporting drug research activities.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

Study Of The Homogeneity Of Drug Loaded In Polymeric Films Using Near-infrared Chemical Imaging And Split-plot Design.

Split-plot design (SPD) and near-infrared chemical imaging were used to study the homogeneity of the drug paracetamol loaded in films and prepared from mixtures of the biocompatible polymers hydroxypropyl methylcellulose, polyvinylpyrrolidone, and polyethyleneglycol. The study was split into two parts: a partial least-squares (PLS) model was developed for a pixel-to-pixel quantification of the drug loaded into films. Afterwards, a SPD was developed to study the influence of the polymeric composition of films and the two process conditions related to their preparation (percentage of the drug in the formulations and curing temperature) on the homogeneity of the drug dispersed in the polymeric matrix. Chemical images of each formulation of the SPD were obtained by pixel-to-pixel predictions of the drug using the PLS model of the first part, and macropixel analyses were performed for each image to obtain the y-responses (homogeneity parameter). The design was modeled using PLS regression, allowing only the most relevant factors to remain in the final model. The interpretation of the SPD was enhanced by utilizing the orthogonal PLS algorithm, where the y-orthogonal variations in the design were separated from the y-correlated variation.

The Analgesic Effect Of Dipyrone In Peripheral Tissue Involves Two Different Mechanisms: Neuronal K(atp) Channel Opening And Cb(1) Receptor Activation.

Dipyrone (metamizole) is an analgesic pro-drug used to control moderate pain. It is metabolized in two major bioactive metabolites: 4-methylaminoantipyrine (4-MAA) and 4-aminoantipyrine (4-AA). The aim of this study was to investigate the participation of peripheral CB1 and CB2 cannabinoid receptors activation in the anti-hyperalgesic effect of dipyrone, 4-MAA or 4-AA. PGE2 (100ng/50µL/paw) was locally administered in the hindpaw of male Wistar rats, and the mechanical nociceptive threshold was quantified by electronic von Frey test, before and 3h after its injection. Dipyrone, 4-MAA or 4-AA was administered 30min before the von Frey test. The selective CB1 receptor antagonist AM251, CB2 receptor antagonist AM630, cGMP inhibitor ODQ or KATP channel blocker glibenclamide were administered 30min before dipyrone, 4-MAA or 4-AA. The antisense-ODN against CB1 receptor expression was intrathecally administered once a day during four consecutive days. PGE2-induced mechanical hyperalgesia was inhibited by dipyrone, 4-MAA, and 4-AA in a dose-response manner. AM251 or ODN anti-sense against neuronal CB1 receptor, but not AM630, reversed the anti-hyperalgesic effect mediated by 4-AA, but not by dipyrone or 4-MAA. On the other hand, the anti-hyperalgesic effect of dipyrone or 4-MAA was reversed by glibenclamide or ODQ. These results suggest that the activation of neuronal CB1, but not CB2 receptor, in peripheral tissue is involved in the anti-hyperalgesic effect of 4-aminoantipyrine. In addition, 4-methylaminoantipyrine mediates the anti-hyperalgesic effect by cGMP activation and KATP opening.

The Effect Of Soy Dietary Supplement And Low Dose Of Hormone Therapy On Main Cardiovascular Health Biomarkers: A Randomized Controlled Trial.

To assess the effects of a soy dietary supplement on the main biomarkers of cardiovascular health in postmenopausal women compared with the effects of low-dose hormone therapy (HT) and placebo. Double-blind, randomized and controlled intention-to-treat trial. Sixty healthy postmenopausal women, aged 40-60 years, 4.1 years mean time since menopause were recruited and randomly assigned to 3 groups: a soy dietary supplement group (isoflavone 90mg), a low-dose HT group (estradiol 1 mg plus noretisterone 0.5 mg) and a placebo group. Lipid profile, glucose level, body mass index, blood pressure and abdominal/hip ratio were evaluated in all the participants at baseline and after 16 weeks. Statistical analyses were performed using the χ2 test, Fisher's exact test, Kruskal-Wallis non-parametric test, analysis of variance (ANOVA), paired Student's t-test and Wilcoxon test. After a 16-week intervention period, total cholesterol decreased 11.3% and LDL-cholesterol decreased 18.6% in the HT group, but both did not change in the soy dietary supplement and placebo groups. Values for triglycerides, HDL-cholesterol, glucose level, body mass index, blood pressure and abdominal/hip ratio did not change over time in any of the three groups. The use of dietary soy supplement did not show any significant favorable effect on cardiovascular health biomarkers compared with HT. The trial is registered at the Brazilian Clinical Trials Registry (Registro Brasileiro de Ensaios Clínicos - ReBEC), number RBR-76mm75.

Impact Of Pharmacist Interventions On Drug-related Problems And Laboratory Markers In Outpatients With Human Immunodeficiency Virus Infection.

Substantial complexity has been introduced into treatment regimens for patients with human immunodeficiency virus (HIV) infection. Many drug-related problems (DRPs) are detected in these patients, such as low adherence, therapeutic inefficacy, and safety issues. We evaluated the impact of pharmacist interventions on CD4+ T-lymphocyte count, HIV viral load, and DRPs in patients with HIV infection. In this 18-month prospective controlled study, 90 outpatients were selected by convenience sampling from the Hospital Dia-University of Campinas Teaching Hospital (Brazil). Forty-five patients comprised the pharmacist intervention group and 45 the control group; all patients had HIV infection with or without acquired immunodeficiency syndrome. Pharmaceutical appointments were conducted based on the Pharmacotherapy Workup method, although DRPs and pharmacist intervention classifications were modified for applicability to institutional service limitations and research requirements. Pharmacist interventions were performed immediately after detection of DRPs. The main outcome measures were DRPs, CD4+ T-lymphocyte count, and HIV viral load. After pharmacist intervention, DRPs decreased from 5.2 (95% confidence interval [CI] =4.1-6.2) to 4.2 (95% CI =3.3-5.1) per patient (P=0.043). A total of 122 pharmacist interventions were proposed, with an average of 2.7 interventions per patient. All the pharmacist interventions were accepted by physicians, and among patients, the interventions were well accepted during the appointments, but compliance with the interventions was not measured. A statistically significant increase in CD4+ T-lymphocyte count in the intervention group was found (260.7 cells/mm(3) [95% CI =175.8-345.6] to 312.0 cells/mm(3) [95% CI =23.5-40.6], P=0.015), which was not observed in the control group. There was no statistical difference between the groups regarding HIV viral load. This study suggests that pharmacist interventions in patients with HIV infection can cause an increase in CD4+ T-lymphocyte counts and a decrease in DRPs, demonstrating the importance of an optimal pharmaceutical care plan.