570 resultados para pharmacokinetic


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Statins are agents widely used to lower LDL-cholesterol (LDL-C) in primary and secondary prevention of coronary heart disease. The five statins available in the UK (simvastatin, pravastatin, fluvastatin, atorvastatin and rosuvastatin) differ in many of their pharmacologic properties. In addition to lowering LDL-C, statins also increase HDL-cholesterol (HDL-C) moderately. There have been rare reports of significant HDL-C decreases in patients commenced on fibrates and when thiazolidinediones are added to fibrates. This is known as a 'paradoxical HDL-C decrease' as both groups of agents usually increase HDL-C. This phenomenon has never been clearly documented following statin therapy. We now describe a patient with type 2 diabetes who showed this paradoxical fall in HDL-C (baseline HDL-C: 1.8 mmol/L; on simvastatin 40 mg HDL-C 0.6 mmol/L; on atorvastatin 20 mg HDL-C 0.9 mmol/L) with a similar decrease in apolipoprotein A1. No similar decrease was observed with pravastatin and rosuvastatin therapy. This phenomenon appeared to be associated with statin treatment and not a statin/fibrate combination. Our patient clearly demonstrated a paradoxical HDL-C fall with simvastatin and atorvastatin, but not pravastatin or rosuvastatin. Simvastatin and atorvastatin share many pharmacokinetic properties such as lipophilicity while pravastatin and rosuvastatin are relatively hydrophilic and are not metabolized by cytochrome P450 3A4. However, these characteristics do not explain the dramatic reductions in HDL-C observed.

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How good is your pharmacy practice? And what does “good” look like? Take a look back at the education and training you have received in your career to date. Has it stood you in good stead? Certainly there is a need to establish a model of professional education and development that produces good pharmacists — you should be able to demonstrate your competence regardless of your sector of work. It may help if we move away from the view that excellence in pharmacy practice is primarily defined by where you practise and the kind of job that you do. The Modernising Pharmacy Careers programme’s aspirations to integrate the undergraduate degree with the preregistration training year are bold and to be applauded — provided the outcome delivers changes that are more than superficial. The new model needs to deliver greater integration of education with practice, while retaining an adequate science base. Theory should be put into the context of practice-based, cross-sector learning needs and opportunities. For example, is the classroom really the best environment in which to learn dispensing? Pharmacokinetic theory could be put into context through creatively designed work placements. And it might make more sense to learn patient counselling in a community pharmacy, and so on. Is it resources we lack to make this happen? Or do we lack the collective will to be imaginative, to be radical and to conceive new approaches to professional education? Implicit in this new approach to education is the expectation that pharmacists should teach and mentor and, conversely, that those who teach should also engage in relevant practice. University education must produce graduates whose knowledge and competence are useful to employers. Moreover, graduates must be adequately prepared to enter any area of the profession endowed with professional self-confidence (something, arguably, that needs further development within the pharmacy psyche). Of course, becoming qualified is just the beginning. Post-qualification, pharmacists need structured career paths that foster this professional confidence, support learning and ensure recognition. To this end, the Royal Pharmaceutical Society-led professional curriculum group is working to define knowledge, skills and experience for all areas of advanced practice. More than ever, the profession needs to adopt a culture of learning, teaching and practice research that is unified. The question is: how do we move away from merely collecting qualifications (trophies) to developing meaningful careers? Pharmacists in all areas and at all levels of the profession need to consider their own willingness to make this shift. The RPS and MPC are leading the way, but are we following?

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Colistin, a cationic polypeptide antibiotic, has reappeared in human medicine as a last-line treatment option for multidrug-resistant Gram-negative bacteria (MDR-GNB). Colistin is widely used in veterinary medicine for the treatment of gastrointestinal infections caused by Enterobacteriaceae. GNB resistant to colistin owing to chromosomal mutations have already been reported both in human and veterinary medicine, however several recent studies have just identified a plasmid-mediated mcr-1 gene encoding for colistin resistance in Escherichia coli colistin resistance. The discovery of a non-chromosomal mechanism of colistin resistance in E. coli has led to strong reactions in the scientific community and to concern among physicians and veterinarians. Colistin use in food animals and particularly in pig production has been singled out as responsible for the emergence of colistin resistance. The present review will focus mainly on the possible link between colistin use in pigs and the spread of colistin resistance in Enterobacteriaceae. First we demonstrate a possible link between Enterobacteriaceae resistance emergence and oral colistin pharmacokinetics/pharmacodynamics and its administration modalities in pigs. We then discuss the potential impact of colistin use in pigs on public health with respect to resistance. We believe that colistin use in pig production should be re-evaluated and its dosing and usage optimised. Moreover, the search for competitive alternatives to using colistin with swine is of paramount importance to preserve the effectiveness of this antibiotic for the treatment of MDR-GNB infections in human medicine.

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Histone deacetylases (HDACs) have been shown to play key roles in tumorigenesis, and

have been validated as effective enzyme target for cancer treatment. Largazole, a marine natural

product isolated from the cyanobacterium Symploca, is an extremely potent HDAC inhibitor that

has been shown to possess high differential cytotoxicity towards cancer cells along with excellent

HDAC class-selectivity. However, improvements can be made in the isoform-selectivity and

pharmacokinetic properties of largazole.

In attempts to make these improvements and furnish a more efficient biochemical probe

as well as a potential therapeutic, several largazole analogues have been designed, synthesized,

and tested for their biological activity. Three different types of analogues were prepared. First,

different chemical functionalities were introduced at the C2 position to probe the class Iselectivity profile of largazole. Additionally, docking studies led to the design of a potential

HDAC8-selective analogue. Secondly, the thiol moiety in largazole was replaced with a wide

variety of othe zinc-binding group in order to probe the effect of Zn2+ affinity on HDAC

inhibition. Lastly, three disulfide analogues of largazole were prepared in order to utilize a

different prodrug strategy to modulate the pharmacokinetic properties of largazole.

Through these analogues it was shown that C2 position can be modified significantly

without a major loss in activity while also eliciting minimal changes in isoform-selectivity. While

the Zn2+-binding group plays a major role in HDAC inhibition, it was also shown that the thiol

can be replaced by other functionalities while still retaining inhibitory activity. Lastly, the use of

a disulfide prodrug strategy was shown to affect pharmacokinetic properties resulting in varying

functional responses in vitro and in vivo.

v

Largazole is already an impressive HDAC inhibitor that shows incredible promise.

However, in order to further develop this natural product into an anti-cancer therapeutic as well as

a chemical probe, improvements in the areas of pharmacokinetics as well as isoform-selectivity

are required. Through these studies we plan on building upon existing structure–activity

relationships to further our understanding of largazole’s mechanism of inhibition so that we may

improve these properties and ultimately develop largazole into an efficient HDAC inhibitor that

may be used as an anti-cancer therapeutic as well as a chemical probe for the studying of

biochemical systems.

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A new modality for preventing HIV transmission is emerging in the form of topical microbicides. Some clinical trials have shown some promising results of these methods of protection while other trials have failed to show efficacy. Due to the relatively novel nature of microbicide drug transport, a rigorous, deterministic analysis of that transport can help improve the design of microbicide vehicles and understand results from clinical trials. This type of analysis can aid microbicide product design by helping understand and organize the determinants of drug transport and the potential efficacies of candidate microbicide products.

Microbicide drug transport is modeled as a diffusion process with convection and reaction effects in appropriate compartments. This is applied here to vaginal gels and rings and a rectal enema, all delivering the microbicide drug Tenofovir. Although the focus here is on Tenofovir, the methods established in this dissertation can readily be adapted to other drugs, given knowledge of their physical and chemical properties, such as the diffusion coefficient, partition coefficient, and reaction kinetics. Other dosage forms such as tablets and fiber meshes can also be modeled using the perspective and methods developed here.

The analyses here include convective details of intravaginal flows by both ambient fluid and spreading gels with different rheological properties and applied volumes. These are input to the overall conservation equations for drug mass transport in different compartments. The results are Tenofovir concentration distributions in time and space for a variety of microbicide products and conditions. The Tenofovir concentrations in the vaginal and rectal mucosal stroma are converted, via a coupled reaction equation, to concentrations of Tenofovir diphosphate, which is the active form of the drug that functions as a reverse transcriptase inhibitor against HIV. Key model outputs are related to concentrations measured in experimental pharmacokinetic (PK) studies, e.g. concentrations in biopsies and blood. A new measure of microbicide prophylactic functionality, the Percent Protected, is calculated. This is the time dependent volume of the entire stroma (and thus fraction of host cells therein) in which Tenofovir diphosphate concentrations equal or exceed a target prophylactic value, e.g. an EC50.

Results show the prophylactic potentials of the studied microbicide vehicles against HIV infections. Key design parameters for each are addressed in application of the models. For a vaginal gel, fast spreading at small volume is more effective than slower spreading at high volume. Vaginal rings are shown to be most effective if inserted and retained as close to the fornix as possible. Because of the long half-life of Tenofovir diphosphate, temporary removal of the vaginal ring (after achieving steady state) for up to 24h does not appreciably diminish Percent Protected. However, full steady state (for the entire stromal volume) is not achieved until several days after ring insertion. Delivery of Tenofovir to the rectal mucosa by an enema is dominated by surface area of coated mucosa and whether the interiors of rectal crypts are filled with the enema fluid. For the enema 100% Percent Protected is achieved much more rapidly than for vaginal products, primarily because of the much thinner epithelial layer of the mucosa. For example, 100% Percent Protected can be achieved with a one minute enema application, and 15 minute wait time.

Results of these models have good agreement with experimental pharmacokinetic data, in animals and clinical trials. They also improve upon traditional, empirical PK modeling, and this is illustrated here. Our deterministic approach can inform design of sampling in clinical trials by indicating time periods during which significant changes in drug concentrations occur in different compartments. More fundamentally, the work here helps delineate the determinants of microbicide drug delivery. This information can be the key to improved, rational design of microbicide products and their dosage regimens.

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Abstract

The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.

This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.

I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.

Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.

II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.

The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.

In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.

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Purpose: There are two goals of this study. The first goal of this study is to investigate the feasibility of using classic textural feature extraction in radiotherapy response assessment among a unique cohort of early stage breast cancer patients who received the single-dose preoperative radiotherapy. The second goal of this study is to investigate the clinical feasibility of using classic texture features as potential biomarkers which are supplementary to regional apparent diffusion coefficient in gynecological cancer radiotherapy response assessment.

Methods and Materials: For the breast cancer study, 15 patients with early stage breast cancer were enrolled in this retrospective study. Each patient received a single-fraction radiation treatment, and DWI and DCE-MRI scans were conducted before and after the radiotherapy. DWI scans were acquired using a spin-echo EPI sequence with diffusion weighting factors of b = 0 and b = 500 mm2/s, and the apparent diffusion coefficient (ADC) maps were calculated. DCE-MRI scans were acquired using a T1-weighted 3D SPGR sequence with a temporal resolution of about 1 minute. The contrast agent (CA) was intravenously injected with a 0.1 mmol/kg bodyweight dose at 2 ml/s. Two parameters, volume transfer constant (Ktrans) and kep were analyzed using the two-compartment Tofts pharmacokinetic model. For pharmacokinetic parametric maps and ADC maps, 33 textural features were generated from the clinical target volume (CTV) in a 3D fashion using the classic gray level co-occurrence matrix (GLCOM) and gray level run length matrix (GLRLM). Wilcoxon signed-rank test was used to determine the significance of each texture feature’s change after the radiotherapy. The significance was set to 0.05 with Bonferroni correction.

For the gynecological cancer study, 12 female patients with gynecologic cancer treated with fractionated external beam radiotherapy (EBRT) combined with high dose rate (HDR) intracavitary brachytherapy were studied. Each patient first received EBRT treatment followed by five fractions of HDR treatment. Before EBRT and before each fraction of brachytherapy, Diffusion Weighted MRI (DWI-MRI) and CT scans were acquired. DWI scans were acquired in sagittal plane utilizing a spin-echo echo-planar imaging sequence with weighting factors of b = 500 s/mm2 and b = 1000 s/mm2, one set of images of b = 0 s/mm2 were also acquired. ADC maps were calculated using linear least-square fitting method. Distributed diffusion coefficient (DDC) maps and stretching parameter α were calculated. For ADC and DDC maps, 33 classic texture features were generated utilizing the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from high-risk clinical target volume (HR-CTV). Wilcoxon signed-rank statistics test was applied to determine the significance of each feature’s numerical value change after radiotherapy. Significance level was set to 0.05 with multi-comparison correction if applicable.

Results: For the breast cancer study, regarding ADC maps calculated from DWI-MRI, 24 out of 33 CTV features changed significantly after the radiotherapy. For DCE-MRI pharmacokinetic parameters, all 33 CTV features of Ktrans and 33 features of kep changed significantly.

For the gynecological cancer study, regarding ADC maps, 28 out of 33 HR-CTV texture features showed significant changes after the EBRT treatment. 28 out of 33 HR-CTV texture features indicated significant changes after HDR treatments. The texture features that indicated significant changes after HDR treatments are the same as those after EBRT treatment. 28 out of 33 HR-CTV texture features showed significant changes after whole radiotherapy treatment process. The texture features that indicated significant changes for the whole treatment process are the same as those after HDR treatments.

Conclusion: Initial results indicate that certain classic texture features are sensitive to radiation-induced changes. Classic texture features with significant numerical changes can be used in monitoring radiotherapy effect. This might suggest that certain texture features might be used as biomarkers which are supplementary to ADC and DDC for assessment of radiotherapy response in breast cancer and gynecological cancer.

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The work presented in this dissertation is focused on applying engineering methods to develop and explore probabilistic survival models for the prediction of decompression sickness in US NAVY divers. Mathematical modeling, computational model development, and numerical optimization techniques were employed to formulate and evaluate the predictive quality of models fitted to empirical data. In Chapters 1 and 2 we present general background information relevant to the development of probabilistic models applied to predicting the incidence of decompression sickness. The remainder of the dissertation introduces techniques developed in an effort to improve the predictive quality of probabilistic decompression models and to reduce the difficulty of model parameter optimization.

The first project explored seventeen variations of the hazard function using a well-perfused parallel compartment model. Models were parametrically optimized using the maximum likelihood technique. Model performance was evaluated using both classical statistical methods and model selection techniques based on information theory. Optimized model parameters were overall similar to those of previously published Results indicated that a novel hazard function definition that included both ambient pressure scaling and individually fitted compartment exponent scaling terms.

We developed ten pharmacokinetic compartmental models that included explicit delay mechanics to determine if predictive quality could be improved through the inclusion of material transfer lags. A fitted discrete delay parameter augmented the inflow to the compartment systems from the environment. Based on the observation that symptoms are often reported after risk accumulation begins for many of our models, we hypothesized that the inclusion of delays might improve correlation between the model predictions and observed data. Model selection techniques identified two models as having the best overall performance, but comparison to the best performing model without delay and model selection using our best identified no delay pharmacokinetic model both indicated that the delay mechanism was not statistically justified and did not substantially improve model predictions.

Our final investigation explored parameter bounding techniques to identify parameter regions for which statistical model failure will not occur. When a model predicts a no probability of a diver experiencing decompression sickness for an exposure that is known to produce symptoms, statistical model failure occurs. Using a metric related to the instantaneous risk, we successfully identify regions where model failure will not occur and identify the boundaries of the region using a root bounding technique. Several models are used to demonstrate the techniques, which may be employed to reduce the difficulty of model optimization for future investigations.

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La circulation extracorporelle (CEC) est une technique utilisée en chirurgie cardiaque effectuée des milliers de fois chaque jour à travers le monde. L’instabilité hémodynamique associée au sevrage de la CEC difficile constitue la principale cause de mortalité en chirurgie cardiaque et l’hypertension pulmonaire (HP) a été identifiée comme un des facteurs de risque les plus importants. Récemment, une hypothèse a été émise suggérant que l'administration prophylactique (avant la CEC) de la milrinone par inhalation puisse avoir un effet préventif et faciliter le sevrage de la CEC chez les patients atteints d’HP. Toutefois, cette indication et voie d'administration pour la milrinone n'ont pas encore été approuvées par les organismes réglementaires. Jusqu'à présent, la recherche clinique sur la milrinone inhalée s’est principalement concentrée sur l’efficacité hémodynamique et l'innocuité chez les patients cardiaques, bien qu’aucun biomarqueur n’ait encore été établi. La dose la plus appropriée pour l’administration par nébulisation n'a pas été déterminée, de même que la caractérisation des profils pharmacocinétiques (PK) et pharmacodynamiques (PD) suite à l'inhalation. L'objectif de notre recherche consistait à caractériser la relation exposition-réponse de la milrinone inhalée administrée chez les patients subissant une chirurgie cardiaque sous CEC. Une méthode analytique par chromatographie liquide à haute performance couplée à un détecteur ultraviolet (HPLC-UV) a été optimisée et validée pour le dosage de la milrinone plasmatique suite à l’inhalation et s’est avérée sensible et précise. La limite de quantification (LLOQ) était de 1.25 ng/ml avec des valeurs de précision intra- et inter-dosage moyennes (CV%) <8%. Des patients souffrant d’HP pour lesquels une chirurgie cardiaque sous CEC était prévue ont d’abord été recrutés pour une étude pilote (n=12) et, par la suite, pour une étude à plus grande échelle (n=28) où la milrinone (5 mg) était administrée par inhalation pré-CEC. Dans l'étude pilote, nous avons comparé l'exposition systémique de la milrinone peu après son administration avec un nébuliseur pneumatique ou un nébuliseur à tamis vibrant. L’efficacité des nébuliseurs en termes de dose émise et dose inhalée a également été déterminée in vitro. Dans l'étude à plus grande échelle conduite en utilisant exclusivement le nébuliseur à tamis vibrant, la dose inhalée in vivo a été estimée et le profil pharmacocinétique de la milrinone inhalée a été pleinement caractérisé aux niveaux plasmatique et urinaire. Le ratio de la pression artérielle moyenne sur la pression artérielle pulmonaire moyenne (PAm/PAPm) a été choisi comme biomarqueur PD. La relation exposition-réponse de la milrinone a été caractérisée pendant la période d'inhalation en étudiant la relation entre l'aire sous la courbe de l’effet (ASCE) et l’aire sous la courbe des concentrations plasmatiques (ASC) de chacun des patients. Enfin, le ratio PAm/PAPm a été exploré comme un prédicteur potentiel de sortie de CEC difficile dans un modèle de régression logistique. Les expériences in vitro ont démontré que les doses émises étaient similaires pour les nébuliseurs pneumatique (64%) et à tamis vibrant (68%). Cependant, la dose inhalée était 2-3 fois supérieure (46% vs 17%) avec le nébuliseur à tamis vibrant, et ce, en accord avec les concentrations plasmatiques. Chez les patients, en raison des variations au niveau des facteurs liés au circuit et au ventilateur causant une plus grande dose expirée, la dose inhalée a été estimée inférieure (30%) et cela a été confirmé après récupération de la dose de milrinone dans l'urine 24 h (26%). Les concentrations plasmatiques maximales (Cmax: 41-189 ng/ml) et l'ampleur de la réponse maximale ΔRmax-R0 (0-65%) ont été observées à la fin de l'inhalation (10-30 min). Les données obtenues suite aux analyses PK sont en accord avec les données publiées pour la milrinone intraveineuse. Après la période d'inhalation, les ASCE individuelles étaient directement reliées aux ASC (P=0.045). Enfin, notre biomarqueur PD ainsi que la durée de CEC ont été identifiés comme des prédicteurs significatifs de la sortie de CEC difficile. La comparaison des ASC et ASCE correspondantes a fourni des données préliminaires supportant une preuve de concept pour l'utilisation du ratio PAm/PAPm comme biomarqueur PD prometteur et justifie de futures études PK/PD. Nous avons pu démontrer que la variation du ratio PAm/PAPm en réponse à la milrinone inhalée contribue à la prévention de la sortie de CEC difficile.

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La diminution des doses administrées ou même la cessation complète d'un traitement chimiothérapeutique est souvent la conséquence de la réduction du nombre de neutrophiles, qui sont les globules blancs les plus fréquents dans le sang. Cette réduction dans le nombre absolu des neutrophiles, aussi connue sous le nom de myélosuppression, est précipitée par les effets létaux non spécifiques des médicaments anti-cancéreux, qui, parallèlement à leur effet thérapeutique, produisent aussi des effets toxiques sur les cellules saines. Dans le but d'atténuer cet impact myélosuppresseur, on administre aux patients un facteur de stimulation des colonies de granulocytes recombinant humain (rhG-CSF), une forme exogène du G-CSF, l'hormone responsable de la stimulation de la production des neutrophiles et de leurs libération dans la circulation sanguine. Bien que les bienfaits d'un traitement prophylactique avec le G-CSF pendant la chimiothérapie soient bien établis, les protocoles d'administration demeurent mal définis et sont fréquemment déterminés ad libitum par les cliniciens. Avec l'optique d'améliorer le dosage thérapeutique et rationaliser l'utilisation du rhG-CSF pendant le traitement chimiothérapeutique, nous avons développé un modèle physiologique du processus de granulopoïèse, qui incorpore les connaissances actuelles de pointe relatives à la production des neutrophiles des cellules souches hématopoïétiques dans la moelle osseuse. À ce modèle physiologique, nous avons intégré des modèles pharmacocinétiques/pharmacodynamiques (PK/PD) de deux médicaments: le PM00104 (Zalypsis®), un médicament anti-cancéreux, et le rhG-CSF (filgrastim). En se servant des principes fondamentaux sous-jacents à la physiologie, nous avons estimé les paramètres de manière exhaustive sans devoir recourir à l'ajustement des données, ce qui nous a permis de prédire des données cliniques provenant de 172 patients soumis au protocol CHOP14 (6 cycles de chimiothérapie avec une période de 14 jours où l'administration du rhG-CSF se fait du jour 4 au jour 13 post-chimiothérapie). En utilisant ce modèle physio-PK/PD, nous avons démontré que le nombre d'administrations du rhG-CSF pourrait être réduit de dix (pratique actuelle) à quatre ou même trois administrations, à condition de retarder le début du traitement prophylactique par le rhG-CSF. Dans un souci d'applicabilité clinique de notre approche de modélisation, nous avons investigué l'impact de la variabilité PK présente dans une population de patients, sur les prédictions du modèle, en intégrant des modèles PK de population (Pop-PK) des deux médicaments. En considérant des cohortes de 500 patients in silico pour chacun des cinq scénarios de variabilité plausibles et en utilisant trois marqueurs cliniques, soient le temps au nadir des neutrophiles, la valeur du nadir, ainsi que l'aire sous la courbe concentration-effet, nous avons établi qu'il n'y avait aucune différence significative dans les prédictions du modèle entre le patient-type et la population. Ceci démontre la robustesse de l'approche que nous avons développée et qui s'apparente à une approche de pharmacologie quantitative des systèmes (QSP). Motivés par l'utilisation du rhG-CSF dans le traitement d'autres maladies, comme des pathologies périodiques telles que la neutropénie cyclique, nous avons ensuite soumis l'étude du modèle au contexte des maladies dynamiques. En mettant en évidence la non validité du paradigme de la rétroaction des cytokines pour l'administration exogène des mimétiques du G-CSF, nous avons développé un modèle physiologique PK/PD novateur comprenant les concentrations libres et liées du G-CSF. Ce nouveau modèle PK a aussi nécessité des changements dans le modèle PD puisqu’il nous a permis de retracer les concentrations du G-CSF lié aux neutrophiles. Nous avons démontré que l'hypothèse sous-jacente de l'équilibre entre la concentration libre et liée, selon la loi d'action de masse, n'est plus valide pour le G-CSF aux concentrations endogènes et mènerait en fait à la surestimation de la clairance rénale du médicament. En procédant ainsi, nous avons réussi à reproduire des données cliniques obtenues dans diverses conditions (l'administration exogène du G-CSF, l'administration du PM00104, CHOP14). Nous avons aussi fourni une explication logique des mécanismes responsables de la réponse physiologique aux deux médicaments. Finalement, afin de mettre en exergue l’approche intégrative en pharmacologie adoptée dans cette thèse, nous avons démontré sa valeur inestimable pour la mise en lumière et la reconstruction des systèmes vivants complexes, en faisant le parallèle avec d’autres disciplines scientifiques telles que la paléontologie et la forensique, où une approche semblable a largement fait ses preuves. Nous avons aussi discuté du potentiel de la pharmacologie quantitative des systèmes appliquées au développement du médicament et à la médecine translationnelle, en se servant du modèle physio-PK/PD que nous avons mis au point.

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Colistin, a cationic polypeptide antibiotic, has reappeared in human medicine as a last-line treatment option for multidrug-resistant Gram-negative bacteria (MDR-GNB). Colistin is widely used in veterinary medicine for the treatment of gastrointestinal infections caused by Enterobacteriaceae. GNB resistant to colistin owing to chromosomal mutations have already been reported both in human and veterinary medicine, however several recent studies have just identified a plasmid-mediated mcr-1 gene encoding for colistin resistance in Escherichia coli colistin resistance. The discovery of a non-chromosomal mechanism of colistin resistance in E. coli has led to strong reactions in the scientific community and to concern among physicians and veterinarians. Colistin use in food animals and particularly in pig production has been singled out as responsible for the emergence of colistin resistance. The present review will focus mainly on the possible link between colistin use in pigs and the spread of colistin resistance in Enterobacteriaceae. First we demonstrate a possible link between Enterobacteriaceae resistance emergence and oral colistin pharmacokinetics/pharmacodynamics and its administration modalities in pigs. We then discuss the potential impact of colistin use in pigs on public health with respect to resistance. We believe that colistin use in pig production should be re-evaluated and its dosing and usage optimised. Moreover, the search for competitive alternatives to using colistin with swine is of paramount importance to preserve the effectiveness of this antibiotic for the treatment of MDR-GNB infections in human medicine.

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An exploratory phase II biomarker-embedded trial (LPT109747; NCT00526669) designed to determine the association of lapatinib-induced fluoropyrimidine gene changes with efficacy of lapatinib plus capecitabine as first-line treatment for advanced gastric cancer or gastroesophageal junction adenocarcinoma independent of tumor HER2 status. Tumor biopsies obtained before and after 7-day lapatinib (1,250 mg) to analyze changes in gene expression, followed by a 14-day course of capecitabine (1,000 mg/m(2) twice daily, 14/21 days) plus lapatinib 1,250 mg daily. Blood samples were acquired for pharmacokinetic analysis. Primary clinical objectives were response rate (RR) and 5-month progression-free survival (PFS). Secondary objectives were overall survival (OS), PFS, time to response, duration of response, toxicity, and identification of associations between lapatinib pharmacokinetics and biomarker endpoints. Primary biomarker objectives were modulation of 5-FU-pathway genes by lapatinib, effects of germline SNPs on treatment outcome, and trough steady-state plasma lapatinib concentrations. Sixty-eight patients were enrolled; (75% gastric cancer, 25% gastroesophageal junction). Twelve patients (17.9%) had confirmed partial response, 31 (46.3%) had stable disease, and 16 (23.9%) had progressive disease. Median PFS and OS were 3.3 and 6.3 months, respectively. Frequent adverse events included diarrhea (45%), decreased appetite (39%), nausea (36%), and fatigue (36%). Lapatinib induced no changes in gene expression from baseline and no significant associations were found for SNPs analyzed. Elevated baseline HER3 mRNA expression was associated with a higher RR (33% vs. 0%; P = 0.008). Lapatinib plus capecitabine was well tolerated, demonstrating modest antitumor activity in patients with advanced gastric cancer. The association of elevated HER3 and RR warrants further investigation as an important player for HER-targeted regimens in combination with capecitabine

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The free fatty acid receptor 1 (FFA1), a G protein-coupled receptor (GPCR) naturally activated by long-chain fatty acids is a novel target for the treatment of metabolic diseases. The basic amine spirocyclic periphery of Eli Lilly's drug candidate LY2881835 for treatment of type 2 diabetes mellitus (which reached phase I clinical trials) inspired a series of novel FFA1 agonists. These were designed to incorporate the 3-[4-(benzyloxy)phenyl]propanoic acid pharmacophore core decorated with a range of spirocyclic motifs. The latter were prepared via the Prins cyclization and subsequent modification of the 4-hydroxytetrahydropyran moiety in the Prins product. Here, we synthesize 19 compounds and test for FFA1 activity. Within this pilot set, a nanomolar potency (EC50=55nM) was reached. Four lead compounds (EC50 range 55-410nM) were characterized for aqueous solubility, metabolic stability, plasma protein binding and Caco-2 permeability. While some instability in the presence of mouse liver microsomes was noted, mouse pharmacokinetic profile of the compound having the best overall ADME properties was evaluated to reveal acceptable bioavailability (F=10.3%) and plasma levels achieved on oral administration.

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La transplantation de cellules souches hématopoïétiques (CSH) constitue une avenue thérapeutique potentiellement curative pour plusieurs cancers hématologiques comme la leucémie. L’utilisation d’une thérapie immunosuppressive pour prévenir la maladie du greffon contre l’hôte (GvHD) est un déterminant majeur du succès de la greffe. Malgré tout, cette complication survient chez 25 à 50% des transplantés et est une cause majeure de mortalité. L’optimisation du régime d’immunosuppression est un facteur facilement modifiable qui pourrait améliorer le pronostic des patients. Particulièrement, les polymorphismes du génome du donneur ou du receveur dans les voies pharmacogénomiques des immunosuppresseurs pourraient influencer l’exposition et l’action de ces médicaments, de même que le pronostic du patient. Le profilage de 20 pharmacogènes prioritaires chez des paires de donneurs-receveurs en greffe de CSH a permis d’identifier des variations génétiques liées au risque de la GvHD aiguë. Principalement, le statut génétique du receveur pour les protéines ABCC1 et ABCC2, impliquées dans le transport du méthotrexate (MTX), ainsi que des cibles moléculaires de ce médicament (ATIC et MTHFR) ont été associées au risque de GvHD aiguë. Similairement, le NFATc1, codant pour une cible moléculaire de la cyclosporine, augmentait lui aussi le risque de la maladie. Les porteurs de deux génotypes à risque et plus étaient particulièrement prédisposés à développer cette complication. Par surcroît, le statut génétique du donneur influençait également le pronostic du receveur après la greffe. Entre autres, des allèles protecteurs ont été identifiés dans les voies liées au transport (SLC19A1) et à l’action du MTX (DHFR). Inversement, NFATc2 a été associé à une augmentation du risque de GvHD aiguë. Afin de mieux comprendre les associations observées entre ces marqueurs génétiques et le risque de GvHD aiguë, une étude prospective innovante est en cours chez des greffés de CSH. Cette étude permettra d’étudier comment la génétique du patient ou du donneur peut influencer la pharmacocinétique et la pharmacodynamie des immunosuppresseurs, de même que leurs liens avec la GvHD aiguë. Ces paramètres sont quantifiés grâce à des approches analytiques que nous avons mises au point afin de répondre aux besoins spécifiques et uniques de cette étude. Les approches proposées dans cette thèse sont complémentaires aux méthodes classiques de suivi des immunosuppresseurs et pourraient aider à optimiser la pharmacothérapie du patient. Une meilleure identification des patients à haut risque de GvHD aiguë avant la greffe, basée sur des marqueurs pharmacogénomiques identitaires, pourrait guider le choix de la prophylaxie immunosuppressive, et ainsi améliorer l’issue clinique de la greffe.

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Este estudo incide sobre as características que a presença do ião flúor em moléculas concede. Mais concretamente em fluoroquinolonas, antibióticos que cada vez são mais utilizados. Fez-se uma analise de vários parâmetros para obtermos informação sobre a interação fármaco-receptor nas fluoroquinolonas. Sendo para isso utilizadas técnicas de caracterização química computacional para conseguirmos caracterizar eletronicamente e estruturalmente (3D) as fluoroquinolonas em complemento aos métodos semi-empíricos utilizados inicialmente. Como é sabido, a especificidade e a afinidade para o sitio alvo, é essencial para eficácia de um fármaco. As fluoroquinolonas sofreram um grande desenvolvimento desde a primeira quinolona sintetizada em 1958, sendo que desde ai foram sintetizadas inúmeros derivados da mesma. Este facto deve-se a serem facilmente manipuladas, derivando fármacos altamente potentes, espectro alargado, factores farmacocinéticos optimizados e efeitos adversos reduzidos. A grande alteração farmacológica para o aumento do interesse neste grupo, foi a substituição em C6 de um átomo de flúor em vez de um de hidrogénio. Para obtermos as informações sobre a influência do ião flúor sobre as propriedades estruturais e electrónicas das fluoroquinolonas, foi feita uma comparação entre a fluoroquinolona com flúor em C6 e com hidrogénio em C6. As quatro fluoroquinolonas presentes neste estudo foram: ciprofloxacina, moxiflocacina, sparfloxacina e pefloxacina. As informações foram obtidas por programas informáticos de mecânica quântica e molecular. Concluiu-se que a presença de substituinte flúor não modificava de forma significativa a geometria das moléculas mas sim a distribuição da carga no carbono vicinal e nos átomos em posição alfa, beta e gama relativamente a este. Esta modificação da distribuição electrónica pode condicionar a ligação do fármaco ao receptor, modificando a sua actividade farmacológica.