949 resultados para Drug development


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Human African trypanosomiasis, also known as sleeping sickness, is a major cause of death in Africa, and for which there are no safe and effective treatments available. The enzyme aldolase from Trypanosoma brucei is an attractive, validated target for drug development. A series of alkyl‑glycolamido and alkyl-monoglycolate derivatives was studied employing a combination of drug design approaches. Three-dimensional quantitative structure-activity relationships (3D QSAR) models were generated using the comparative molecular field analysis (CoMFA). Significant results were obtained for the best QSAR model (r2 = 0.95, non-cross-validated correlation coefficient, and q2 = 0.80, cross-validated correlation coefficient), indicating its predictive ability for untested compounds. The model was then used to predict values of the dependent variables (pKi) of an external test set,the predicted values were in good agreement with the experimental results. The integration of 3D QSAR, molecular docking and molecular dynamics simulations provided further insight into the structural basis for selective inhibition of the target enzyme.

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During the previous 10 years, global R&D expenditure in the pharmaceuticals and biotechnology sector has steadily increased, without a corresponding increase in output of new medicines. To address this situation, the biopharmaceutical industry's greatest need is to predict the failures at the earliest possible stage of the drug development process. A major key to reducing failures in drug screenings is the development and use of preclinical models that are more predictive of efficacy and safety in clinical trials. Further, relevant animal models are needed to allow a wider testing of novel hypotheses. Key to this is the developing, refining, and validating of complex animal models that directly link therapeutic targets to the phenotype of disease, allowing earlier prediction of human response to medicines and identification of safety biomarkers. Morehover, well-designed animal studies are essential to bridge the gap between test in cell cultures and people. Zebrafish is emerging, complementary to other models, as a powerful system for cancer studies and drugs discovery. We aim to investigate this research area designing a new preclinical cancer model based on the in vivo imaging of zebrafish embryogenesis. Technological advances in imaging have made it feasible to acquire nondestructive in vivo images of fluorescently labeled structures, such as cell nuclei and membranes, throughout early Zebrafishsh embryogenesis. This In vivo image-based investigation provides measurements for a large number of features at cellular level and events including nuclei movements, cells counting, and mitosis detection, thereby enabling the estimation of more significant parameters such as proliferation rate, highly relevant for investigating anticancer drug effects. In this work, we designed a standardized procedure for accessing drug activity at the cellular level in live zebrafish embryos. The procedure includes methodologies and tools that combine imaging and fully automated measurements of embryonic cell proliferation rate. We achieved proliferation rate estimation through the automatic classification and density measurement of epithelial enveloping layer and deep layer cells. Automatic embryonic cells classification provides the bases to measure the variability of relevant parameters, such as cell density, in different classes of cells and is finalized to the estimation of efficacy and selectivity of anticancer drugs. Through these methodologies we were able to evaluate and to measure in vivo the therapeutic potential and overall toxicity of Dbait and Irinotecan anticancer molecules. Results achieved on these anticancer molecules are presented and discussed; furthermore, extensive accuracy measurements are provided to investigate the robustness of the proposed procedure. Altogether, these observations indicate that zebrafish embryo can be a useful and cost-effective alternative to some mammalian models for the preclinical test of anticancer drugs and it might also provides, in the near future, opportunities to accelerate the process of drug discovery.

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Pharmacokinetic and pharmacodynamic properties of a chiral drug can significantly differ between application of the racemate and single enantiomers. During drug development, the characteristics of candidate compounds have to be assessed prior to clinical testing. Since biotransformation significantly influences drug actions in an organism, metabolism studies represent a crucial part of such tests. Hence, an optimized and economical capillary electrophoretic method for on-line studies of the enantioselective drug metabolism mediated by cytochrome P450 enzymes was developed. It comprises a diffusion-based procedure, which enables mixing of the enzyme with virtually any compound inside the nanoliter-scale capillary reactor and without the need of additional optimization of mixing conditions. For CYP3A4, ketamine as probe substrate and highly sulfated γ-cyclodextrin as chiral selector, improved separation conditions for ketamine and norketamine enantiomers compared to a previously published electrophoretically mediated microanalysis method were elucidated. The new approach was thoroughly validated for the CYP3A4-mediated N-demethylation pathway of ketamine and applied to the determination of its kinetic parameters and the inhibition characteristics in presence of ketoconazole and dexmedetomidine. The determined parameters were found to be comparable to literature data obtained with different techniques. The presented method constitutes a miniaturized and cost-effective tool, which should be suitable for the assessment of the stereoselective aspects of kinetic and inhibition studies of cytochrome P450-mediated metabolic steps within early stages of the development of a new drug.

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Anticancer drugs typically are administered in the clinic in the form of mixtures, sometimes called combinations. Only in rare cases, however, are mixtures approved as drugs. Rather, research on mixtures tends to occur after single drugs have been approved. The goal of this research project was to develop modeling approaches that would encourage rational preclinical mixture design. To this end, a series of models were developed. First, several QSAR classification models were constructed to predict the cytotoxicity, oral clearance, and acute systemic toxicity of drugs. The QSAR models were applied to a set of over 115,000 natural compounds in order to identify promising ones for testing in mixtures. Second, an improved method was developed to assess synergistic, antagonistic, and additive effects between drugs in a mixture. This method, dubbed the MixLow method, is similar to the Median-Effect method, the de facto standard for assessing drug interactions. The primary difference between the two is that the MixLow method uses a nonlinear mixed-effects model to estimate parameters of concentration-effect curves, rather than an ordinary least squares procedure. Parameter estimators produced by the MixLow method were more precise than those produced by the Median-Effect Method, and coverage of Loewe index confidence intervals was superior. Third, a model was developed to predict drug interactions based on scores obtained from virtual docking experiments. This represents a novel approach for modeling drug mixtures and was more useful for the data modeled here than competing approaches. The model was applied to cytotoxicity data for 45 mixtures, each composed of up to 10 selected drugs. One drug, doxorubicin, was a standard chemotherapy agent and the others were well-known natural compounds including curcumin, EGCG, quercetin, and rhein. Predictions of synergism/antagonism were made for all possible fixed-ratio mixtures, cytotoxicities of the 10 best-scoring mixtures were tested, and drug interactions were assessed. Predicted and observed responses were highly correlated (r2 = 0.83). Results suggested that some mixtures allowed up to an 11-fold reduction of doxorubicin concentrations without sacrificing efficacy. Taken together, the models developed in this project present a general approach to rational design of mixtures during preclinical drug development. ^

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The brain cholecystokinin-B/gastrin receptor (CCK-BR) is a major target for drug development because of its postulated role in modulating anxiety, memory, and the perception of pain. Drug discovery efforts have resulted in the identification of small synthetic molecules that can selectively activate this receptor subtype. These drugs include the peptide-derived compound PD135,158 as well as the nonpeptide benzodiazepine-based ligand, L-740,093 (S enantiomer). We now report that the maximal level of receptor-mediated second messenger signaling that can be achieved by these compounds (drug efficacy) markedly differs among species homologs of the CCK-BR. Further analysis reveals that the observed differences in drug efficacy are in large part explained by single or double aliphatic amino acid substitutions between respective species homologs. This interspecies variability in ligand efficacy introduces the possibility of species differences in receptor-mediated function, an important consideration when selecting animal models for preclinical drug testing. The finding that even single amino acid substitutions can significantly affect drug efficacy prompted us to examine ligand-induced signaling by a known naturally occurring human CCK-BR variant (glutamic acid replaced by lysine in position 288; 288E → K). When examined using the 288E → K receptor, the efficacies of both PD135,158 and L-740,093 (S) were markedly increased compared with values obtained with the wild-type human protein. These observations suggest that functional variability resulting from human receptor polymorphisms may contribute to interindividual differences in drug effects.

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Intracellular schizonts of the apicomplexans Theileria annulata and Theileria parva immortalize bovine leucocytes thereby causing fatal immunoproliferative diseases. Buparvaquone, a hydroxynaphthoquinone related to parvaquone, is the only drug available against Theileria. The drug is only effective at the onset of infection and emerging resistance underlines the need for identifying alternative compounds. Current drug assays employ monitoring of proliferation of infected cells, with apoptosis of the infected host cell as a read-out, but it is often unclear whether active compounds directly impair the viability of the parasite or primarily induce host cell death. We here report on the development of a quantitative reverse transcriptase real time PCR method based on two Theileria genes, tasp and tap104, which are both expressed in schizonts. Upon in vitro treatment of T. annulata infected bovine monocytes with buparvaquone, TaSP and Tap104 mRNA expression levels significantly decreased in relation to host cell actin already within 4 h of drug exposure, while significant differences in host cell proliferation were detectable only after 48-72 h. TEM revealed marked alterations of the schizont ultrastructure already after 2 h of buparvaquone treatment, while the host cell remained unaffected. Expression of TaSP and Tap104 proteins showed a marked decrease only after 24 h. Therefore, the analysis of expression levels of mRNA coding for TaSP and Tap104 allows to directly measuring impairment of parasite viability. We subsequently applied this method using a series of compounds affecting different targets in other apicomplexan parasites, and show that monitoring of TaSP- and Tap104 mRNA levels constitutes a suitable tool for anti-theilerial drug development.

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Despite the enormous economic importance of Neospora caninum related veterinary diseases, the number of effective therapeutic agents is relatively small. Development of new therapeutic strategies to combat the economic impact of neosporosis remains an important scientific endeavor. This study demonstrates molecular, structural and phenotypic evidence that N. caninum calcium-dependent protein kinase 1 (NcCDPK1) is a promising molecular target for neosporosis drug development. Recombinant NcCDPK1 was expressed, purified and screened against a select group of bumped kinase inhibitors (BKIs) previously shown to have low IC50s against Toxoplasma gondii CDPK1 and T. gondii tachyzoites. NcCDPK1 was inhibited by low concentrations of BKIs. The three-dimensional structure of NcCDPK1 in complex with BKIs was studied crystallographically. The BKI-NcCDPK1 structures demonstrated the structural basis for potency and selectivity. Calcium-dependent conformational changes in solution as characterized by small-angle X-ray scattering are consistent with previous structures in low Calcium-state but different in the Calcium-bound active state than predicted by X-ray crystallography. BKIs effectively inhibited N. caninum tachyzoite proliferation in vitro. Electron microscopic analysis of N. caninum cells revealed ultra-structural changes in the presence of BKI compound 1294. BKI compound 1294 interfered with an early step in Neospora tachyzoite host cell invasion and egress. Prolonged incubation in the presence of 1294 interfered produced observable interference with viability and replication. Oral dosing of BKI compound 1294 at 50 mg/kg for 5 days in established murine neosporosis resulted in a 10-fold reduced cerebral parasite burden compared to untreated control. Further experiments are needed to determine the PK, optimal dosage, and duration for effective treatment in cattle and dogs, but these data demonstrate proof-of-concept for BKIs, and 1294 specifically, for therapy of bovine and canine neosporosis.

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National Highway Traffic Safety Administration, Washington, D.C.

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

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Free drug measurement and pharmacodymanic markers provide the opportunity for a better understanding of drug efficacy and toxicity. High-performance liquid chromatography (HPLC)-mass spectrometry (MS) is a powerful analytical technique that could facilitate the measurement of free drug and these markers. Currently, there are very few published methods for the determination of free drug concentrations by HPLC-MS. The development of atmospheric pressure ionisation sources, together with on-line microdialysis or on-line equilibrium dialysis and column switching techniques have reduced sample run times and increased assay efficiency. The availability of such methods will aid in drug development and the clinical use of certain drugs, including anti-convulsants, anti-arrhythmics, immunosuppressants, local anaesthetics, anti-fungals and protease inhibitors. The history of free drug measurement and an overview of the current HPLC-MS applications for these drugs are discussed. Immunosuppressant drugs are used as an example for the application of HPLC-MS in the measurement of drug pharmacodynamics. Potential biomarkers of immunosuppression that could be measured by HPLC-MS include purine nucleoside/nucleotides, drug-protein complexes and phosphorylated peptides. At the proteomic level, two-dimensional gel electrophoresis combined with matrix-assisted laser desorption/ionisation time-of-flight (TOF) MS is a powerful tool for identifying proteins involved in the response to inflammatory mediators. (C) 2003 Elsevier Science B.V. All rights reserved.

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Multidimensional compound optimization is a new paradigm in the drug discovery process, yielding efficiencies during early stages and reducing attrition in the later stages of drug development. The success of this strategy relies heavily on understanding this multidimensional data and extracting useful information from it. This paper demonstrates how principled visualization algorithms can be used to understand and explore a large data set created in the early stages of drug discovery. The experiments presented are performed on a real-world data set comprising biological activity data and some whole-molecular physicochemical properties. Data visualization is a popular way of presenting complex data in a simpler form. We have applied powerful principled visualization methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), to help the domain experts (screening scientists, chemists, biologists, etc.) understand and draw meaningful decisions. We also benchmark these principled methods against relatively better known visualization approaches, principal component analysis (PCA), Sammon's mapping, and self-organizing maps (SOMs), to demonstrate their enhanced power to help the user visualize the large multidimensional data sets one has to deal with during the early stages of the drug discovery process. The results reported clearly show that the GTM and HGTM algorithms allow the user to cluster active compounds for different targets and understand them better than the benchmarks. An interactive software tool supporting these visualization algorithms was provided to the domain experts. The tool facilitates the domain experts by exploration of the projection obtained from the visualization algorithms providing facilities such as parallel coordinate plots, magnification factors, directional curvatures, and integration with industry standard software. © 2006 American Chemical Society.

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A novel dissolution method was developed, suitable for powder mixtures, based on the USP basket apparatus. The baskets were modified such that the powder mixtures were retained within the baskets and not dispersed, a potential difficulty that may arise when using conventional USP basket and paddle apparatus. The advantages of this method were that the components of the mixtures were maintained in close proximity, maximizing any drug:excipient interaction and leading to more linear dissolution profiles. Two weakly acidic model drugs, ibuprofen and acetaminophen, and a selection of pharmaceutical excipients, including potential dissolution-enhancing alkalizing agents, were chosen for investigation. Dissolution profiles were obtained for simple physical mixtures. The f1 fit factor values, calculated using pure drug as the reference material, demonstrated a trend in line with expectations, with several dissolution enhancers apparent for both drugs. Also, the dissolution rates were linear over substantial parts of the profiles. For both drugs, a rank order comparison between the f1 fit factor and calculated dissolution rate, obtained from the linear section of the dissolution profile, demonstrated a correlation using a significance level of P=0.05. The method was proven to be suitable for discriminating between the effects of excipients on the dissolution of the model drugs. The method design produced dissolution profiles where the dissolution rate was linear for a substantial time, allowing determination of the dissolution rate without mathematical transformation of the data. This method may be suitable as a preliminary excipient-screening tool in the drug formulation development process.

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Formulation of solid dispersions is one of the effective methods to increase the rate of solubilization and dissolution of poorly soluble drugs. Solid dispersions of chloramphenicol (CP) and sulphamethoxazole (SX) as model drugs were prepared by melt fusion method using polyethylene glycol 8000 (PEG 8000) as an inert carrier. The dissolution rate of CP and SX were rapid from solid dispersions with low drug and high polymer content. Characterization was performed using fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC) and scanning electron microscopy (SEM). FTIR analysis for the solid dispersions of CP and SX showed that there was no interaction between PEG 8000 and the drugs. Hyper-DSC studies revealed that CP and SX were converted into an amorphous form when formulated as solid dispersion in PEG 8000. Mathematical analysis of the release kinetics demonstrated that drug release from the various formulations followed different mechanisms. Permeability studies demonstrated that both CP and SX when formulated as solid dispersions showed enhanced permeability across Caco-2 cells and CP can be classified as well-absorbed compound when formulated as solid dispersions. © 2013 Informa Healthcare USA, Inc.

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Assessment of oral drug bioavailability is an important parameter for new chemical entities (NCEs) in drug development cycle. After evaluating the pharmacological response of these new molecules, the following critical stage is to investigate their in vitro permeability. Despite the great success achieved by prodrugs, covalent linking the drug molecule with a hydrophobic moiety might result in a new entity that might be toxic or ineffective. Therefore, an alternative that would improve the drug uptake without affecting the efficacy of the drug molecule would be advantageous. The aim of the current study is to investigate the effect of ion-pairing on the permeability profile of a model drug: indomethacin (IND) to understand the mechanism behind the permeability improvement across Caco-2 monolayers. Arginine and lysine formed ion-pairs with IND at various molar ratios 1:1, 1:2, 1:4 and 1:8 as reflected by the double reciprocal graphs. The partitioning capacities of the IND were evaluated using octanol/water partitioning studies and the apparent permeabilities (P app) were measured across Caco-2 monolayers for the different formulations. Partitioning studies reflected the high hydrophobicity of IND (Log P = 3) which dropped upon increasing the concentrations of arginine/lysine in the ion pairs. Nevertheless, the prepared ion pairs improved IND permeability especially after 60 min of the start of the experiment. Coupling partitioning and permeability results suggest a decrease in the passive transcellular uptake due to the drop in IND portioning capacities and a possible involvement of active carriers. Future work will investigate which transport gene might be involved in the absorption of the ion paired formulations using molecular biology technologies. © 2014 Elsevier B.V. All rights reserved.

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Areas covered: The review discusses the main challenges of ODT manufacturing process and the emerging solutions featured at early drug development stages. The research specifically describes the methods reported for taste masking/assessment and solubilisation of unpalatable and poorly soluble drugs, respectively. Furthermore, this review highlights the techniques used for developing modified-release ODTs, an emerging area in the field. In addition, it also discusses the poor flowability and segregation problems of directly compressed powders. Moreover, the review describes the tests reported in the literature for ODT disintegration time assessment since a universal technique is still non-existent. Expert opinion: The approaches used to overcome the manufacturing challenges often have a bearing on the price of the end product. However, despite the technical and regulatory challenges, ODTs can offer many advantages over the conventional dosage forms if accompanied by suitable adjuvant technologies and in vitro analytical tools. © 2014 Informa UK, Ltd. Introduction: Orally disintegrating tablets (ODTs) provide several advantages over conventional tablets such as suitability for patients with swallowing difficulties and faster onset of action. The manufacture of ODTs by compression/tableting offers a practical and cost-effective strategy over the freeze drying (lyophilisation) method. Nonetheless, the FDA recommends a disintegration time of 30 s and a maximum weight of 500 mg for a tablet to be labelled as an ODT. These requirements, alongside other desirable product properties, have created a number of challenges for the formulator to overcome while developing compressed ODTs.