Monitoring the activation state of the insulin receptor using bioluminescence resonance energy transfer

We have developed a procedure based on bioluminescence resonance energy transfer (BRET) to monitor the activation state of the insulin receptor in vitro. Human insulin receptor cDNA was fused to either Renilla luciferase (Rluc) or enhanced yellow fluorescent protein (EYFP) coding sequences. Fusion insulin receptors were partially purified by wheat-germ lectin chromatography from human embryonic kidney 293 cells cotransfected with these constructs. The conformational change induced by insulin on its receptor could be detected as an energy transfer (BRET signal) between Rluc and EYFP. BRET signal parallels insulin-induced autophosphorylation of the fusion receptor. Dose-dependent effects of insulin, insulin-like growth factor 1, and epidermal growth factor on BRET signal are in agreement with known pharmacological properties of these ligands. Moreover, antibodies that activate or inhibit the autophosphorylation of the receptor have similar effects on BRET signal. This method allows for rapid analysis of the effects of agonists on insulin receptor activity and could therefore be used in a high-throughput screening test for discovery of molecules with insulin-like properties.     

Prediction of steady state bioequivalence relationships using single dose data II-nonlinear kinetics

Two nonlinear pharmacokinetic models were simulated to investigate the relationship between single and multiple dose bioequivalency parameters for drugs such as phenytoin and propranolol which exhibit either saturable elimination kinetics or a capacity limited first pass effect. Mean Tmax, Cmax and area under the plasma-concentration time curve values from 0 to infinity (AUC 0-infinity) were compared after a single and multiple dose(s) of a test or reference drug. The aim was to determine if there were systematic changes in the limits of the single dose confidence interval at steady state that would limit the usefulness of confidence intervals following a single dose in accurately predicting bioavailability following multiple dosing. The 90 per cent confidence interval expressed as a percentage of the reference mean for Tmax, Cmax, and AUC 0-infinity showed model dependent changes from single to multiple dosing in response to the level of data error and changes in absorption. Changes in clearance also seemed to have a marked effect on the observed limits of the single and multiple dose confidence intervals especially for Cmax which showed a characteristic change in the intervals as a function of the clearance ratio. The model used to describe phenytoin had confidence intervals for Cmax and AUC 0-infinity from single to multiple dosing that were similar to that seen for the experimental data. However, the model predictions for Tmax confidence intervals following single and multiple dosing was at variance with the experimental data for formulations A and B.     

Prediction of unbound serum valproic acid concentration by using in vivo binding parameters.

In a previous study, we determined the in vivo binding parameters of valproic acid (VPA) to serum proteins in seven healthy young adults at steady state by using the Scatchard equation. To evaluate the ability of the Scatchard binding equation to predict steady-state unbound serum VPA concentrations (Cf), 39 adult patients receiving VPA monotherapy and ranging in age from 16 to 68 years were studied. The correlation between predicted and observed Cf was high (r = 0.865). Mean prediction error, mean absolute error (MAE), and root mean squared error (RMSE) were calculated, and served as a measure of prediction bias and precision. The MAE and RMSE were low (MAE = 12.9 mumol/L, RMSE = 17.7 mumol/L). It is feasible to use the Scatchard binding equation to predict Cf in patients receiving VPA monotherapy.     

Monitoring the activation state of insulin/insulin-like growth factor-1 hybrid receptors using bioluminescence resonance energy transfer

In cells expressing both the insulin receptor isoform A (IRA) and the insulin-like growth factor-1 receptor (IGF1R), the presence of hybrid receptors, made up of an alphabeta-IRA chain associated with an alphabeta-IGF1R chain, has been demonstrated. These heterodimers are found in normal cells, and they also seem to play crucial roles in a number of cancers. However, they remain difficult to study, due to the concomitant presence of IRA and IGF1R homodimers. Using bioluminescence resonance energy transfer (BRET), we have developed assays to specifically monitor the activation state of IRA/IGF1R hybrids, both in vitro and in living cells. The first assay allowed the study of ligand-induced conformational changes within hybrid receptors purified from cells cotransfected with one type of receptor fused to Renilla reniformis luciferase (Rluc), and the other type of receptor fused to yellow fluorescent protein (YFP). In these conditions, only hybrid receptors were BRET-competent. In the second assay, the activation state of IRA/IGF1R hybrids was monitored in real time, in living cells, by cotransfection of kinase-dead versions of IRA-Rluc or IGF1R-Rluc, wild-type untagged IRA or IGF1R, and a YFP-tagged soluble version of the substrate-trapping mutant of protein tyrosine phosphatase 1B (YFP-PTP1B-D181A-Cter). In hybrid receptors, trans-phosphorylation of the kinase-dead alphabeta-Rluc moiety by the wild-type alphabeta moiety induced the recruitment of YFP-PTP1B-D181A-Cter, resulting in a hybrid-specific ligand-induced BRET signal. Therefore, both methods allow monitoring of the activity of IRA/IGF1R hybrid receptor and could be used to detect molecules of therapeutic interest for the treatment of cancer.     

Prediction of the pharmacokinetic parameters of reduced- dolasetron in man using in vitro-in vivo and interspecies allometric scaling

1. Dolasetron (Anzemet®) is apotent andselective 5-HT₃ receptor antagonist which is rapidly and extensively reduced to yield its major pharmacologically active metabolite, reduced dolasetron (RD). RD is further metabolized by CYP450 enzymes as well as undergoing renal excretion. As both in vitro and in vivo data on RD were available from animals andman, two approaches to predict the human pharmacokinetic parameters ofRD were assessed. 2. First, in vitro studies, using liver microsomes from animal species and man, were undertaken to measure V_max and K_m and to assess the intrinsic clearance (CL_int). With appropriate liver weight and liver bloodflow scaling factorsthe predicted in vivo metabolic clearance (CL_{m_pred}) was calculated. Human CL_{m_pred} was underestimated by a factor of 5 when it was calculated using the above scaling factors. As, in a prospective study, the observed human in vivo metabolic clearance (CL_{m_obs})is unknown, CL_{m_pred} was substituted into the least-squares correlation equation obtained from a plot of CL_{m_pred} against CL_{m_obs}, using animal data. The estimate of human CL_{m_obs} was improved as it was only underestimated by a factor of 1.5. 3. Second, allometric scaling of in vivo animal pharmacokinetic data, using body weight, was performed topredict pharmacokinetic parameters in man. Good predictions of human pharmacokinetic parameters of RD were obtained for plasma clearance (1.7 l/min predicted versus 1.6 l/min observed), half-life (6.0?h predicted versus 5.6?h observed), and volume of distribution (860.9 l predicted versus 770.4 l observed). 4. The integration of in vitro metabolic data from microsomes gave similar results to conventional allometric scaling, whereas the normalization of clearance by brain weight resulted in an approximately three-fold underestimation of human clearance. 5. For RD, a drug that is eliminated by both renal and metabolic clearance, retrospective conventional allometric scaling allowed accurate prediction of pharmacokinetic parameters in man, whereas in vitro-in vivo scaling resulted in an underestimation of in vivo CL_m. Although these results are somewhat at variance, ideally both scaling methods should be applied to improve the prediction of human pharmacokinetic parameters.     

人体关键药代动力学参数预测方法

分布容积、清除率、半衰期和生物利用度是重要的药物代谢动力学参数,决定着药物在体内的暴露程度与暴露时间,在新药开发过程中尽早预测人体内这些参数对选择与优化潜在新药有重要价值。本文综述了采用临床前药代动力学实验数据、体外吸收与代谢数据、化合物理化性质、计算机模拟等多种方法预测人体内关键药代动力学参数的研究及其进展。     

Prediction of sun protection factors and UVA parameters of sunscreens by using a calibrated step film model

At the stage of screening of new sun protection formulations, quick and inexpensive methods for estimation of the ultraviolet (UV) screening performance are highly desirable. It has been shown recently that apart from measurements of sun protection factors in vitro, calculations using a calibrated step film model are also a possibility. In the present investigation, further evidence for the usefulness of the step film model in terms of prediction of the sun protection factor is shown. In addition, it is demonstrated that parameters, which characterize the protection in the UVA range such as the UVA/UVB ratio and the critical wavelength can be calculated in good accordance with experimental data. Although with less accuracy, the estimation of UVA protection factors is also possible, if the photodegradation some filters undergo upon irradiation is taken into consideration.     

麻黄素相关药物的应用现状

麻黄素是 2 0世纪初叶我国的化学、药理学家从中药麻黄中提取出的生物碱 ,1 92 4年被引入西方医学应用的第一个拟似交感神经药 ,因此备受国际医药学界的重视 ,至今仍被各国的药典所收载。世界主要制药国已有麻黄素的专利制剂 1 1种 ,含麻黄素的复方制剂商品名 3 75种 ,但是由于相关药物的出现和取代 ,市场上已停用或少用的专利制剂5种、复方制剂 1 45种 [1 ,2 ]。我国是麻黄素主要生产国 ,年产量 40 0 t左右 ,大部分出口销售于国际市场。半个世纪以来 ,山西大同又是我国麻黄素的主产地 ,其应用状况应予关注。由于麻黄素和伪麻黄素容易被犯罪…     

Prediction of clinical pharmacokinetic parameters of linezolid using animal data by allometric scaling: applicability for the development of novel oxazolidinones

1.?Allometric scaling has previously been used as an effective tool for the prediction of human pharmacokinetic data. The pharmacokinetic data for linezolid, a novel oxazolidinone to treat Gram-positive pathogens, in mice, rats and dogs were subjected to simple allometric scaling. Generated allometric equations for parameters such as clearance (CL), volume of distribution (V_ss) and elimination rate constant (K₁₀) were used to predict human pharmacokinetic parameters including elimination half-lives. In addition, the human plasma concentration–time curve was simulated using a one-compartmental model.

2.?Application of simple allometry (Y?=?aW^b) for animal parameters such as CL, V_ss, and K₁₀ showed excellent allometric fit (r?≥?0.98). The allometric equations for CL, V_ss, and K₁₀ were??0.5465W^0.6595,??0.1369W^0.9246, and??0.4117W^–0.3139, respectively. The confidence in predictability of CL and V_ss parameters was particularly high since the allometric exponents of CL and V_ss almost approached the suggested values of 0.75 and 1.00, respectively.

3.?Animal pharmacokinetic parameters generated in the present authors’?laboratories for linezolid were in close agreement with reported literature values. The predicted human values for CL (4.68?l?h^?1), V_ss (37.07 litres), and K₁₀ (0.10?h^?1) were within the range observed for linezolid in the literature (CL?=?4?10.5 l?h^?1; V_ss?=?21???53 litres; K₁₀?=?0.09???0.3?h^?1). The human half-life (t_1/2) predicted using allometry (6.9?h) was similar to reported values in humans of 5?h. In summary, the retrospective analysis for linezolid suggests that allometric scaling can be used as a prospective tool for predicting human pharmacokinetic parameters of novel oxazolidinones.     

Prediction of clinical pharmacokinetic parameters of linezolid using animal data by allometric scaling: applicability for the development of novel oxazolidinones

1. Allometric scaling has previously been used as an effective tool for the prediction of human pharmacokinetic data. The pharmacokinetic data for linezolid, a novel oxazolidinone to treat Gram-positive pathogens, in mice, rats and dogs were subjected to simple allometric scaling. Generated allometric equations for parameters such as clearance (CL), volume of distribution (Vss) and elimination rate constant (K10) were used to predict human pharmacokinetic parameters including elimination half-lives. In addition, the human plasma concentration-time curve was simulated using a one-compartmental model. 2. Application of simple allometry (Y = aWb) for animal parameters such as CL, Vss, and K10 showed excellent allometric fit (r > or = 0.98). The allometric equations for CL, Vss, and K10 were -0.5465W(0.6595), -0.1369W(0.9246), and -0.4117W(-0.3139), respectively. The confidence in predictability of CL and Vss parameters was particularly high since the allometric exponents of CL and Vss almost approached the suggested values of 0.75 and 1.00, respectively. 3. Animal pharmacokinetic parameters generated in the present authors' laboratories for linezolid were in close agreement with reported literature values. The predicted human values for CL (4.68 l h(-1)), Vss (37.07 litres), and K10 (0.10 h(-1)) were within the range observed for linezolid in the literature (CL = 4-10.5 l h(-1); Vss = 21-53 litres; K10 = 0.09-0.3 h(-1)). The human half-life (t(1/2)) predicted using allometry (6.9 h) was similar to reported values in humans of 5 h. In summary, the retrospective analysis for linezolid suggests that allometric scaling can be used as a prospective tool for predicting human pharmacokinetic parameters of novel oxazolidinones.     

Clinical efficacy of metformin against insulin resistance parameters: sinking the iceberg

It has been increasingly recognised in recent years that type 2 (non-insulin-dependent) diabetes is part of a cluster of cardiovascular risk factors known as the metabolic syndrome, but also endorsed with such names as the deadly quartet, syndrome X and the insulin resistance syndrome. Atherosclerosis is the most common complication of type 2 diabetes among Europeans, and coronary artery, cerebrovascular and peripheral vascular disease are 2 to 5 times more common in people with this condition than in those without diabetes. These observations indicate that the treatment of type 2 diabetes requires agents that do more than simply lower blood glucose levels, and a therapy with both antihyperglycaemic effects and beneficial effects on dyslipidaemia, hypertension, obesity, hyperinsulinaemia and insulin resistance is likely to be most useful. In this respect, metformin has an important and established role: this drug has been shown to lower blood glucose and triglyceride levels, and to assist with weight reduction and to reduce hyperinsulinaemia and insulin resistance. Studies in the Israeli sand rat, Psammomys obesus, have indicated hyperinsulinaemia/insulin resistance to be the initial and underlying metabolic disorder in obesity and type 2 diabetes. Thus, the well established effect of metformin in reducing insulin resistance makes this drug an excellent candidate for the prevention of progression of impaired glucose tolerance to type 2 diabetes, and for the reduction of mortality associated with cardiovascular disease.     

Prediction of steady state plasma and saliva levels of desmethylimipramine using a single dose,single time point procedure

In normal volunteer study (20 subjects) where each ingested 75 mg desmethylimipramine (DMI), blood and saliva samples were collected at 1, 2, 3, 4, 5, 7, 12, 24, and 32 h post dose. Each subject then was given DMI 25 mg b.i.d. for 15 days. Blood and saliva samples were collected on days 3, 4, 12, 13, 14, and 15. All samples were analyzed for total DMI content. Strong correlations were found between the blood samples collected 12, 24, and 32 h post dose (r=0.93, 0.96, 0.95) and saliva samples collected 24 and 32 h post single dose (r=0.91, 0.84) and the subjects' respective steady states. Although the correlation between blood and saliva levels was weaker (r=0.7) because of considerable interindividual variation in the saliva/plasma DMI ratio (16-fold variation), this ratio in individual subjects was stable. These data suggest that, as has been shown for other psychotropic drugs, single blood measures at 24 h post ingestion of 75 mg DMI can be used to predict optimal dosage in individual patients. Acceptable predictions of steady state plasma levels were obtained when this technique was applied to patient data available in the literature. It is also suggested that if the saliva/plasma ratio is established for each individual patient, their drug level monitoring may be possible using this noninvasive approach.     

Exploring the metabolic state of microorganisms using metabolomics

Microorganisms depend on their ability to modulate their metabolic composition according to specific circumstances, such as different phases of the growth cycle and circadian rhythms, fluctuations in environmental conditions, as well as experimental perturbations. A thorough understanding of these metabolic adaptations requires the ability to comprehensively identify and quantify the metabolome of bacterial cells in different states. In this review, we present an overview of the diverse metabolomics approaches recently adopted to explore the metabolism of a wide variety of microorganisms. Focusing on a selection of illustrative case studies, we assess the different experimental designs used and explore the major achievements and remaining challenges in the field. We conclude by discussing the important complementary information provided by computational methods such as genome-scale metabolic modeling, which enable an integrated analysis of metabolic state changes in the context of overall cellular physiology.     

Prediction and evaluation of fetal toxicity induced by NSAIDs using transplacental kinetic parameters obtained from human placental perfusion studies

AIMThe use of nonsteroidal anti-inflammatory drugs (NSAIDs) in full-term pregnant women leads to fetal or neonatal toxicity, such as constriction of the ductus arteriosus (DA) and persistent pulmonary hypertension in the newborn. The aim of this study was to predict quantitatively the fetal toxicity of three NSAIDs (antipyrine, salicylic acid and diclofenac) using the transplacental pharmacokinetic parameters obtained from our previous placental perfusion studies.METHODSHuman fetal plasma concentration profile after oral administration of each NSAID to the mother was estimated using the transplacental pharmacokinetic parameters and pharmacokinetic parameters in adult women. The fetal plasma concentration–response relationship for the three NSAIDs was estimated by pharmacokinetic/pharmacodynamic analysis of the results of previous studies investigating the effects of NSAIDs on the ratio of inner diameter of the DA to that of the pulmonary artery (DA/PA) in rats and the plasma concentration profiles of NSAIDs in pregnant rats.RESULTSThe risk of constriction of the DA was well predicted by the model. Mean DA/PA ratio after oral administration of diclofenac to the mother was estimated to be 39.0%, whereas both of the corresponding values after oral administration of antipyrine and salicylic acid were estimated to be 5.9%. These results suggest that the fetal risk of diclofenac is higher than those of salicylic acid and antipyrine.CONCLUSIONSThis study presents a novel approach to predict quantitatively the fetal risk of NSAIDs administered to the mother. Human placental perfusion study and pharmacokinetic/pharmacodynamic analysis may provide basic data for predicting human fetal toxicity of drugs.     

Protection of insulin from enzymatic degradation by its association to liposomes

The degradative action of digestive enzymes (pepsin, α-chymotrypsin and trypsin) was investigated against insulin associated or entrapped in positively charged liposomes. Under the chosen experimental conditions, both insulin preparations were protected against enzymatic degradation. Furthermore, the nature of the interaction between external phospholipidic bilayer and insulin was found to result from an ionic association. Finally, the protective role of liposomes appeared highly dependent upon the molar proportion phospholipid/hormone.     

Prediction of the human oral bioavailability by using in vitro and in silico drug related parameters in a physiologically based absorption model

Estimates of the human oral absolute bioavailability were made by using a physiological-based pharmacokinetic model of absorption and the drug solubility at the gastrointestinal pH range 1.5-7.5, the apparent permeability (P(app)) in Caco-2 cells and the intrinsic clearance (Cl(int)) in human hepatocytes suspensions as major drug related parameters. The predictive ability of this approach was tested in 164 drugs divided in four levels of input data: (i) in vitro data for both P(app) and Cl(int); (ii) in vitro data for Cl(int) only; (iii) in vitro data for P(app) only and (iv) in silico data for both P(app) and Cl(int). In all scenarios, solubility was estimated in silico. Excellent predictive abilities were observed when in vitro data for both P(app) and Cl(int) were used, with 84% of drugs with oral bioavailability predictions within a±20% interval of the correct value. This predictive ability is reduced with the introduction of the in silico estimated parameters, particularly when Cl(int) is used. Performance of the model using only in silico data provided 53% of drugs with bioavailability predictions within a±20% acceptance interval. However, 74% of drugs in the same scenario resulted in bioavailability predictions within a±35% interval, which indicates that a qualitative prediction of the absolute bioavailability is still possible. This approach is a valuable way to estimate a fundamental pharmacokinetic parameter, using data typically collected in the drug discovery and early development phases, providing also mechanistic information of the limiting bioavailability steps of the drug.