Biomedical subjects

S Ekins

Publications and source records attributed to S Ekins.

25 records · Page 2Linked to original sources

PubMed1996

Xenobiotic metabolism in rat, dog, and human precision-cut liver slices, freshly isolated hepatocytes, and vitrified precision-cut liver slices.

Human, rat, and dog phase I and phase II xenobiotic metabolism in precision-cut liver slices and freshly isolated hepatocytes was compared using a range of substrates. Carbamazepine (50 microM) and styrene (2 mM) were used as probes to study the maintenance of cytochrome P450 and epoxide hydrolase-mediated metabolism in male Sprague-Dawley rat, precision-cut liver slices and hepatocytes. Carbamazepine metabolism in both models resulted in the formation of the bioactive 10,11-epoxide (KM = 766 microM and Vmax = 2.5 pmol/min/mg protein in precision-cut slices). Epoxide formation was higher (2.4-fold) in hepatocytes than slices. Styrene was deactivated to styrene diol at a higher rate in hepatocytes (9.7-fold) than slices. The lower rate of metabolism in slices compared with hepatocytes confirms our previous observations using testosterone, 7-ethoxycoumarin, 1-chloro-2,4-dinitrobenzene and 2-(5'-chloro-2'-phosphoryloxyphenyl)-6-chloro-4-(3H)-quinazolinone in the rat. Testosterone 6 beta-hydroxylation in human liver slices was similar to cultured hepatocytes, but lower than in freshly isolated hepatocytes. 7-Ethoxycoumarin O-deethylation was higher in freshly isolated human hepatocytes, as was the ratio of glucuronide to 7-hydroxycoumarin. Testosterone hydroxylations, 7-ethoxycoumarin O-deethylation, and 1-chloro-2,4-dinitrobenzene conjugation were also lower in male beagle dog slices, compared with freshly isolated hepatocytes. Attempts at long-term preservation of dog liver slices using vitrification and storage for up to 9 days at -196 degrees C resulted in the retention of phase I and phase II metabolism, although conjugation was lower than in freshly prepared slices. Xenobiotic metabolism in short-term incubations is consistently lower in dog and rat precision-cut slices than in freshly isolated hepatocytes; whereas, in humans, this quantitative difference is partly hidden by the large interindividual variation.

Adolescent↗

PubMed1995

Quantitative differences in phase I and II metabolism between rat precision-cut liver slices and isolated hepatocytes.

Testosterone (250 microM), 7-ethoxycoumarin (25 microM), and 1-chloro-2,4-dinitrobenzene (CDNB, 50 microM) were used as substrates to compare phase I and II metabolism in rat precision-cut liver slices and rat hepatocytes. Overall clearance to metabolites was significantly greater in hepatocytes for testosterone (1.9- to 16.9-fold), 7-ethoxycoumarin (O-deethylation, 14.8-fold; glucuronidation, 3.1-fold), and CDNB (8.7-fold). The same metabolites for each of the substrates were detected in slices and hepatocytes. However, the ratio of sulfate to glucuronide conjugation was higher in slices, in line with the markedly slower rate of formation of 7-hydroxycoumarin. The slower rate of CDNB conjugation could not be explained by differences in the intracellular concentration of glutathione. These data suggest that metabolism in precision-cut slices is limited by diffusion of the substrate. This was illustrated by the use of 2-(5'-chloro-2'-phosphoryloxyphenyl)-6-chloro-4-(3H)-quinazolinone as a fluorescent probe to investigate diffusion in slices and hepatocytes.

Animals↗

PubMedDate not supplied

Progress in predicting human ADME parameters in silico.

Understanding the development of a scientific approach is a valuable exercise in gauging the potential directions the process could take in the future. The relatively short history of applying computational methods to absorption, distribution, metabolism and excretion (ADME) can be split into defined periods. The first began in the 1960s and continued through the 1970s with the work of Corwin Hansch et al. Their models utilized small sets of in vivo ADME data. The second era from the 1980s through 1990s witnessed the widespread incorporation of in vitro approaches as surrogates of in vivo ADME studies. These approaches fostered the initiation and increase in interpretable computational ADME models available in the literature. The third era is the present were there are many literature data sets derived from in vitro data for absorption, drug-drug interactions (DDI), drug transporters and efflux pumps [P-glycoprotein (P-gp), MRP], intrinsic clearance and brain penetration, which can theoretically be used to predict the situation in vivo in humans. Combinatorial synthesis, high throughput screening and computational approaches have emerged as a result of continual pressure on pharmaceutical companies to accelerate drug discovery while decreasing drug development costs. The goal has become to reduce the drop-out rate of drug candidates in the latter, most expensive stages of drug development. This is accomplished by increasing the failure rate of candidate compounds in the preclinical stages and increasing the speed of nomination of likely clinical candidates. The industry now understands the reasons for clinical failure other than efficacy are mainly related to pharmacokinetics and toxicity. The late 1990s saw significant company investment in ADME and drug safety departments to assess properties such as metabolic stability, cytochrome P-450 inhibition, absorption and genotoxicity earlier in the drug discovery paradigm. The next logical step in this process is the evaluation of higher throughput data to determine if computational (in silico) models can be constructed and validated from it. Such models would allow an exponential increase in the number of compounds screened virtually for ADME parameters. A number of researchers have started to utilize in silico, in vitro and in vivo approaches in parallel to address intestinal permeability and cytochrome P-450-mediated DDI. This review will assess how computational approaches for ADME parameters have evolved and how they are likely to progress.

Catalysis↗

PubMedDate not supplied

Present and future in vitro approaches for drug metabolism.

The 1980s through 1990s witnessed the widespread incorporation of in vitro absorption, distribution, metabolism, and excretion (ADME) approaches into drug development by drug companies. This has been exemplified by the integration of the basic science of cytochrome P450s (CYPs) into most drug metabolism departments so that information on the metabolic pathways of drugs and drug-drug interactions (DDIs) is no longer an academic exercise, but essential for regulatory submission. This has come about due to the application of a variety of new technologies and in vitro models. For example, subcellular fractions have been widely used in metabolism studies since the 1960s. The last two decades has seen the increased use of hepatocytes as the reproducibility of cell isolations improved. The 1990s saw the rejuvenation of liver slices (as new slicers were developed) and the utilization of cDNA expressed enzymes as these technologies matured. In addition, there has been considerable interest in extrapolating in vitro data to in vivo for parameters such as absorption, clearance and DDIs. The current philosophy of drug development is moving to a 'fail early--fail cheaply' paradigm. Therefore, in vitro ADME approaches are being applied to drug candidates earlier in development since they are essential for identifying compounds likely to present ADME challenges in the latter stages of drug development. These in vitro tools are also being used earlier in lead optimization biology, in parallel with approaches for optimizing target structure activity relationships, as well as identification of DDI and the involvement of metabolic pathways that demonstrate genetic polymorphisms. This would suggest that the line between discovery and development drug metabolism has blurred. In vitro approaches to ADME are increasingly being linked with high-throughput automation and analysis. Further, if we think of perhaps the fastest available way to screen for successful drugs with optimal ADME characteristics, then we arrive at predictive computational algorithms, which are only now being generated and validated in parallel with in vitro and in vivo methods. In addition, as we increase the number of ADME parameters determined early, the overall amount of data generated for both discovery and development will increase. This will present challenges for the efficient and fast interpretation of such data, as well as incorporation and communication to chemistry, biology, and clinical colleagues. This review will focus on and assess the nature of present in vitro metabolism approaches and indicate how they are likely to develop in the future.

Animals↗

PubMedDate not supplied

Application of in silico approaches to predicting drug--drug interactions.

In an environment driven to find the next blockbuster drug, failure years into a project should not be an option. Recent studies have shown that poor absorption, distribution, metabolism, and excretion (ADME), and the related properties of toxicity and pharmacokinetics are responsible for a large proportion of failures. One way to understand and potentially predict molecules likely to be successful in humans as drugs from an ADME point of view is to use simulations. Such simulations may include simple rule-based approaches, structure--activity relationships, three-dimensional quantitative structure--activity relationships (3D-QSAR), and pharmacophores. All of these represent useful tools in understanding metabolism by the cytochromes P450, predicting drug--drug interactions (DDIs), and other pharmacokinetic parameters. The present paper briefly reviews the application of some computational tools applied to predicting DDIs and will provide the reader with an idea of their utility.

Computer Simulation↗

PubMedDate not supplied

Three-dimensional quantitative structure-permeability relationship analysis for a series of inhibitors of rhinovirus replication.

Multiple three-dimensional quantitative structure-activity relationship (3D-QSAR) approaches were applied to predicting passive Caco-2 permeability for a series of 28 inhibitors of rhinovirus replication. Catalyst, genetic function approximation (GFA) with MS-WHIM descriptors, CoMFA, and VolSurf were all used for generating 3D-quantitative structure permeability relationships utilizing a training set of 19 molecules. Each of these approaches was then compared using a test set of nine molecules not present in the training set. Statistical parameters for the test set predictions (r(2) and leave-one-out q(2)) were used to compare the models. It was found that the Catalyst pharmacophore model was the most predictive (test set of predicted versus observed permeability, r(2) = 0.94). This model consisted of a hydrogen bond acceptor, hydrogen bond donor, and ring aromatic feature with a training set correlation of r(2) = 0.83. The CoMFA model consisted of three components with an r(2) value of 0.96 and produced good predictions for the test set (r(2) = 0.84). VolSurf resulted in an r(2) value of 0.76 and good predictions for the test set (r(2) = 0.83). Test set predictions with GFA/WHIM descriptors (r(2) = 0.46) were inferior when compared with the Catalyst, CoMFA, and VolSurf model predictions in this evaluation. In summary it would appear that the 3D techniques have considerable value in predicting passive permeability for a congeneric series of molecules, representing a valuable asset for drug discovery.

Antiviral Agents↗

PubMedDate not supplied

Algorithms for network analysis in systems-ADME/Tox using the MetaCore and MetaDrug platforms.

The authors have previously applied two integrated platforms, MetaCore and MetaDrug, for the assembly and analysis of human biological networks as a useful method for the integration and functional interpretation of high-throughput experimental data. The present study demonstrates in detail the specific algorithms that are used in both software platforms. Using a standard set of genes as input, namely CYP3A4 (an enzyme), PXR (a nuclear hormone receptor), MDR1 (a transporter) and hERG (an ion channel) related to the absorption, distribution, metabolism, excretion and toxicity (ADME/Tox) of xenobiotics, we have now generated networks with each algorithm. The relative advantages and disadvantages of these algorithms are explained using these examples as well as appropriate instances of utility to illustrate further the particular circumstances for their use. In addition, the benefits of the different network algorithms are identified when compared with algorithms available in other products, where this information is available.

Algorithms↗