Cyprotex is a preclinical discovery/development contract research organisation measuring and analysing the ADME and pharmacokinetic properties of potential new drugs. It is a specialist provider of in vitro ADME screening as well as in silico methods used in the prediction of in vivo pharmacokinetics. Wikipedia.
Krstajic D.,Research Center for Cheminformatics |
Krstajic D.,University of Belgrade |
Krstajic D.,Persona Inc. |
Buturovic L.J.,Persona Inc. |
And 2 more authors.
Journal of Cheminformatics
Background: We address the problem of selecting and assessing classification and regression models using cross-validation. Current state-of-the-art methods can yield models with high variance, rendering them unsuitable for a number of practical applications including QSAR. In this paper we describe and evaluate best practices which improve reliability and increase confidence in selected models. A key operational component of the proposed methods is cloud computing which enables routine use of previously infeasible approaches. Methods. We describe in detail an algorithm for repeated grid-search V-fold cross-validation for parameter tuning in classification and regression, and we define a repeated nested cross-validation algorithm for model assessment. As regards variable selection and parameter tuning we define two algorithms (repeated grid-search cross-validation and double cross-validation), and provide arguments for using the repeated grid-search in the general case. Results: We show results of our algorithms on seven QSAR datasets. The variation of the prediction performance, which is the result of choosing different splits of the dataset in V-fold cross-validation, needs to be taken into account when selecting and assessing classification and regression models. Conclusions: We demonstrate the importance of repeating cross-validation when selecting an optimal model, as well as the importance of repeating nested cross-validation when assessing a prediction error. © 2014 Krstajic et al.; licensee Chemistry Central Ltd. Source
Clark G.T.,Quotient Bioresearch Ltd. |
Clark G.T.,Cyprotex |
Russell P.J.,Colworth Science Park |
Westwood S.,Quotient Bioresearch Ltd.
After obtaining his PhD in Bioorganic Chemistry from the University of Southampton in 1999, Graeme T Clark has spent the past 13 years working in the field of analytical chemistry. He has held posts of increasing responsibility in academia, biotech, large pharma and contract research where he has both implemented novel technologies and managed functions as diverse as lipidomics, small-molecule bioanalysis (Discovery to Phase IIb clinical trials), biotransformation and LC-MS/MS-based large-molecule analysis. He has published over 18 peer-reviewed articles on subjects covering lipid profiling and biomarkers, microsampling, dried blood spot bioanalysis and novel analytical solutions to peptide bioanalysis. Graeme currently leads up the Bioanalysis and Metabolite Identification group at Cyprotex focussing on in vitro and in vivo analysis. A previously validated LC-MS/MS method for the analysis of H.g.-12 (a steroid glycoside found in Hoodia gordonii) in patients failed when clinical plasma samples from the target population were collected. The failure was identified as a result of much higher lipid concentrations (lipemia) than previously observed, and through the course of the method redevelopment it was further clarified as excessive neutral lipids. The sample preparation element was focused on as not only did the assay fail acceptance criteria, but attempted analysis of the clinical samples resulted in routine system overpressures and physical failure of the LC-MS/MS. The original method was based on liquid-liquid extraction with tertiary-butyl methyl ether and here we present the systematic assessment of SPE, supported liquid extraction as well as pretreatment and multistage sample preparation approaches to solve the bioanalytical challenge. © 2012 Future Science Ltd. Source
Floettmann J.E.,Astrazeneca |
Buckett L.K.,Astrazeneca |
Turnbull A.V.,Astrazeneca |
Smith T.,Cyprotex |
And 4 more authors.
Acyl-coenzyme A: cholesterol O-Acyltransferase (ACAT) and Acyl-coenzyme A: diacylglycerol O-acyltransferase (DGAT) enzymes play important roles in synthesizing neutral lipids, and inhibitors of these enzymes have been investigated as potential treatments for diabetes and other metabolic diseases. Administration of a Acyl-coenzyme A: diacylglycerol O-acyltransferase 1 (DGAT1) inhibitor with very limited cellular selectivity over ACAT resulted in significant adrenocortical degenerative changes in dogs. These changes included macrosteatotic vacuolation associated with adrenocyte cell death in the zonae glomerulosa and fasciculata and minimal to substantial mixed inflammatory cell infiltration and were similar to those described previously for some ACAT inhibitors in dogs. In the mouse, similar but only transient adrenocortical degenerative changes were seen as well as a distinctive nondegenerative reduction in cortical fine vacuolation. In the marmoset, only the distinctive nondegenerative reduction in cortical fine vacuolation was observed, suggesting that the dog, followed by the mouse, is the most sensitive species for cortical degeneration. Biochemical analysis of adrenal cholesterol and cholesteryl ester indicated that the distinctive reduction in cortical fine vacuolation correlated with a significant reduction in cholesteryl ester in the mouse and marmoset, whereas no significant reduction in cholestryl ester, but an increase in free cholesterol was observed in dogs. Administration of a DGAT1 inhibitor with markedly improved selectivity over ACAT to the marmoset and the mouse resulted in no adrenal pathology at exposures sufficient to cause substantial DGAT1 but not ACAT inhibition, thereby implicating ACAT rather than DGAT1 inhibition as the probable cause of the observed adrenal changes. Recognizing that the distinctive nondegenerative reduction in cortical fine vacuolation in the mouse could be used as a histopathological biomarker for an in vivo model of the more severe changes observed in dogs, the mouse has subsequently been used as a model to select DGAT1 inhibitors free of adrenocortical toxicity. Copyright © 2013 by The Author(s). Source
Cyprotex | Date: 2014-09-10
Computer software platforms for supporting workflow integration and database management of laboratory robotics analytics and algorithmic data processing in the provision of ADME Tox experimental services.
Cyprotex | Date: 2011-11-10
Assays and reagents for use in genetic research; Assays for research purposes; Enzymes for scientific and research purposes.