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High-Performance Liquid Chromatography
Published in Joseph Chamberlain, The Analysis of Drugs in Biological Fluids, 2018
One great advantage of micelle chromatography is that the system is capable of solubilizing proteins and hence is capable of accepting direct injections of plasma or serum without precipitating the proteins and causing clogging or deterioration of the column. This is obviously a great advantage in bioanalysis. As well as making a preprecipitation step unnecessary, it is also claimed that the micelles compete with drug for binding sites on the protein, thus releasing the free drug for chromatography.687 A number of applications of such direct analysis have been described (Table 7.2). The use of micelles has found particular application in capillary electrophoresis (see discussion later).
Metabolomic Techniques to Discover Food Biomarkers
Published in Dale A. Schoeller, Margriet S. Westerterp-Plantenga, Advances in the Assessment of Dietary Intake, 2017
Pekka Keski-Rahkonen, Joseph A. Rothwell, Augustin Scalbert
In quantitative MS-based bioanalysis, addition of internal standards is usually performed during the sample preparation. Quantification is then based on the response ratio of the analyte to the internal standard, calculated as a function of the concentration of the analyte. This is an efficient way of compensating for multiple sources of variability, and can cover the entire analytical process from sample extraction to detection. However, due to physicochemical differences between the analytes, any single compound cannot be used as a universal internal standard, and a common practice is to incorporate a stable isotope labeled analogue of each analyte whenever possible. In untargeted metabolomics, the use of individual internal standards is not possible, but it may be feasible to employ carefully selected internal standards to assist in normalizing the data for variability in injection volumes or other factors that are not compound specific.
Use of Classical Pharmacokinetic Evaluations in Drug Development and Safety Assessment
Published in John C. Lipscomb, Edward V. Ohanian, Toxicokinetics and Risk Assessment, 2016
Suggested matrices for these experiments are rat plasma from initial oral dosing PK studies, and rat and human liver microsomal samples that initially define the metabolic stability of the compounds. Bioanalysis should be initially performed in the microsomal samples since this matrix is simpler compared to plasma (i.e., less endogenous compounds to provide background). Detection of simple mass changes (e.g., +16 m/z for oxidation and/or −14 m/z for demethylation) in single quad mode and at least initially, the a priori prediction should guide this analysis. If structure of metabolites from these predictions can be easily elucidated (i.e., a distinct N-demethylation or O-demethylation or oxidation), structural elucidation should proceed. Once metabolites are defined in the microsomal incubation, bioanalysis of the rat plasma may occur and should focus on metabolites identified in the microsomal samples. If possible, MRM methods can be developed from the microsomal bioanalysis and used to analyze the rat plasma to ensure selectivity. Select limited plasma samples (i.e., only two samples may be needed—one close to the Cmax/Tmax of the parent and one half-life from this Cmax/Tmax) for analysis.
Bioanalytical strategies in drug discovery and development
Published in Drug Metabolism Reviews, 2021
Aarzoo Thakur, Zhiyuan Tan, Tsubasa Kameyama, Eman El-Khateeb, Shakti Nagpal, Stephanie Malone, Rohitash Jamwal, Chukwunonso K. Nwabufo
The determination of the identity and concentration of novel drugs and/or their metabolites in biological fluids is an important aspect of pharmacokinetic, pharmacodynamic, and toxicokinetic studies that inform the safety and efficacy profile of investigational drugs which is essential for determining their clinical translation (Russell et al. 2020, 2021; Nwabufo 2021). Bioanalysis is a branch of analytical chemistry that deals with the quantitative measurement of biomarkers, chemical entities, biologics, and/or their metabolites in biological matrices like blood, urine, serum, cerebrospinal fluids (CSF), and tissues, etc. Due to its important role in drug development, it is essential that an appropriate bioanalytical method is developed and validated to ensure the integrity of generated data.
Introduction to the mini special issue on next generation drug discovery and development: rethinking translational pharmacology for accelerated drug development
Published in Drug Metabolism Reviews, 2021
Several investigational drugs fail clinical development due to inadequate translation of preclinical efficacy and safety profile, ultimately leading to an increased health care burden and failed drug cost. To change this current narrative, the next generation drug discovery and development landscape will require an accurate predictive potential for non-clinical surrogates and early implementation of such predictive studies in the development process. I developed this mini special issue to evaluate recent advancements and opportunities for four main subthemes that support drug discovery and development including prediction of metabolic pathways, translational pharmacokinetic and pharmacodynamic studies, pharmacogenomics, and trends in bioanalysis. Scientific papers in these areas were covered by investigators from the International Society for the Study of Xenobiotics New Investigator Group (ISSXNIG) and other investigators.
Hematocrit effect on dried blood spots in adults: a computational study and theoretical considerations
Published in Scandinavian Journal of Clinical and Laboratory Investigation, 2019
Chrysa Daousani, Vangelis Karalis, Anđelija Malenović, Yannis Dotsikas
Indeed, the results of the present analysis prove that the preparation of calibration standards and QC samples at a Ht value based on demographic data is fully rationalized and will lead to a tolerated level of % relative error attributed to Ht effect, without need for predetermination of the range of sample Ht levels before analysis of DBS samples; a task that would require extra blood analysis. An upper level of 3% for relative error could be a ‘tolerable contribution’ of Ht-effect to % total analytical error in most of the cases and, therefore, well-acknowledged control of Ht effect can be achieved, as well as the acceptance criteria (±15%) for accuracy, Ht-allocated portion of % error being well defined. In this way, acknowledged regulatory criteria for bioanalysis can be targeted, leading to a wider utilization of DBS for drug development purposes, including application in human pharmacokinetic and clinical trials. It should be stated that the general 3% limit is suggested via theoretical calculations and may vary per analyte, as in real samples’ analysis many factors contribute to total error and in some cases, the Ht error may be deleted by an opposite error. That is why there may be cases in the literature in which samples with extreme Ht values have relative error values within the acceptance criteria (±15%) or in other cases to estimate a relative error value opposite than the expected one.