Recovery bioanalytical

Recently, the miniaturization procedures of bioanalytical studies have become an important research area with particular focus on modem concept of lab-on-a-chip technology [48], with a reduction in manufacturing costs, easy transport, minimal space and minimal maintenance requirements (and costs) in the laboratory and in the fields, even if this progress require a long design and implementation time, non-stable robotic operation, and limited error recovery abilities. 

Low permeability can itself be the cause of apparent discrepancies between biochemical and cell-based assays and may or may not have physiological relevance. Independent of the solubility limitation mentioned above, the selection of an appropriate loading concentration in cell-based permeability assays impacts on the assay outcome and depends on what information one wants to extract from the measurement loading at high concentration (i.e., 100 pM) will essentially cancel the effect of active transports unless passive diffusion is low. When high loading concentrations are used, poor recovery and bioanalytics are usually not an issue. 

Loading at low concentration (i.e., 5)iM) will increase the sensitivity to active transports but make recovery and bioanalytical aspects more challenging. 

J. Wieling, H. Dijkstra, C.K. Mensink, J.H.G. Jonkman, P.M.J. Coenegracht, C.A.A. Duineveld and D.A. Doombos, Chemometrics in Bioanalytical Sample Preparation a Fractionated Combined Mixture and Factorial Design for the Modelling of the Recovery of Five Tricyclic Amines from Plasma after Liquid-Liquid Extraction, Journal of Chromatography, 629(2) (1993) 181-199. 

The fundamental parameters for bioanalytical validations include accuracy, precision, selectivity, sensitivity, reproducibility, stability of the drug in the matrix under study storage conditions, range, recovery, and response function (see Section 8.2.1). These parameters are also applicable to microbiological and ligand-binding assays. However, these assays possess some unique characteristics that should be considered during method validation, such as selectivity and quantification issues. 

From a practical point of view, internal standard in a LC-MS/MS assay serves three distinct purposes in the analytical process. The first purpose is to compensate extraction recovery inconsistencies. The second purpose is to compensate injection volume variation. The third purpose is to compensate possible matrix effects during the MS ionization process as has already been discussed in detail above. In 2009, Tan A. et al. reported 12 case studies from incurred sample analyses using a wide variety of bioanalytical methods for the investigation of inconsistent internal standard response [23], For similar reasons, it has now become common for laboratory SOPs to contain specific requirements for the acceptable internal standard response of each individual sample within a sample batch during regulated bioanalysis. These requirements (e.g., 60-140 %, 50-150 % of the average internal standard area for all samples in the batch) ensure that the behavior of the internal standard, regardless of how well it tracks the analyte, is under control, and is consistent in all samples. 

The assay has been validated and the results of validation demonstrate that the standard curve is linear over the concentration range of 100-2000 ng/mL. The assay is reproducible and accurate, with recovery of the analyte and internal standard in the range of 80-90 %. The analysis requires 0.5 mL of plasma and has a limit of quantification of 70 ng/mL. The stability of plasma samples stored at -20 °C has been demonstrated for up to 12 weeks. Autoinjector stability has been demonstrated for over 13 h and freeze-thaw stability has been demonstrated for 3 freeze-thaw cycles. The procedure has a sample throughput of at least 30 specimens per day. The assay meets the guidelines for bioanalytical methods validation for human studies (Shah et al. 1991). 

The optimization and validation of immunoassays for immunogenicity (ADA) testing has been described in detail in several publications [9,14,33,34]. In this section, we will describe the evaluation of relevant performance characteristics (validation parameters) that require the most effort. Some of these are different from the validation of traditional bioanalytical pharmacokinetic (PK) methods for macromolecules [35 37]. Precision, specificity, robustness, and ruggedness are determined similarly between ADA and PK methods. However, recovery/accuracy, sensitivity, stability, linearity, system suitability controls, and selectivity are treated differently between these two types of assays. 

For certain types of regulatory or forensic assays there may be specific requirements for the absolute recovery required for the assay, e.g. 70-120%, but the bioanalyt-ical guidelines do not impose any specific requirements for recovery other than that it should be shown to be consistent and precise to ensure method reproducibility. Experiments designed to investigate and optimize the absolute recovery in conjunction with the cleanliness of the extract should be apartof any method development activities, and then tested during validation with the objectives described above. 

The most recent bioanalytical Workshop Report (Viswanathan 2007) devotes considerable space to this topic and some recommendations not discussed previously (Section 9.4.7b) are included below. There should be some assessment of both reproducibility and accuracy of the reported concentration. Sufficient data should be generated to demonstrate that the current matrix (i.e. the incurred sample matrix) produces results similar to those previously validated. It is recognized that accuracy of the result generated from incurred samples can be more difficult to assess. It requires evaluation of any additional factors besides reproducibility upon storage, which could perturb the reported concentration. These could include metabolites converted to parent during sample preparation or LC-MS/MS analysis, matrix effects from high concentrations of metabolites, or variable recovery between analyte and internal standard (Viswanathan 2007). Most of these phenomena are those described previously (Jemal 2002) and discussed in Section 9.4.7b. 

Due to the high cost of cell culture, Caco-2 assays are usually used as a follow-up to PAMPA in ADME screening [78], and as a result, the sample burden for bioanalysis is not as heavy as for some first-hne assays, such as metabolic stability. There have been a number of reports in the literature that use automated optimization and single LC-MS/MS for sample analysis for Caco-2 assay support [46,79-81]. Nevertheless, Caco-2 samples pose a unique bioanalytical challenge. Unlike plasma or microsomal samples rich in proteins that help solubilize compounds and prevent adsorptive loss, Caco-2 samples are essentially aqueous buffer samples with very little protein. As a result, compounds with low solubility and/ or adsorption problems tend to exhibit poor recoveries in the assay due to precipitation and adsorptive losses [82,83]. An effective solution to this problem is the use of organic solvent to catch compounds immediately after incubation, but prior to analysis, in order to maintain solubility and prevent adsorptive loss to container surfaces. Another approach involves the addition of some protein such as bovine serum albumin (BSA) to the assay buffer system, thus reducing compound loss/ precipitation and improving recoveries [84]. 

Flavonoids can be determined quantitatively by direct (in glycoside or conjugated form) or indirect (after hydrolysis) analysis. However, sample preparation (e.g., particle size) and solvents used in extraction steps can significantly affect the results [99]. Method development for quantitation is often validated in terms of selectivity, accuracy, precision, recovery, calibration curve, and reproducibility. Biological sample methods have to comply with the Food and Drug Administration (FDA) guidelines for validation of bioanalytical method [100]. 

---