Biological fluids are commonly analyzed in clinical and forensic studies for drug concentration measurements. Conventional quantification procedures are always associated with lengthy sample pretreatment steps to eliminate the interfering compounds that potentially exist in complex biological matrices. The objective of this study was to address these problems employing solid-phase microextraction (SPME) technique. Antibodies (Abs) were employed to serve as an extremely specific extraction phase for direct extraction of analytes from untreated biological matrices based on their exquisite selectivity for antigens (Ags).
Much of the research was focused on selecting the most appropriate antibody (Ab) for a particular application based on evaluation of characteristics of various types of Abs obtained from four suppliers. Abs’ binding characteristics were evaluated before and after immobilization in terms of affinity, valence, homogeneity, capacity and cross-reactivity for three benzodiazepines. The performance of immunoaffinity probes of the same type provided by different suppliers was found to be comparable. Finally, the probes’ utility for extraction of benzodiazepines from plasma samples was evaluated.
The limit of detection of the method developed in this work was 0.01 ng/mL with upper limits of quantification of 0.5 ng/mL in buffer and 2 ng/mL in plasma. The method’s precision was 12% for extraction from buffer and less than 10% for extraction from plasma. With limits of detection similar to the current state-of-the-art methods available for quantification of drugs in biological matrices, the method presented in this thesis was found advantageous compared to other available methods due to its simplified sample preparation procedure.
Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OWTU.10012/3444 |
Date | January 2007 |
Creators | Safari Sanjani, Saharnaz Jay |
Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
Language | English |
Detected Language | English |
Type | Thesis or Dissertation |
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