Development and validation of an efficient and highly sensitive enzyme-linked immunosorbent assay for alemtuzumab quantification in human serum and plasma

Abstract

Background:Alemtuzumab is a humanized monoclonal antibody that targets the CD52 glycoprotein expressed on most lymphocytes, subsequently inducing complement-mediated and antibody-mediated cytotoxicity. Owing to its ability to induce profound immune depletion, alemtuzumab is frequently used in patients before allogeneic hematopoietic stem cell transplantation to prevent graft rejection and acute graft-versus-host disease. In this clinical context, a stable immunoassay with high sensitivity and specificity to determine alemtuzumab levels is essential for performing pharmacokinetic and pharmacodynamic analyses; however, the available methods have several limitations. Here, we report the successful development and validation of an efficient and highly sensitive enzyme-linked immunosorbent assay technique based on commercially available reagents to quantify alemtuzumab in human serum or plasma.Methods:This enzyme-linked immunosorbent assay technique was developed and validated in accordance with the European Medicines Agency guidelines on bioanalytical method validation.Results:The assay sensitivity (lower limit of quantification) is 0.5 ng center dot mL(-1), and the dynamic range is 0.78-25 ng center dot mL(-1). To accommodate quantification of peak concentration and concentrations below the lympholytic level (<0.1 mcg center dot mL(-1)), patients' serum samples were prediluted 20-400 times according to the expected alemtuzumab concentration. The overall within-run accuracy was between 96% and 105%, whereas overall within-run precision (coefficient of variation) was between 3% and 9%. The between-run assessment provided an overall accuracy between 86% and 95% and an overall coefficient of variation between 5% and 14%.Conclusions:The developed assay provides accurate insight into alemtuzumab exposure and its effects on the clinical response to treatment, which is key to optimizing treatment strategies.