A method for detection of anti-drug antibodies to a biotherapeutic (CSL112) with endogenous counterpart (apolipoprotein A-I) using a novel sample pre-treatment electrochemiluminescence assay

Abstract

BackgroundThere are numerous challenges encountered during clinical testing for an immunogenic response to a plasma-derived therapeutic. Distinguishing between antibodies that recognize endogenous versus therapeutic protein can be particularly difficult. This study focused on CSL112 (human plasma-derived apolipoprotein A-I; apoA-I), which is in clinical development for reducing the risk of recurrent major adverse cardiovascular events following acute myocardial infarction. AimTo develop and validate a high-throughput, highly sensitive and specific assay to detect antibodies to CSL112 that can be used for immunogenicity assessment in large clinical studies. ResultsWe developed a clinical anti-drug antibody (ADA) assay utilizing an immunoglobulin purification step that improved specificity and drug tolerance, demonstrating that measurement of pre-existing or treatment emergent ADAs was highly dependent on assay format. The Sample Pre-treatment Electrochemiluminescence (ECL; SPECL) assay incorporates a protein A extraction of serum samples before a bridging assay is performed on an ECL platform. The assay is qualitative, sensitive (lower limit of quantification <39 ng/mL) and has a drug tolerance of 0.5 mg/mL in line with U.S. Food and Drug Administration requirements for clinical immunogenicity assays for therapeutic proteins. Importantly, the SPECL assay demonstrated the absence of antibodies to both apoA-I and CSL112 both prior to drug exposure and after repeated dosing across multiple trials (n = 970 subjects). ConclusionThe SPECL method has been validated and applied to support the CSL112 preclinical and clinical development program and has broader application to similar protein therapeutics. Attributes of the methodology include high drug tolerance, high sensitivity, selectivity, and precision. This format is amenable to automation providing the high throughput and reduced variability required to support large scale clinical studies that span extended time periods.