PROJECT SUMMARY/ABSTRACT
The goal of this project is to develop a multiplexed rapid point-of-care diagnostic (“disposable device”) to
detect antibodies (“Abs”) against therapeutic monoclonal antibodies (“mAbs”) approved for the treatment of
Rheumatoid Arthritis (RA). Patients often develop anti-mAb Abs, which may abrogate the therapeutic mAb
efficacy and/or cause adverse events. We have devised a unique use of chimeric proteins as capture reagents
in multiplexed disposable devices, which eliminate nonspecific signal during anti-mAb Ab screening, and
allows direct comparison of their immunogenicity and risk assessment. The scientific approach is described in
granted U.S. patents assigned to ConquerAb Inc. The disposable device allows Ab isotype detection in less
than 15 minutes from one drop of blood, and can be used before the next drug infusion (trough mAb
concentration) for detection of free anti-mAb Abs, suggesting selection of dose or an alternative treatment. In
addition, this disposable device will harmonize Ab detection, allowing integration of patient data generated at
different point-of-care facilities (big data). Existing assays for anti-mAb detection, such as enzyme-linked
immunosorbent assay (ELISA) require preparation of serum or plasma, sample handling, multiple steps,
trained operators, may take days to provide results, and are more prone to errors. In addition, some of those
assays may use an acid dissociation step, which unfortunately may denature Abs. Another problem is that the
time of sample collection can vary, resulting in samples that have different concentrations of mAbs in complex
with anti-mAb Abs, leading to inconsistent results that cannot be validly integrated. For this Phase 1 we
propose development of a multiplexed diagnostic for detection of anti-mAb Abs with a proprietary technology.
The test strip will also be incorporated into a patented self-contained disposable device, and tested in a clinical
study with anonymized RA patients. This is an innovative strategy that can have a major impact in detecting,
comparing and mitigating unwanted immunogenicity of protein-based therapies, and also in the utilization of
big data for precision medicine.