Abstract: Bio-analytical development plays a pivotal role in the biotech and pharmaceutical industries, serving as the backbone for drug discovery, development, and post-marketing surveillance. However, the development of analytical assays often faces challenges due to the increasing complexity of new treatments, the need for more sensitive and selective analytical methods, and the demand for broader analytes and faster turnaround times. To address these complexities, technologies used today such as Immunoassays and LC-MS, necessitate extensive development, validation, and sample-specific preparation due to their iterative, and sequential approach. In the face of these challenges, the pharmaceutical industry is constantly seeking innovative solutions and strategies to streamline the bio-analytical development process, improve the quality of data, and ultimately, expedite the delivery of safe and effective drugs and treatments to patients.
In this research, we present Quantum Electrochemical Spectroscopy (QES), an innovative approach that simplifies analytical testing and assay development. QES is a user-friendly technique requiring minimal sample volume (2-10µl), a single pipetting step, and no reagents or sample preparation. QES uses a small bench-top instrument to measure molecular vibrations, creating a unique digital fingerprint for each sample. This unbiased mathematical representation of the sample can be used to create classifiers and detect anomalies. I can also enables efficient detection, quantification, and classification of protein, metabolites, and small molecules, either a-priori or a-posteriori without the need to re-run the sample.
Previous studies have shown QES's ability to differentiate mass isotopes and structural isomers with high sensitivity and specificity (1). In this work, we demonstrate its capacity to identify, distinguish and quantify 2 very similar peptides. Long-acting (Toujeo/insulin glargine) and short-acting (Humalog/insulin lispro) differ by three amino acids at positions B28, B29, and B30 of the B-chain. QES can identify, quantify and differentiate mixtures of both molecules as low as fg/mL, showcasing the high sensitivity of the QES approach. We also transferred this AI-driven analytical method to detect and quantify other analytes in more complex matrices. For example low-abundance inflammatory proteins (e.g., IL-6) in blood-derived samples through the creation of standard curves.
The process of developing new assays for pharmaceutical development is typically labor-intensive and costly, driven by the extensive validation required by reagent-centric methods or the extensive sample preparation techniques. QES, however, eliminates the need for reagents or sample preparation and only requires one pipetting step, dramatically reducing the complexity and cost of method creation and validation. Despite its simplicity, QES does not compromise on breadth, sensitivity or specificity of analyte detection, as demonstrated by the very low amount of insulin molecules identified and quantified. We also demonstrate QES's ability to quantify larger proteins (IL-6) in a more complex blood-derived matrix.
(1) Gupta, Chaitanya, et al. The Journal of Physical Chemistry C 121.28 (2017): 15085-15105.