Use of Raman Spectroscopy in the Evaluation of Materials used in In vitro Diagnostic Devices

In-vitro diagnostics tests are an important part of patient care, influencing greater than 70% of the decision made on the care pathway to follow. The ability to consistently produce product with equivalent performance is key to supporting healthcare professionals in this decision making. A large proportion of in-vitro diagnostics are immunoassay, relying on the highly specific interaction of antibodies with the target molecule. These tests are commonly contain complex mixes of biological components, including the antibody of choice often modified by addition of a marker compound. Many of the antibody conjugates, serum proteins and animal sera are not well characterised in terms of the properties required for optimum performance within the immunoassay system and so a change in material lot represents a significant risk to the performance of the reagent. Each new lot of the biological materials for these systems therefore has to be assessed as to its performance to ensure the product consistency and quality is maintained, with significant time and resources investigated in these evaluations. Development of improved material testing methodology will result in improved effectiveness of material selection, increased productivity through reduced scrap and rework activities and increased customer satisfaction.
Through a previous PhD studentship, the application of Raman spectroscopy has been demonstrated to:
1. distinguish different grades of BSA and define the structural differences between these grades
2. identify the presence of structural changes in protein structure following exposure to different conditions of pH, temperature and mixing
3. in combination with FTIR, characterise the structural changes occurring following conjugation of BSA to a small molecule and the further minute changes that occur as the conjugated protein ages

This project seeks to expand on the work described above to further the develop the methodology and machine learning analytics for use as a quality control and/or troubleshooting tool within immunoassay manufacturing. The ultimate aim is to be able to use analytical tools such as Raman within the quality control process for new materials, to reduce the time and resources taken to identify and qualify suitable new lots. The project scope will include:
expanding the range of proteins characterised, the use of machine learning analytics to determine which specific characteristic are linked to positive or negative performance characteristics in immunoassays and examination of proteins within complex reagent mixing as a potential troubleshooting tool for unexpected reagent performance challenges