Thursday, October 19, 2017
12:00 PM EDT

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Proteins and antibodies comprise an extremely diverse class of biological macromolecules and they are often unstable when not in their native environments, which can vary considerably. If specific buffer conditions are not maintained they may lose activity, aggregate or fall into proteolysis. For this reason, it is essential to nominate specific buffer formulations that increase the physical and chemical stability of each target protein.

Reproducibility of scientific studies has been repeatedly put into question. International companies, such as Amgen and Bayer HealthCare, were not able to reproduce most of the examined landmark papers in their field. These findings called to question the quality of the research reagents being used and its impact on the accuracy of the experimental data. Of the research expenses presumably wasted in the USA, by far the largest fraction of about 36% is assigned to biological reagents, which amounts to losses of about 10-50 billion US$ annually, depending on the reporting source. In many negative examples discussed, biological reagents (antibodies and proteins) played a significant role. Discussions concerning quality control measures for biologics were sparked at least 20 years ago and a series of recent articles focusing on the quality control (QC) of biologics shows the persistent interest and relevance of this problem. However, efforts to improve this situation have not yet led to any fundamental advancements.

“Due to the difficulties and expense of QC’ing a product at each step of the manufacturing and experimental pipeline the impact of product stability on data accuracy has primarily been ignored”, SA. Clark 2016.

In this webinar, you will learn more about:

  1. Importance of quality control for biological reagents (with current market short comings) and implementation of new big data compatible standard 1mg:1hr.:1000datapoints
    1. QC is not just important at the product development and packaging stage but at every step of the downstream R&D process.
    2. As you add new components/chemicals to the experimental solution how do you monitor target stability?
    3. We have a full biochemical profile so you know the impact of DMSO, etc. ahead of time
  2. New tool MYXR 1.0 for the rapid, accurate and cost-effective QC and biochemical profiling of biopharmaceutical reagents in near real-time. Description of online data analytics (supported by our proprietary biological A.I.) for client data evaluation to:
    1. Guide product manufacturing
    2. Protein characterization or identification*
    3. Data driven R&D decisions (construct nomination → structure based drug design)
    4. Guiding benchtop experimentation efforts
      1. Protocol development
      2. Providing real-time product biochemical profiles
      3. Mixing proteins and buffer compromise
      4. Immunoengineering
  1. Implementation of big data analytics and the proteome
    1. Reclassification of protein families according to biochemical properties not genetic lineage
    2. Drug design from a proteocentric point of view
    3. Rational for precipitation / aggregation / degradation
    4. Role of glycosylation in protein stability and protein-protein interactions
    5. Understandingprotein promiscuity and side effects

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