Steve Soper,
Foundation Distinguished Professor, Director, Center of BioModular Multi-Scale System for Precision Medicine,
The University of Kansas
Prof. Soper is currently a Foundation Distinguished Professor in Chemistry and Mechanical Engineering at the University of Kansas, Lawrence. Prof. Soper also holds an appointment at Ulsan National Institute of Science and Technology in Ulsan, South Korea, where he is a World Class University Professor. He is also serving as a Science Advisor for a number of major worldwide companies. Prof. Soper is currently on the Editorial Board for Scientific Reports and Journal of Micro- and Nanosystems.
As a result of his efforts, Prof. Soper has secured extramural funding totaling >$103M and has published over 265 peer-reviewed manuscripts (h index = 71) and is the author of 20 patents. He is also the founder of a startup company, BioFluidica, which is marketing devices for the isolation and enumeration of circulating tumor cells. His list of awards includes Chemical Instrumentation by the American Chemical Society, the Benedetti-Pichler Award for Microchemistry, Fellow of the AAAS, Fellow of Applied Spectroscopy, Fellow of the Royal Society of Chemistry, R&D 100 Award, Distinguished Masters Award at LSU and Outstanding Scientist/Engineer in the state of Louisiana in 2001. Finally, Prof. Soper has granted 60 PhDs and 6 MS degrees to students under his mentorship. He currently heads a group of 20 researchers.
Determining Critical Quality Attributes (CQAs) of Adeno-Associated Virus Gene Therapies using Resistive Pulse Sensing
Wednesday, 3 April 2024 at 17:00
Add to Calendar ▼2024-04-03 17:00:002024-04-03 18:00:00Europe/LondonDetermining Critical Quality Attributes (CQAs) of Adeno-Associated Virus Gene Therapies using Resistive Pulse SensingExtracellular Vesicles (EVs) and Nanoparticles 2024: Diagnostics, Delivery, Therapeutics in Miami, FloridaMiami, FloridaSELECTBIOenquiries@selectbiosciences.com
Adeno-associated virus (AAV) vectors have been used to successfully introduce therapeutic gene fragments (i.e., gene therapy) into host cells and thus offer a significant tool for combating diseases that are unaffected by conventional drug therapy. This has led to a significant number of new clinical trials involving AAVs. However, broad application of AAV gene therapy across potential disease targets is hampered by a lack in definition of critical quality attributes (CQAs), analytics to measure CQAs, development of universal customizable vector cassettes, and affordable manufacturing methods. Presently, one of the most significant production and quality control issues facing AAV manufacturing is the presence of non-transducing viral particles (including empty particles) in the final vector preparation. Not only does this introduce errors and inconsistencies in the identification of actual titer delivered to the patient, but it also results in decreased infectivity of the dose due to increased host immune response to the defective virions. The issue of empty capsids is considered one of the top five major concerns in the production of AAVs today. The establishment of quantifiable traits at various points in the production process along with suitable analytical techniques are needed. Techniques to determine the full-to-empty capsid ratio include transmission electron microscopy (TEM) and analytical ultracentrifugation. Unfortunately, these techniques are fraught with challenges. There have also been a number of different chromatographic techniques to determine the full-to-empty ratio, but are challenged by inter-laboratory variability. All of the aforementioned techniques are batch-type processes and thus, cannot do real-time reporting to optimize the manufacturing process in-line. In this presentation, we will discuss the use of synthetic nanopore-based sensors capable of detecting and characterizing AAVs. Specifically, we will discuss the use of nanopore technology to detect capsids, characterize capsids as either full or empty, and to analyze capsids to determine if they contain full-length or foreshortened gene fragments. The sensors consist of dual in-plane nanopores that flank either end of a nano-column from which one can deduce the electrophoretic mobility of the target nanoparticle. We will show that empty and full capsids possess different mobilities and with the use of resistive pulse sensing (RPS) and machine learning, we can classify the particles as either full or empty quantitatively in near real-time.
