As gene therapy programs grow in number and scale, manufacturing processes must keep pace with demand by providing the speed, throughput, and automation necessary for advancement. Droplet digital PCR is the current gold standard for quantifying rAAV genomes but suffers from a long turn-around time and low throughput. The QIAcuity dPCR system provides a fully integrated solution that reduces hands-on time while improving throughput and turn-around time.

A comparison of in-process samples to the current gold standard system shows that:

  1. QIAcuity dPCR is as accurate as the current gold standard with lower cost and much higher throughput
  2. Sample preparation and upstream optimization are key for accurate in-process rAAV genome titer quantitation
About the speaker
A'Drian Pineda, Sr. Business Development Manager, digital PCR
QIAGEN
A'Drian Pineda is the Sr. Business Development Manager for digital PCR (dPCR) at QIAGEN, supporting the North American BioPharma market. Before joining QIAGEN, he spent 6 years as a Field Application Scientist and Manager specializing in support for BioPharma and ddPCR customers in R&D, AD and GMP manufacturing. Previous roles include work with viral vectored gene therapies, vaccines, cell line development and process development, most recently at Novartis and GSK. A’Drian earned his M.Sc. from Vanderbilt University in Nashville, TN.
Hui-wen Liu, Sr. Scientist, Analytical development, Gene therapy Franchise
Resilience
Hui-wen Liu is a senior scientist in analytical development within Gene therapy Franchise at Resilience. She received her Ph.D. in Molecular Biology at Ohio State University, where she studied transcription control during cell cycle progression. Her postdoc training at Vollum Institute focused on NAD+ metabolism in neuropathy. Her current work is to develop assays that characterize the rAAV payload and investigate new technologies to improve assay performance.
Date of recording:Thursday, 17 March 2022
Duration:60 minutes
Categories
Webinar
Pharma / Biopharma
Genetherapy
Digital PCR
dPCR