Tuesday, 6 October // 16:00 UK time // 11:00 US Eastern
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In this webinar, we demonstrate how the AI-driven design of experiments (DoE) platform Alchemite™ was used at Tosoh Bioscience to identify purification conditions that maximize both product purity and recovery for an important class of therapeutics – oligonucleotides. We will demonstrate how AI-guided experimentation reduced the number of laboratory experiments.
Therapeutic oligonucleotides, including antisense oligonucleotides (ASOs) and aptamers, are short, synthetic strands of DNA or RNA used for the treatment of cancer, genetic disorders, and rare diseases. Ensuring the quality and safety of these molecules requires the efficient removal of closely related impurities. Oligonucleotide structures can be complex, making development of a robust purification process challenging and resource-intensive.
Anion exchange chromatography is frequently used as an initial purification step for oligonucleotides. However, identifying optimal process conditions, including resin selection, buffer composition, pH, elution salt type, flow rate, and temperature, often requires extensive experimental screening and significant material consumption. This webinar will show how the development team at Tosoh Bioscience applied machine learning to accelerate identification of the best purification conditions for single stranded modified and unmodified 20-mer oligonucleotides.
Presenters:
Dr Elena Kumm, Application Scientist, Tosoh Bioscience
Dr Charlie Phillips, Principal Solution Scientist, Intellegens
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