Supporting the Development of Scalable Manufacturing Processes for Complex Synthetics through Automation and Machine Learning

As complex synthetic molecules such as peptides and oligonucleotides gain momentum for their precision and therapeutic potential, R&D teams face unique challenges in effectively scaling development and manufacturing processes. The use of machine learning and artificial intelligence can help accelerate scale-up with data-driven decision-making and optimization tools.

Join our own Adrian Amador, Director of Chemistry at Snapdragon Chemistry, a Cambrex company, on April 29th at 10:00 AM EDT for this live webinar in which he will discuss real examples of how automation and advanced optimization methodologies can be integrated into chemical process development workflows to support scalability, reproducibility and efficiency.

Cases to be Discussed:

  • Use of a Bayesian optimizer for multi-objective optimization of a solid-phase oligonucleotide synthesis process
  • Development of a fully automated liquid phase peptide synthesis platform to accelerate the development of scalable peptide manufacturing processes