Using Data Science to Maximise Protein Production banner

The escalating demand for recombinant proteins has spurred the exploration of data science along with engineering strategies for selecting and optimising host cell lines. This encompasses comprehensive verification and sequence analysis of the target gene or protein, along with processes such as codon optimisation, vector construction, and clone/host selection each requiring meticulous consideration of numerous variables. Cambridge Healthtech Institute’s Using Data Science to Maximise Protein Production explores high-throughput expression systems, elucidates data organisation methodologies, outlines data-driven design strategies, and with streamlining the number of experiments, saving time and costs. Learn from seasoned, savvy protein and data scientists who are fostering wider adoption of deep learning models for cell line engineering, protein expression, and production.

Recommended Short Course*
Monday, 4 November, 14:00 – 17:00
SC3: Tools for Cell Line Engineering and Development
*Separate registration required. See short courses page for details. All short courses take place in-person only.






For more details on the conference, please contact:

Mary Ann Brown
Executive Director, Conferences
Cambridge Healthtech Institute
Phone: (+1) 781-697-7687
Email: mabrown@healthtech.com

For sponsorship information, please contact:

Companies A-K
Jason Gerardi
Sr. Manager, Business Development
Cambridge Healthtech Institute
Phone: (+1) 781-972-5452
Email: jgerardi@healthtech.com

Companies L-Z
Ashley Parsons
Manager, Business Development
Cambridge Healthtech Institute
Phone: (+1) 781-972-1340
Email: ashleyparsons@healthtech.com