End of September, we attended the 7th edition of conference Bioproduction organized by MabDesign, in Lyon. The focus this year was on the development and bioproduction of therapeutics drugs such as mAbs. There were several presentations both from SME and large biopharma groups and a section in the program dedicated to innovation in bioproduction. It was interesting to meet the various attendees, who showed a growing interest in predictive tools for improving bioproduction.
As this was mentioned in various presentations, major improvements have been made in bioprocesses by embedding sensors in bioreactors to monitor Critical Process Parameters (CPP) including CO2, O2, pH, temperature… However, from all the data generated, one of the big challenges is to extract meaningful information to make rational decision.
This topic is actually echoing our involvement and current work within the CALIPSO project, led by Sanofi.
This CALIPSO project has been launched in 2021 and is funded by the French BPI. The goal is to develop a new generation of tools that will revolutionize R&D methodology and the management of industrial bioproduction processes. Ultimately, this will enable productivity gains up to a factor 10 and accelerate access to new treatments at an acceptable cost. Click here for more information!
In this context, Ypso-Facto brings its dual expertise on software development and predictive simulation. We are developing software tools to visualize and analyze data, extract meaningful information and contextualize data (so-called data science ontologies) to support rational decision- making.
Moreover, those tools will be designed to predict, thanks to a modeling approach, the behaviour of fermentation and cell culture bioreactors (Upstream process), as well as affinity chromatography, ion exchange or hydrophobic interaction purification systems (Downstream process). The modeling approaches that can be used are diverse: based on artificial intelligence, machine learning, statistics or mechanistic models… They all have pros and cons, depending on the context and what you want to achieve. If you are curious to learn more, we advise you to read the blog post: Modeling: Mechanistic or Statistical ?
At Ypso-Facto, our core expertise is mechanistic modeling, and this expertise is now accessible to you in Ypso-Ionic®, our software solution dedicated to chromatographic process, for both data management and predictive simulation.
If you were not at the conference and did not get a chance to have a demo, just contact us to arrange one – In the meantime, you can watch this 3 min video to learn more about Ypso-Ionic®.