Research Projects

Machine Learning-Driven Cell Culture Media

Accelerating media design with artificial intelligence

Ali Parsaee
Alberta Machine Intelligence Institute (AMII), Canada

media

Overview

Who: Ali Parsaee, Machine Learning Resident

When: 2024 – Present

Institutes: Alberta Machine Intelligence Institute (AMII), Canada

Supervisors: David Staszak, Lead Machine Learning Scientist at Amii

Summary

Ali is training a machine learning (ML) model to determine which culture media formulations will result in the best cell growth at the lowest cost. Using just a few laboratory experiments, Ali’s model will predict the best media formulations to try, reducing the number of cost- and time-intensive experiments scientists need to do in the laboratory. This ML-guided media design could reduce the cost of research and the cost of the final media!

Why This Matters

Designing cell culture media that helps cells grow quickly while reducing costs is a critical step to ensuring cultured meat can be a reality. However, a single media formulation includes dozens of ingredients – testing out different combinations of even just a few of these ingredients is a lot of experiments! Artificial intelligence, and in particular its subset machine learning, has great potential to accelerate research in media optimization by reducing the number of experiments scientists need to do in the laboratory.

Special thanks to Schmidt Futures for their generous support of Ali’s research. We rely on philanthropic partners to help projects like this one get off the ground. To learn more about how you can support New Harvest’s research program, please email brittany@new-harvest.org.