Daniel Benjamin | Chief Scientific Officer
Metalytics
Use of stable isotopes in metabolic flux analysis (MFA) studies and how the MFA results are benefiting the biomanufacturing industry
Abstract: Metabolic flux analysis (MFA) is the science of using stable isotopes to elucidate both the route of metabolism as well as the rate of metabolism. In this presentation we will demonstrate how stable isotopes are used in MFA studies with a description of the data that is collected, processed, and converted into actionable information for the biomanufacturing industry. We will present three different case studies demonstrating what knowledge was gained and used to improve productivity. We will also highlight the ability to use this stable isotope-derived MFA data to train a machine learning model that enables the rapid and accurate prediction of metabolic fluxes with limited experimental data.
- Stable isotopes are crucial for calculating the precise rate and route of metabolite flow within cells using a technology called metabolic flux analysis (MFA)
- Metalytics has successfully used this stable isotope-enabled MFA data to improve the productivity of biomanufacturing
- Metalytics is currently using this MFA data to train a digital twin that can rapidly and accurately predict metabolic flux with limited experimental data
Moderated by
Roswell Shelhamer | Cambridge Isotope Laboratories, Inc.
Business Development Manager – Metabolic, MRI/MRS, Clinical
Speaker Biography
Daniel is the Chief Scientific Officer at Metalytics. Daniel received his PhD in metabolic biochemistry from UC Berkeley and was a post-doctoral fellow at Stanford University. As a graduate student, Daniel helped elucidate metabolic pathways that are critical for promoting the aggressive features of breast and ovarian cancer, and he helped to develop small-molecule inhibitors that specifically target these pathways. As a postdoc, Daniel studied the changes in the metabolism of stem cells during the aging process, in order to develop metabolism-based therapeutics to enhance stem cell function in older patients.