Introduction

The iBioG-Med is a culture media optimization design platform developed by BioEngine independently through statistics, data mining and machine learning for the development of customized culture media formulations. The iBioG-Med platform allows rapid development of customized media for target cells, meeting customer expectations for cells/products as well as meeting the need for risk control. The platform can also avoid the drawbacks of long experimental cycles, empiricism in concentration selection, information omission and waste in traditional development methods for culture media formulations.

iBioG-Med contains three sub-models, I-SCR, I-FIT, and I-GEN. Variable selection model (I-SCR) can effectively describe the key components of the medium and establish the relationship between the medium components and technical objectives (e.g. antibody yield, antibody key quality attributes, etc.), which can be used to guide the subsequent optimization process and quality control of the medium production. Compared to traditional fitting models, the prediction model based on data distribution (I-FIT) has a higher expressivity and more accurate simulation and prediction of culture medium performance. The Learning model based on genetic algorithm (I-GEN) can be used to calculate formulation performance, greatly reducing workload and speeding up media development.

The iBioG-Med platform has successfully helped more than a dozen customers develop and optimize their culture media formulations. Some projects have been successfully marketed or entered clinical phases II and III. In addition, the iBioG-Med platform is used for the development of the DrivingM® standard catalog culture medium. iBioG-Med can iterate and upgrade the standard catalog media for each scenario to better meet the needs of our customers.