Discovering Changes in Cell Stability Using Process Mining: A Case Study

A bioprocess is a series of biological, chemical, and physical operations used to produce a product using living cells or their components. Bioprocesses are often used for the production of monoclonal antibodies (mAbs). The first step of the mAb production bioprocess is to take a vial containing a small amount of the selected cell line and grow those cells until they are of sufficient quantity. This step is known as the seed train in bioprocess development. During the seed train phase, it is essential to monitor the stability of the cells and their growth due to challenges such as variations in cell behaviour, batch-to-batch differences, and potential changes in cultivation conditions. In this paper, we present a case study where process mining is used to analyse the stability of cell lines during the seed train phase at a large pharmaceutical company in Australia. In order to do so, first it was necessary to transform the collected seed train data into an event log. Next, process models were discovered for high- and low-growth seed trains. We then derived insights into the performance of the seed train growth rate whereby characteristics of cell cultures in early stages can be associated with growth rate performance in later stages. Finally, we showed how the discovered models can be used to predict the growth performance of new seed trains.