Systematic Data and Knowledge Utilization to Speed up Bioprocess Design

Abstract Bioprocess design may require a substantial number of experiments to investigate the options for each bioprocess step. With the aim of reducing the amount of experimentation that is undertaken, we propose that data and knowledge about bioprocess design can be systematically exploited. We present a new general framework called the Bioprocess Data and Knowledge Framework (BDKF), for representing and reasoning with data and knowledge to produce the possible solutions for the bioprocess design. In the centrifugation case study, we established a database with 344 experiments described by 34 parameters, a knowledgebase with ontological, theoretical and empirical knowledge about centrifugation and showed how they were used for searching relevant process design information, predicting process performance and suggesting new experiments to be done. It demonstrates that BDKF is a promising approach for bioprocess data and knowledge utilization