Increasing Biomanufacturing Yield with Bleed–Feed: Optimal Policies and Insights

Problem definition : Bleed–feed is a novel technology that allows biomanufacturers to skip intermediary bioreactor setups. However, the specific time at which bleed–feed is performed is critical for success. The process is stringently regulated, and its implementation involves unique tradeoffs in operational decision making. Our analysis formalizes the operational challenges related to bleed–feed decisions, and our results inform biomanufacturers and policymakers on the potential impact of this technology on current practice. Academic/practical relevance : Operations management (OM) methodologies have not yet been widely adopted in the biomanufacturing industry. This research presents one of the first attempts to demonstrate how OM can complement biomanufacturing to improve operational decisions. We present a practically relevant problem and a rigorous solution approach that is relevant to both OM and biomanufacturing. Methodology : We develop a finite-horizon, discrete-time Markov decision processes model and analyze the structural characteristics of optimal bleed–feed policies. Moreover, we characterize the behavior of the value function as a function of regulatory restrictions. As a salient feature, the MDP model captures both the biological dynamics of fermentation and the operational tradeoffs in biomanufacturing. Results : We show that optimal bleed–feed policies have a three-way control-limit structure under mild conditions that were validated with industry data. Moreover, our analysis reveals that the marginal benefits of bleed–feed diminish as additional bleed–feeds are performed. As a practically relevant benchmark, we consider a risk-averse heuristic and identify sufficient conditions for its optimality. Managerial implications : Our analysis (supported with an industry case study) shows that bleed–feed implementation can provide benefits. Real-world implementation at MSD resulted in an 82.5% improvement in the batch yield per setup (using one bleed–feed). We find that low-risk fermentation systems benefit the most from bleed–feed implementation. We also find that the performance gap between optimal policies and the risk-averse heuristic is higher when the failure risks or the critical biomass levels are lower.