Deployment of metabolic heat rate based soft sensor for estimation and control of specific growth rate in glycoengineered Pichia pastoris for human interferon alpha 2b production

Abstract

Lack of appropriate process models, reliable online sensors, and process variability in bioprocess systems are poising challenges in real-time monitoring and control of critical process parameters (CPPs). This present investigation deals with the development of a non-invasive soft sensor by utilizing metabolic heat rate as input signal for online estimation of specific growth rate (μest) during the induction phase of glycoengineered Pichia pastoris for human interferon-alpha 2b (huIFNα2b) production. Feedforward strategy employing a predetermined exponential feeding of methanol during the induction phase was dealt at defined setpoint values (μSP). Standard PID controller with predetermined gain values regulated methanol feeding in accordance with the deviation from the μSP value. An adaptive PID (gain scheduling) significantly minimized the deviation of μ from its μSP value, reduced the amplitude of oscillation and achieved long-term controller stability. Robust control of methanol feeding by adaptive PID resulted in a 1.5 and 2.2-fold increase in productivity of huIFNα2b compared to standard PID and feedforward controls respectively. Moreover, adaptive PID control facilitated narrow range control of μ for longer durations (> 20 h) with a low average tracking error (< 6%) enumerating its scope of application in therapeutic protein production in near future.