Advances in Ai-Driven Bioreactors for Optimized Polyhydroxybutyrate Production

Polyhydroxybutyrate (PHB) is a biodegradable biopolymer with promising applications as a sustainable alternative to petroleum-based plastics. However, PHB production is often limited by fluctuating bioreactor conditions, requiring intensive manual control to maintain optimal growth environments for microbial fermentation. This short communication presents a conceptual framework for an AI-driven bioreactor system designed to autonomously monitor and regulate key parameters such as pH, temperature, aeration, and nutrient concentrations. Integrating real-time biosensors with machine learning algorithms, the proposed system enables dynamic optimization of microbial growth and PHB synthesis through feedback-controlled adjustments. This approach addresses the limitations of traditional static bioreactor systems by providing consistent, high-yield outputs with reduced human intervention. While this is a design-based proposal without experimental validation, it is grounded in current trends in bioengineering and artificial intelligence integration. A schematic of the AI-regulated system is included to illustrate its functional architecture. This work contributes a novel direction for future research in smart bioprocessing and scalable PHB production, emphasizing the role of AI in sustainable biomanufacturing.