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In the modern world, technology is at its peak. Different avenues inprogramming and technology have been explored for data analysis, automation,and robotics. Machine learning is key to optimize data analysis, make accuratepredictions, and hasten/improve existing functions. Thus, presently, the fieldof machine learning in artificial intelligence is being developed and its usesin varying fields are being explored. One field in which its uses stand out isthat of microbial biosynthesis. In this paper, a comprehensive overview of thediffering machine learning programs used in biosynthesis is provided, alongsidebrief descriptions of the fields of machine learning and microbial biosynthesisseparately. This information includes past trends, modern developments, futureimprovements, explanations of processes, and current problems they face. Thus,this paper's main contribution is to distill developments in, and provide aholistic explanation of, 2 key fields and their applicability to improveindustry/research. It also highlights challenges and research directions,acting to instigate more research and development in the growing fields.Finally, the paper aims to act as a reference for academics performingresearch, industry professionals improving their processes, and studentslooking to understand the concept of machine learning in biosynthesis.

Applications of machine Learning to improve the efficiency and range of microbial biosynthesis: a review of state-of-art techniques