Abstract
The intersection of biomedicine and technology has yielded transformative advancements, and Generative Artificial Intelligence (GenAI) started to stand at the forefront of this synergy. In the field of life sciences, GenAI is emerging as a catalyst, accelerating drug discovery by swiftly generating and predicting novel molecules. This expedites the identification of potential drug candidates, significantly reducing time and costs compared to traditional methods. Beyond drug discovery, GenAI contributes to protein folding predictions, genomics research, and biomarker identification, enhancing our understanding of diseases and health conditions, fostering the development of personalized medicine. In agribusiness, GenAI proves instrumental in optimizing crop breeding and improving agricultural productivity. It can generate new crop varieties with desired traits by analyzing vast datasets comprising genomic and ecological information, addressing challenges such as disease resistance, improved yield, and enhanced nutritional content. Moreover, GenAI transcends traditional applications and extends its influence on synthetic biology, contributing to the design of novel enzymes and pathways. This opens avenues for bio-based manufacturing, renewable energy production, and environmental remediation. By harnessing the power of GenAI, the synergies between biomedicine and technology are harnessed to accelerate innovation, improve efficiency, decrease costs, and address critical challenges. Conversely, the ethical considerations surrounding GenAI, especially Large Language Model (LLM) utilization in life sciences and agribusiness, such as data privacy, algorithmic bias, and the equitable distribution of benefits, must be addressed to ensure responsible and fair implementation. This review article discusses the multifaceted impact of GenAI in a new era of advancements in life sciences and agribusiness.
