Abstract：
Since the discovery of antibiotics, penicillin has remained the top choice in clinical medicine. With continuous advancements in biotechnology, penicillin production has become cost-effective and efficient. Genetic engineering techniques have been employed to enhance biosynthetic pathways, leading to the production of new penicillin derivatives with improved properties and increased efficacy against antibiotic-resistant pathogens. Advances in bioreactor design, media formulation, and process optimization have contributed to higher yields, reduced production costs, and increased penicillin accessibility. While biotechnological advances have clearly benefited the global production of this life-saving drug, they have also created challenges in terms of waste management. Production fermentation broths from industries contain residual antibiotics, by-products, and other contaminants that pose direct environmental threats, while increased global consumption intensifies the risk of antimicrobial resistance in both the environment and living organisms. The current geographical and spatial distribution of antibiotic and penicillin consumption dramatically reveals a worldwide threat. These challenges are being addressed through the development of novel waste management techniques. Efforts are aimed at both upstream and downstream processing of antibiotic and penicillin production to minimize costs and improve yield efficiency while lowering the overall environmental impact. Yield optimization using artificial intelligence (AI), along with biological and chemical treatment of waste, is also being explored to reduce adverse impacts. The implementation of strict regulatory frameworks and guidelines is also essential to ensure proper management and disposal of penicillin production waste. This review is novel because it explores the key remaining challenges in antibiotic development, the scope of machine learning tools such as Quantitative Structure-Activity Relationship (QSAR) in modern biotechnology-driven production, improved waste management for antibiotics, discovering alternative path to reducing antibiotic use in agriculture through alternative meat production, addressing current practices, and offering effective recommendations.
摘要：
自从发现抗生素以来，青霉素仍然是临床医学的首选。随着生物技术的不断进步,青霉素生产已经变得具有成本效益和效率。基因工程技术已被用于增强生物合成途径，导致生产新的青霉素衍生物，这些衍生物具有改善的特性并增强了对抗生素抗性病原体的功效。生物反应器设计的进展，培养基配方，和工艺优化有助于提高产量，降低了生产成本，增加了青霉素的可及性。虽然生物技术的进步显然有利于这种救命药物的全球生产，他们也在废物管理方面提出了挑战。来自工业的生产发酵液含有残留的抗生素，副产品,和其他对环境造成直接威胁的污染物，虽然全球消费量的增加加剧了环境和生物体中抗菌素耐药性的风险。抗生素和青霉素消费的当前地理和空间分布显着揭示了全球威胁。这些挑战正在通过开发新的废物管理技术来解决。努力的目标是在抗生素和青霉素生产的上游和下游加工，以最大程度地降低成本并提高产量效率，同时降低总体环境影响。使用人工智能(AI)进行产量优化，随着废物的生物和化学处理，也在探索以减少不利影响。实施严格的监管框架和准则对于确保青霉素生产废物的适当管理和处置也至关重要。这篇综述是新颖的，因为它探讨了抗生素开发中的关键挑战，现代生物技术驱动的生产中的定量结构-活动关系（QSAR）等机器学习工具的范围，改善抗生素的废物管理，通过替代肉类生产发现减少农业中抗生素使用的替代途径，解决当前的做法，提供有效的建议。
