Biofilm-mediated infections; novel therapeutic approaches and harnessing artificial intelligence for early detection and treatment of biofilm-associated infections

A biofilm is a group of bacteria that have self-produced a matrix and are grouped together in a dense population. By resisting the host's immune system's phagocytosis process and attacking with anti-microbial chemicals such as reactive oxygen and nitrogen species, a biofilm enables pathogenic bacteria to evade elimination. One of the major problems in managing chronic injuries is treating wounds colonized by biofilms. These days, a major issue is the biofilms, which exacerbate infection pathogenesis and severity. Numerous investigators have already discovered cutting-edge methods for biofilm manipulation. Using phytochemicals is a practical tactic to control and prevent the production of biofilms. Numerous studies conducted in the last few years have demonstrated the antibacterial and antibiofilm qualities of nanoparticles (NPs) against bacteria, fungi, and protozoa. Because hydrogel has antibiofilm properties, it has been employed extensively in wound care recently. It may be removed with ease and without causing trauma. Today, artificial intelligence (AI) is being used to improve these tactics by providing customized treatment alternatives and predictive analytics. Artificial intelligence (AI) algorithms have the capability to examine extensive datasets and detect trends in biofilm formation and resistance mechanisms. This can aid in the creation of more potent antimicrobial drugs. AI models analyze complex datasets, predict biofilm formation, and guide the design of personalized treatment strategies by identifying resistance mechanisms and therapeutic targets with exceptional precision. This review provides an integrative perspective on biofilm formation mechanisms and their role in infections, highlighting the innovative applications of AI in this domain. By integrating data from diverse biological systems, AI accelerates drug discovery, optimizes treatment regimens, and enables real-time monitoring of biofilm dynamics. From predictive analytics to personalized care, we explore how AI enhances biofilm diagnostics and introduces precision medicine in biofilmassociated infections. This approach not only addresses the limitations of traditional methods but also paves the way for revolutionary advancements in infection control, antimicrobial resistance management, and improved patient outcomes.