Niño-Vega Gustavo A, Padró-Villegas Leonardo, López-Romero Everardo
Departamento de Biología, División de Ciencias Naturales y Exactas, Campus Guanajuato, Universidad de Guanajuato, Noria Alta s/n, col. Noria Alta, Guanajuato C.P. 36050, Mexico.
J Fungi (Basel). 2024 Dec 15;10(12):871. doi: 10.3390/jof10120871.
This review explores current advancements and challenges in antifungal therapies amid rising fungal infections, particularly in immunocompromised patients. We detail the limitations of existing antifungal classes-azoles, echinocandins, polyenes, and flucytosine-in managing systemic infections and the urgent need for alternative solutions. With the increasing incidence of resistance pathogens, such as and , we assess emerging antifungal agents, including Ibrexafungerp, T-2307, and N'-Phenylhydrazides, which target diverse fungal cell mechanisms. Innovations, such as nanoparticles, drug repurposing, and natural products, are also evaluated for their potential to improve efficacy and reduce resistance. We emphasize the importance of novel approaches to address the growing threat posed by fungal infections, particularly for patients with limited treatment options. Finally, we briefly examine the potential use of artificial intelligence (AI) in the development of new antifungal treatments, diagnoses, and resistance prediction, which provides powerful tools in the fight against fungal pathogens. Overall, we highlight the pressing need for continued research to advance antifungal treatments and improve outcomes for high-risk populations.
本综述探讨了在真菌感染不断增加的情况下，尤其是在免疫功能低下患者中，抗真菌治疗的当前进展和挑战。我们详细阐述了现有抗真菌药物类别——唑类、棘白菌素类、多烯类和氟胞嘧啶——在治疗全身感染方面的局限性，以及对替代解决方案的迫切需求。随着耐药病原体（如[此处缺失具体病原体名称]）发病率的不断上升，我们评估了新兴的抗真菌药物，包括艾伯康唑、T-2307和N'-苯基酰肼，它们针对不同的真菌细胞机制。纳米颗粒、药物重新利用和天然产物等创新方法也因其提高疗效和降低耐药性的潜力而得到评估。我们强调了采用新方法应对真菌感染日益增长的威胁的重要性，特别是对于治疗选择有限的患者。最后，我们简要探讨了人工智能（AI）在新型抗真菌治疗、诊断和耐药性预测方面的潜在应用，这为对抗真菌病原体提供了强大工具。总体而言，我们强调迫切需要持续研究，以推进抗真菌治疗并改善高危人群的治疗结果。
