Department of Pharmacology, Physiology, and Neuroscience, Rutgers University-New Jersey Medical School, Newark, New Jersey, United States of America.
Center for Tuberculosis Research and Department of Medicine, Johns Hopkins University, Baltimore, MD, United States of America.
PLoS One. 2021 May 3;16(5):e0249841. doi: 10.1371/journal.pone.0249841. eCollection 2021.
We present further study of a subset of carbapenems, arising from a previously reported machine learning approach, with regard to their mouse pharmacokinetic profiling and subsequent study in a mouse model of sub-acute Mycobacterium tuberculosis infection. Pharmacokinetic metrics for such small molecules were compared to those for meropenem and biapenem, resulting in the selection of two carbapenems to be assessed for their ability to reduce M. tuberculosis bacterial loads in the lungs of infected mice. The original syntheses of these two carbapenems were optimized to provide multigram quantities of each compound. One of the two experimental carbapenems, JSF-2204, exhibited efficacy equivalent to that of meropenem, while both were inferior to rifampin. The lessons learned in this study point toward the need to further enhance the pharmacokinetic profiles of experimental carbapenems to positively impact in vivo efficacy performance.
我们进一步研究了一组碳青霉烯类抗生素,这些抗生素是根据之前报道的机器学习方法选择的,研究内容涉及它们在小鼠体内的药代动力学特征,以及在亚急性结核分枝杆菌感染小鼠模型中的后续研究。我们比较了这些小分子的药代动力学指标与美罗培南和比阿培南的药代动力学指标,从而选择了两种碳青霉烯类抗生素来评估它们在感染小鼠肺部降低结核分枝杆菌负荷的能力。这两种碳青霉烯类抗生素的原始合成方法经过优化,以提供每种化合物的大量供应。两种实验性碳青霉烯类抗生素中的一种,JSF-2204,表现出与美罗培南相当的疗效,而两者均劣于利福平。本研究中的经验教训表明,需要进一步提高实验性碳青霉烯类抗生素的药代动力学特征,以积极影响体内疗效表现。