Abstract

More than 70% of bacteria are resistant to all or nearly all known antimicrobials, creating the need for the development of new types of antimicrobials or the use of "last-line" antimicrobial therapies for the treatment of multi-resistant bacteria. These antibiotics include Glycopeptide (Vancomycin), Polymyxin (Colistin), Lipopeptide (Daptomycin), and Carbapenem (Meropenem). However, due to the toxicity of these types of molecules, it is necessary to develop new rapid methodologies to be used in Therapeutic Drug Monitoring (TDM). TDM could improve patient outcomes and reduce healthcare costs by enabling a favorable clinical outcome. In this way, personalized antibiotic therapy emerges as a viable option, offering optimal dosing for each patient according to pharmacokinetic (PK) and pharmacodynamic (PD) parameters. Various techniques are used for this monitoring, including high-performance liquid chromatography (HPLC), gas chromatography-mass spectrometry (GC-MS), and immunoassays. The objective of this study is the development and characterization by ELISA of specific polyclonal antibodies for the recognition of the antibiotics Vancomycin (glycopeptide), Colistin (polymyxin), Daptomycin (lipopeptide), and Meropenem (carbapenem) for future applications in the monitoring of these antibiotics in different fluids, such as human plasma. The developed antibodies are capable of recognizing the antibiotic molecules with good detectability, showing an IC50 of 0.05 nM for Vancomycin, 7.56 nM for Colistin, 183.6 nM for Meropenem, and 13.82 nM for Daptomycin. These antibodies offer a promising tool for the precise and effective therapeutic monitoring of these critical antibiotics, potentially enhancing treatment efficacy and patient safety.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.