Stability Studies of Antipseudomonal Beta Lactam Agents for Outpatient Therapy.
Beatriz Fernández-RubioLaura Herrera-HidalgoArístides de AlarcónRafael Luque-MárquezLuis Eduardo Lopez-CortesSònia LuqueJosé María Gutiérrez-UrbónAurora Fernández-PoloAlicia Gutiérrez-ValenciaMaría V Gil-NavarroPublished in: Pharmaceutics (2023)
Outpatient parenteral antimicrobial therapy (OPAT) is a useful treatment strategy against Pseudomonas aeruginosa and other multidrug-resistant bacteria. However, it is hindered by the lack of stability data for the administration of antibiotics under OPAT conditions. Our objective was to investigate the stability of nine antipseudomonal and broad-spectrum beta lactam antibiotics (aztreonam, cefepime, cefiderocol, ceftazidime, ceftazidime/avibactam, ceftolozane/tazobactam, meropenem, meropenem/vaborbactam, and piperacillin/tazobactam) to allow the spread of OPAT programs. All the antibiotics were diluted in 500 mL 0.9% sodium chloride and stored at 4, 25, 32, and 37 °C for 72 h in two different devices (infusion bags and elastomeric pumps). The solutions were considered stable if the color, clearness, and pH remained unchanged and if the percentage of intact drug was ≥90%. All the antimicrobials remained stable 72 h under refrigerated conditions and at least 30 h at 25 °C. At 32 °C, all the antibiotics except for meropenem and meropenem/vaborbactam remained stable for 24 h or more. At 37 °C, only aztreonam, piperacillin/tazobactam, cefepime, cefiderocol, and ceftolozane/tazobactam were stable for at least 24 h. The stability results were the same in the two devices tested. All the antibiotics studied are actual alternatives for the treatment of antipseudomonal or multidrug-resistant infections in OPAT programs, although the temperature of the devices is crucial to ensure antibiotic stability.
Keyphrases
- gram negative
- multidrug resistant
- acinetobacter baumannii
- drug resistant
- klebsiella pneumoniae
- pseudomonas aeruginosa
- public health
- low dose
- staphylococcus aureus
- big data
- cystic fibrosis
- stem cells
- electronic health record
- machine learning
- emergency department
- bone marrow
- artificial intelligence
- drug induced
- adverse drug