bioRxivMicrobiologyPreprint
Novel regimens for treatment of Mycobacterium avium lung disease based on advanced in vitro systems and the mathematics of basis functions
Shashikant SrivastavaiD, Sanjay Kumar SinghiD, Gunavanthi D. BoorgulaiD, Pamela J. McShaneiD, Tawanda GumboiD
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Abstract
Azithromycin plus ethambutol plus rifabutin (azithromycin-ethambutol-rifabutin) is the standard-of-care (SOC) for Mycobacterium avium-complex lung disease. The SOC achieves sustained sputum culture conversion in only 43-53% of patients, after an average of 18 months of therapy. Recent quantitative analyses ranked omadacycline, ceftriaxone, and minocycline highest for microbial kill. Azithromycin-minocycline-ethambutol, azithromycin-omadacycline-ethambutol, epetraborole-omadacycline-ethambutol, ceftriaxone-omadacycline-rifabutin, and the SOC were compared in the intracellular hollow fiber system model of M. avium lung disease (HFS-MAC). HFS-MAC units were treated once daily for 28 days to mimic the intrapulmonary pharmacokinetics of each drug. The ceftriaxone concentrations measured in the HFS-MAC were only 1% of those achieved in the lung by standard clinical doses. Changes in the bacterial burden were described using basis functions (BF). For liquid cultures, BF 1 (BF1) was described by a linear regression-based slope, with steepest kill slope (95% Confidence interval) of 7.87 (1.52 to14.23) by ceftriaxone-omadacycline-rifabutin versus 1.04 (-0.84 to 2.92) for SOC. For the CFU/mL readout, the BF1 steepest non-linear kill slope was for ceftriaxone-omadacycline-rifabutin of 0.55 (0.35 to 0.98) log10 CFU/mL/day versus 0.16 (0.07 to 0.25) log10 CFU/mL/day for the SOC. Thus, ceftriaxone-omadacycline-rifabutin is potentially better than the SOC, even though further ceftriaxone dose optimization is required. BF2 described rebound growth and drug-resistant subpopulation growth, and demonstrated that contrary to popular belief, SOC rebound was best explained by ethambutol-resistance (r2>0.99, p=0.01) and not by azithromycin-resistance (r2=0.27, p=0.32), questioning ethambutols role in the SOC. The BF framework is potentially easy to adapt for modeling other anti-infective agents across many infectious diseases.
- organism: human
- assay: metagenomics
- research focus: drug response / drug discovery
- approach: statistical model
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