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Novel regimens for treatment of Mycobacterium avium lung disease based on advanced in vitro systems and the mathematics of basis functions

Srivastava, S.; Singh, S.; Boorgula, G. D.; McShane, P. J.; Gumbo, T.

2026-03-31 microbiology
10.64898/2026.03.30.715241 bioRxiv
Show 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.

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