Omadacycline efficacy in the hollow fibre system model of pulmonary Mycobacterium avium complex and potency at clinically attainable doses

Abstract

Objectives: The standard of care (SOC) for the treatment of pulmonary Mycobacterium avium complex (MAC) disease (clarithromycin, rifabutin, and ethambutol) achieves sustained sputum conversion rates of only 54%. Thus, new treatments should be prioritized.

Methods: We identified the omadacycline MIC against one laboratory MAC strain and calculated drug half life in solution, which we compared with measured MAC doubling times. Next, we performed an omadacycline hollow fibre system model of intracellular MAC (HFS-MAC) exposure-effect study, as well as the three-drug SOC, using pharmacokinetics achieved in patient lung lesions. Data was analysed using bacterial kill slopes (γ-slopes) and inhibitory sigmoid Emax bacterial burden versus exposure analyses. Monte Carlo experiments (MCE) were used to identify the optimal omadacycline clinical dose.

Results: Omadacycline concentration declined in solution with a half-life of 27.7 h versus a MAC doubling time of 16.3 h, leading to artefactually high MICs. Exposures mediating 80% of maximal effect changed up to 8-fold depending on sampling day with bacterial burden versus exposure analyses, while γ-slope-based analyses gave a single robust estimate. The highest omadacycline monotherapy γ-slope was -0.114 (95% CI: -0.141 to -0.087) (r2 = 0.98) versus -0.114 (95% CI: -0.133 to -0.094) (r2 = 0.99) with the SOC. MCEs demonstrated that 450 mg of omadacycline given orally on the first 2 days followed by 300 mg daily would achieve the AUC0-24 target of 39.67 mg·h/L.

Conclusions: Omadacycline may be a potential treatment option for pulmonary MAC, possibly as a back-bone treatment for a new MAC regimen and warrants future study in treatment of this disease.

Figure 1.

MICs and omadacycline stability. (a) Visual inspection of plates demonstrates omadacycline trailing effect and an MIC of 16 mg/L. (b) The wells were cultured for colony forming units and results modelled using inhibitory sigmoid E_max model. The lowest concentration associated with a bacterial burden below that on day 0, which corresponded with clarithromycin MIC, was used to read the omadacycline MIC. Since the x-axis is a log-scale, and log 0 does not exist (or is undefined), the lowest concentration shown is at 0.0625 mg/L and not 0 mg/L. (c) Decline in omadacycline concentration with time when infused from the same solution in a syringe. (d) The drug AUC decline followed an exponential decline model. This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.

Figure 2.

Drug pharmacokinetics achieved in the HFS-MAC, equivalent to site of infection. (a) Non-compartmental pharmacokinetic analysis of omadacycline concentrations measured in each HFS-MAC unit. Because of the dynamic range, the concentrations are shown as ng/mL. The last dose was given on day 28, and then allowed to decline. (b) Compartmental pharmacokinetic model predicted versus observed concentrations [r²= 0.84]. (c to f) The lines show the mean concentration and shaded areas 95% CIs for a compartmental pharmacokinetic model where each HFS-MAC unit was taken as a patient in a population. This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.

Figure 3.

Change of MAC burden with treatment in the HFS-MAC. Symbols show the mean cfu per mL and error bars are standard deviation. Particularly interesting is using the three-drug standard of care (SOC) as the context, and that high dose monotherapy has efficacy that equals that of SOC. This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.

Figure 4.

Traditional versus γ-slope-based pharmacokinetics/pharmacodynamics approaches for omadacycline. (a and b) Symbols are mean log₁₀ cfu/mL and error bars are standard deviation; on days 3 and 7 the datapoints for the higher AUC MIC exposures were automatically eliminated by the program as outliers. Three important findings are the change of E_max, EC₅₀, and E_con with each sampling day. Particularly, in (b), the 2.0 log₁₀ cfu/mL kill is achieved at different exposures depending on sampling day and the exposure value varies almost 50-fold depending on which day is used for the regression. (c) The error bars show the 95% CI. In the γ-slope-base pharmacokinetics/pharmacodynamics modelling, a single equation and single set of parameter estimates summarized all data points. This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.

Figure 5.

Monte Carlo experiments in 10 000 subjects treated with standard dose omadacycline. (a) Symbols are mean concentrations and shaded area is the 95% CI. Concentration–time profiles in the first week are shown for serum and in the lung. (b) Target attainment probability for 10 000 patients showing proportion of patients who achieve target AUC/MIC exposures under two different drug penetration criteria. This figure appears in colour in the online version of JAC and in black and white in the print version of JAC.