Charles Burdet (1,2), Thu Thuy Nguyen (1), Jean de Gunzburg (3), Annie Ducher (3), Marion Ghidi (3), Xavier Duval (1,2), Marina Varastet (3), Antoine Andremont (1,2), France Mentré (1,2)
(1) INSERM & Paris Diderot University, UMR 1137, Paris, France; (2), AP-HP, Bichat Hospital, Paris, France; (3) Da Volterra, Paris, France
Objectives: Antibiotic administration leads to fecal microbiota disruption with emergence of antimicrobial resistance [1]. Animal data suggest that emergence of bacterial resistance can be predicted from fecal antibiotic exposure [2]. We developed a joint model of plasma and fecal pharmacokinetics of the fluoroquinolone antimicrobial moxifloxacin after oral administration in humans.
Methods: Fourteen healthy volunteers were recruited in a randomized clinical trial (sponsor Da Volterra) and received a 5-day course of moxifloxacin. Moxifloxacin dosing regimen (400 mg OAD) was similar to that usually administered in infected patients. Moxifloxacin plasma concentrations were determined at D1 and D5. Eleven fecal samples were obtained from D1 to D16 for measures of moxifloxacin concentrations. Nonlinear mixed-effects modeling was performed to characterize the pharmacokinetic properties of moxifloxacin and its fecal excretion. Model selection was performed by visual inspection of various goodness of fit plots and the Bayesian Information Criteria. Analysis was performed using the SAEM algorithm and the Monolix software (Lixoft, France) [3].
Results: Moxifloxacin plasma concentrations were best described by a 2 compartment model with first order absorption and linear elimination, with a lag time. Fecal concentrations were modeled using a transit compartment between plasma and feces. Goodness-of-fit of this model was satisfactory. Median (min-max) AUC of fecal moxifloxacin was 662 µg.d/g (412-1731).
Conclusions: We developed the first joint model of moxifloxacin pharmacokinetics in plasma and feces. The administration of moxifloxacin modifies the composition of the fecal microbiota, as it was shown for other antimicrobials [4, 5]. This might allow for resistant strains or other pathogenic bacteria to colonize the gut. The modeling of bacterial counts is thereby necessary.
References:
[1] Andremont A. Commensal Flora May Play Key Role in Spreading Antibiotic Resistance. ASM News 2003; 69(12): 601-7.
[2] Nguyen TT, Guedj J, Chachaty E, de Gunzburg J, Andremont A, Mentre F. Mathematical modeling of bacterial kinetics to predict the impact of antibiotic colonic exposure and treatment duration on the amount of resistant enterobacteria excreted. PLoS Comput Biol 2014; 10(9): e1003840.
[3] Kuhn E, Lavielle M. Maximum likelihood estimation in nonlinear mixed effects models. Comput Statist Data Anal 2005; 49: 1020-38.
[4] Fantin B, Duval X, Massias L, et al. Ciprofloxacin dosage and emergence of resistance in human commensal bacteria. J Infect Dis 2009; 200(3): 390-8.
[5] Michea-Hamzehpour M, Auckenthaler R, Kunz J, Pechere JC. Effect of a single dose of cefotaxime or ceftriaxone on human faecal flora. A double-blind study. Drugs 1988; 35 Suppl 2: 6-11.
Reference: PAGE 25 (2016) Abstr 5789 [www.page-meeting.org/?abstract=5789]
Poster: Drug/Disease modeling - Infection