Teresa Garcia-Martinez (1,2), Mª Dolores Belles-Medall(1), Raul Ferrando Piqueres (1,2), Victor Mangas-Sanjuan (2,3), Matilde Merino-Sanjuan (2,3)
: (1) Department of Pharmacy, General University Hospital of Castellón. Castellón de La Plana, Spain. (2) Department of Pharmacy and Pharmaceutical Technology and Parasitology, Faculty of Pharmacy, University of Valencia, Valencia, Spain. (3) Interuniversity Institute of Recognition Research Molecular and Technological Development, Burjassot, Valencia, Spain.
Introduction: Daptomycin is authorized for the treatment of complicated skin and soft tissue infections (IPPBc), right-sided infective endocarditis (EID) due to Staphylococcus aureus, and bacteraemia caused by Staphylococcus aureus when is associated with EID or IPPBc. The authorized dose is 4 mg/kg in a single daily dose in IPPBc without bacteraemia and 6 mg / kg in a single daily dose in EID and IPPBc associated with bacteraemia. The use of larger doses is currently being extended, in a range between 8 and 12 mg / kg / day. The results provided by the post-marketing trials show that the higher clinical response rate is obtained when a dose of 10mg / kg is used, which is justified by the daptomycin-dependent concentration effect[1-2]
Objectives: The aim of this study is to develop a population pharmacokinetic model of daptomycin in patients with multiple type of infections using limited sampling strategies able to predict the success of the therapy based on the PK/PD target.
Methods: Prospective study of patients treated with intravenous daptomycin at any indication for one year in the General University Hospital of Castellon from March to December 2019. Blood samples were obtained at the fourth day of treatment at different sampling times within a 24-hour interval and the number of blood samples varied from 2 to 5 per individual. Daptomycin concentrations were determined by a validated HPLC method [3]. Demographic and biochemical variables (serum creatinine and serum albumin)from each patient were collected. Several compartmental pharmacokinetic models were implemented assuming linear and non-linear PK processes. Inter-individual variability (IIV) associated to the PK parameters was modeled exponentially and residual unexplained variability (RUV) was described with an additive model on the logarithmic scale. The population PK parameters were estimated using SAEM+IMP. Model selection was based on the statistically decrease of the OFV and the GOF plots. Model evaluation was performed through pc-VPC and bootstrap analysis (n=1000). Experimental data were logarithmically transformed. All data analyses were performed based on the population approach with the software Monolix Suite 2019R2 [4].
Results: 49 patients (10 women) with a median age of 68 years (range: 23-89 years) and a mean dose of daptomycin of 8.3 mg/kg (range: 5-13.3) were included. The mean serum creatinine values were 0.88 mg/dl and the serum albumin was 2.9 g/dl. A total of 180 concentration values (6.1%< LLOQ) were available with the following distribution: 67 pre-dose samples, 39 at 30 minutes after the end of the infusion and 74 between infusions. The one-compartment model parametrized in terms of CL and V adequately characterized the time-course of daptomycin in the population (OFV=694.2), whereas the two-compartment model did not statistically improved (OFV = 695.45). The large V (300 L) estimated could explain that daptomycin is highly bounded to blood cells. A moderate half-life (22h) was estimated based on the values obtained for CL (9.34 L/h) and V. IIV was only included in CL (21%) and no statistical improvement was observed when IIV was also added to V. The precision of the population parameters was high (RSE < 15%), but moderate for the IIV on CL (RSE =47%).
Conclusions: The one-compartment pharmacokinetic model was able to describe the pharmacokinetics of daptomycin with linear elimination kinetics and moderate interindividual variability on CL. Prospective analysis are encouraged to understand the clinical relevance of therapeutic drug monitoring of daptomycin for its optimal dose selection.
References:
[1] M. Falcone, A. Russo, MI Cassetta, A Lappa, L. Tritapepe, G. d’Ettorre, S. Fallani, A. Novelli, M. Venditti. J Infect Chemother (4):732- 9 (2013).
[2] Soraluce A, Asín-Prieto E, Rodríguez-Gascón A, Barrasa H, Maynar J, Carcelero E, Soy D, Isla A. Int J Antimicrob Agents. 2018 Aug;52(2):158-165.
[3] C. M. Tobin, J. M. Darville, A. M. Lovering and A. P. MacGowan. An HPLC assay for daptomycin in serum. Journal of Antimicrobial Chemotherapy 62, 1462–1476.
[4] http://lixoft.com/download/win64-monolix-suite-2019r2/
Reference: PAGE () Abstr 9426 [www.page-meeting.org/?abstract=9426]
Poster: Drug/Disease Modelling - Infection