Performance of Population Pharmacokinetic Models in Predicting Polymyxin B Exposures.
Vincent H Tam, Lawrence S Lee, Tat-Ming Ng, Tze-Peng Lim, Benjamin P Z Cherng, Hafeez Adewusi, Kim H Hee, Ying Ding, Shimin Jasmine Chung, Li-Min Ling, Piotr Chlebicki, Andrea L H Kwa, David C Lye
Author Information
Vincent H Tam: University of Houston, Houston, TX 77204, USA. ORCID
Lawrence S Lee: National Centre for Infectious Diseases, Singapore 308442, Singapore.
Tat-Ming Ng: Tan Tock Seng Hospital, Singapore 308433, Singapore.
Tze-Peng Lim: Singapore General Hospital, Singapore 169608, Singapore. ORCID
Benjamin P Z Cherng: Singapore General Hospital, Singapore 169608, Singapore.
Hafeez Adewusi: University of Houston, Houston, TX 77204, USA.
Kim H Hee: Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore.
Ying Ding: National Centre for Infectious Diseases, Singapore 308442, Singapore.
Shimin Jasmine Chung: Singapore General Hospital, Singapore 169608, Singapore.
Li-Min Ling: National Centre for Infectious Diseases, Singapore 308442, Singapore.
Piotr Chlebicki: Singapore General Hospital, Singapore 169608, Singapore.
Andrea L H Kwa: Singapore General Hospital, Singapore 169608, Singapore.
David C Lye: National Centre for Infectious Diseases, Singapore 308442, Singapore.
Polymyxin B is the last line of defense in treating multidrug-resistant gram-negative bacterial infections. Dosing of polymyxin B is currently based on total body weight, and a substantial intersubject variability has been reported. We evaluated the performance of different population pharmacokinetic models to predict polymyxin B exposures observed in individual patients. In a prospective observational study, standard dosing (mean 2.5 mg/kg daily) was administered in 13 adult patients. Serial blood samples were obtained at steady state, and plasma polymyxin B concentrations were determined by a validated liquid chromatography tandem mass spectrometry (LC-MS/MS) method. The best-fit estimates of clearance and daily doses were used to derive the observed area under the curve (AUC) in concentration-time profiles. For comparison, 5 different population pharmacokinetic models of polymyxin B were conditioned using patient-specific dosing and demographic (if applicable) variables to predict polymyxin B AUC of the same patient. The predictive performance of the models was assessed by the coefficient of correlation, bias, and precision. The correlations between observed and predicted AUC in all 5 models examined were poor (r < 0.2). Nonetheless, the models were reasonable in capturing AUC variability in the patient population. Therapeutic drug monitoring currently remains the only viable approach to individualized dosing.
