The Pmetrics Population Modeling and Monte Carlo Simulation, and BestDose Clinical, Software
Roger Jelliffe, MD, Michael Neely, MD, Walter Yamada, Ph.D.,Alan Schumitzky, PhD, David Bayard, PhD, Michael Van Guilder, PhD, Andreas Botnen, M.S., Alison Thomson, Ph.D, Maurice Khayat, M.D., and Aida Bustad, B. S.
USC Laboratory of Applied Pharmacokinetics and Bioinformatics Children’s Hospital of Los Angeles, USC Keck School of Medicine, Los Angeles CA
The Pmetrics population modeling software runs on Windows or Mac machines, and is imbedded in R. The user defines a structural PK/PD model The data files are entered. along with the instructions. Routines for checking data files and viewing results are provided. Likelihoods are exact, behavior is statistically consistent, and parameter estimates are precise [1]. Rigorous Monte Carlo simulation is provided which preserves the unique discrete point mass nonparametric models. The Pmetrics and BestDose software is available free by license from Dr. Neely.
The BestDose clinical software [2] uses Pmetrics population models, currently for a 3 compartment linear system. More complex and capable software to manage multiple nonlinear interacting multidrug systems is in development. BestDose computes the dosage regimen to hit desired targets with minimum expected weighted squared error, thus providing maximal precision in dosage regimen design, a feature not seen with any other currently known clinical software. Models for planning, monitoring, and adjusting therapy with aminoglycosides, vancomycin (including continuous IV vancomycin), digoxin, carbamazepine, and valproate are available.
The interacting multiple model (IMM) Bayesian fitting option [3] now allows parameter values to change if needed for analysis of acutely ill unstable patients with high intrapatient variability, and provides the most precise tracking of drugs in over 130 clinically unstable gentamicin and 130 vancomycin patients [4].
Multiple model optimal (MMopt) sampling strategies for developing the most informative TDM protocols are also available, using a new strategy not based on Fisher information, but rather on minimizing the Bayes risk of misclassification of the nonparametric support points which make up the population and each patient's individual models. MMopt outperforms the methods based on Fisher information such as ED, EID, and E log D optimal. MMopt also does not require 1 sample per parameter but can also use only one or two samples as desired [5,6].
In all the software, creatinine clearance is estimated based on one or two either stable or changing serum creatinines, age, gender, height, and weight [7].
References:
[1] Bustad A, Terziivanov D, Leary R, Port R, Schumitzky A, and Jelliffe R: Parametric and Nonparametric Population Methods: Their Comparative Performance in Analysing a Clinical Data Set and Two Monte Carlo Simulation Studies. Clin. Pharmacokinet., 45: 365-383, 2006.
[2] Jelliffe R, Schumitzky A, Bayard D, Milman M, Van Guilder M, Wang X, Jiang F, Barbaut X, and Maire P: Model-Based, Goal-Oriented, Individualized Drug Therapy: Linkage of Population Modeling, New "Multiple Model" Dosage Design, Bayesian Feedback, and Individualized Target Goals. Clin. Pharmacokinet. 34: 57-77, 1998.
[3] Bayard D, and Jelliffe R: A Bayesian Approach to Tracking Patients having Changing Pharmacokinetic Parameters. J. Pharmacokin. Pharmacodyn. 31 (1): 75-107, 2004.
[4] Macdonald I, Staatz C, Jelliffe R, and Thomson A: Evaluation and Comparison of Simple Multiple Model, Richer Data Multiple Model, and Sequential Interacting Multiple Model (IMM) Bayesian Analyses of Gentamicin and Vancomycin Data Collected From Patients Undergoing Cardiothoracic Surgery. Ther. Drug Monit. 30:67–74, 2008.
[5] Jelliffe R and Neely, eds, Individualized Drug Therapy for Patients, Elsevier, 2016, pp 91-102.
[6] Bayard DS, Neely M. Experiment design for nonparametric models based on minimizing Bayes Risk: application to voriconazole. J Pharmacokinet Pharmacodynam. Epub ahead of print 2016 Dec 1.
[7] Jelliffe R: Estimation of Creatinine Clearance in Patients with Unstable Renal Function, without a Urine Specimen. Am. J. Nephrology, 22: 3200-324, 2002.
