Roger W. Jelliffe

Creatinine Clearance: Bedside Estimate

Excerpt To the editor: Previously described computer programs have shown their ability to estimate endogenous creatinine clearance (Ccr) with reasonable accuracy when urine specimens cannot be obta...

Accurate detection of outliers and subpopulations with Pmetrics, a nonparametric and parametric pharmacometric modeling and simulation package for R.

Introduction: Nonparametric population modeling algorithms have a theoretical superiority over parametric methods to detect pharmacokinetic and pharmacodynamic subgroups and outliers within a study population. Methods: The authors created “Pmetrics,” a new Windows and Unix R software package that updates the older MM-USCPACK software for nonparametric and parametric population modeling and simulation of pharmacokinetic and pharmacodynamic systems. The parametric iterative 2-stage Bayesian and the nonparametric adaptive grid (NPAG) approaches in Pmetrics were used to fit a simulated population with bimodal elimination (Kel) and unimodal volume of distribution (Vd), plus an extreme outlier, for a 1-compartment model of an intravenous drug. Results: The true means (SD) for Kel and Vd in the population sample were 0.19 (0.17) and 102 (22.3), respectively. Those found by NPAG were 0.19 (0.16) and 104 (22.6). The iterative 2-stage Bayesian estimated them to be 0.18 (0.16) and 104 (24.4). However, given the bimodality of Kel, no subject had a value near the mean for the population. Only NPAG was able to accurately detect the bimodal distribution for Kel and to find the outlier in both the population model and in the Bayesian posterior parameter estimates. Conclusions: Built on over 3 decades of work, Pmetrics adopts a robust, reliable, and mature nonparametric approach to population modeling, which was better than the parametric method at discovering true pharmacokinetic subgroups and an outlier.

Voriconazole Pharmacokinetics and Pharmacodynamics in Children

BACKGROUND Voriconazole pharmacokinetic and pharmacodynamic data are lacking in children. METHODS Records at the Childrens Hospital Los Angeles were reviewed for children with > or =1 serum voriconazole concentration measured from 1 May 2006 through 1 June 2007. Information on demographic characteristics, dosing histories, serum concentrations, toxicity and survival, and outcomes was obtained. RESULTS A total of 207 voriconazole measurements were obtained from 46 patients (age, 0.8-20.5 years). A 2-compartment Michaelis-Menten pharmacokinetic model fit the data best but explained only 80% of the observed variability. The crude mortality rate was 28%, and each trough serum voriconazole concentration <1000 ng/mL was associated with a 2.6-fold increased odds of death (95% confidence interval, 1.6-4.8; P=.002). Serum voriconazole concentrations were not associated with hepatotoxicity. Simulations predicted an intravenous dose of 7 mg/kg or an oral dose of 200 mg twice daily would achieve a trough >1000 ng/mL in most patients, but with a wide range of possible concentrations. CONCLUSIONS We found a pharmacodynamic association between a voriconazole trough >1000 ng/mL and survival and marked pharmacokinetic variability, particularly after enteral dosing, justifying the measurement of serum concentrations.

An Improved Method of Digoxin Therapy

Abstract An improved method of oral digoxin therapy is discussed for euthyroid patients with normal electrolytes and gastrointestinal absorption, whose renal function may be normal, impaired, or ra...

A computer program for estimation of creatinine clearance from unstable serum creatinine levels, age, sex, and weight☆

Abstract Quantitative appraisal of renal function has been difficult when reliable urine collections from patients cannot be obtained for measurement of endogenous creatinine clearance (CCr) by standard methods. Previous estimates of CCr from data of stable serum creatinine have been reasonably accurate for clinical purposes. A reappraisal of this data, coupled with a dynamic model of creatinine kinetics in patients, has led to a method to estimate CCr even when serum creatinine levels and renal function are rapidly changing. A computer program has been written for a hospital-based time-shared terminal to estimate CCr in this manner.

Population pharmacokinetic modeling of isoniazid, rifampin, and pyrazinamide.

Isoniazid (INH), rifampin (RIF), and pyrazinamide (PZA) are the most important drugs for the treatment of tuberculosis (TB). The pharmacokinetics of all three drugs in the plasma of 24 healthy males were studied as part of a randomized cross-over phase I study of two dosage forms. Subjects ingested single doses of INH at 250 mg, RIF at 600 mg, and PZA at 1,500 mg. Plasma was collected for 36 h and was assayed by high-performance liquid chromatography. The data were analyzed by noncompartmental, iterative two-stage maximum a posteriori probability Bayesian (IT2B) and nonparametric expectation maximization (NPEM) population modeling methods. Fast and slow acetylators of INH had median peak concentrations in plasma (C[max]) of 2.44 and 3.64 microg/ml, respectively, both of which occurred at 1.0 h postdose (time of maximum concentrations of drugs in plasma [T(max)]), with median elimination half-lives (t1/2) of 1.2 and 3.3 h, respectively (by the NPEM method). RIF produced a median C(max) of 11.80 microg/ml, a T(max) of 1.0 h, and a t1/2 of 3.4 h. PZA produced a median C(max) of 28.80 microg/ml, a T(max) of 1.0 h, and a t1/2 of 10.0 h. The pharmacokinetic behaviors of INH, RIF, and PZA were well described by the three methods used. These models can serve as benchmarks for comparison with models for other populations, such as patients with TB or TB with AIDS.

A Nomogram for Digoxin Therapy

Abstract A nomogram is described for developing loading and maintenance dosage regimens of digoxin for adult euthyrold patients with reasonably normal hepatic function, in normal electrolyte balance, who have no obvious abnormality of gastrointestinal absorption. The nomogram relates observed data of risk of adverse reactions, risk of arrhythmias, serum digoxin levels, calculated maximum total body digoxin concentrations, body weight, total oral loading dose, data of renal function and daily maintenance dose. Physicians may select an acceptable risk or peak serum level depending upon each patients clinical status, and then develop a loading and maintenance dosage regimen to consider giving, adjusted to the patients body weight and renal function, to achieve ones selected therapeutic goals with reasonable accuracy for most patients most of the time.

Individualizing drug dosage regimens: roles of population pharmacokinetic and dynamic models, Bayesian fitting, and adaptive control.

The role of population pharmacokinetic modeling is to store experience with drug behavior. The behavior of the model is then correlated with the clinical behavior of the patients studied, permitting selection of a specific serum level therapeutic goal that is based on each individual patients need for the drug and on the risk of adverse reactions, both of which must be considered. A dosage regimen is then computed to achieve that goal with maximum precision. The patient should not run a greater risk of toxicity than is justified, and should obtain the maximum possible benefit within the acceptable risk. The regimen is given and the patient monitored.

Model-based, goal-oriented, individualised drug therapy : Linkage of population modelling, new 'multiple model' dosage design, Bayesian feedback and individualised target goals

SummaryThis article examines the use of population pharmacokinetic models to store experiences about drugs in patients and to apply that experience to the care of new patients. Population models are the Bayesian prior. For truly individualised therapy, it is necessary first to select a specific target goal, such as a desired serum or peripheral compartment concentration, and then to develop the dosage regimen individualised to best hit that target in that patient.One must monitor the behaviour of the drug by measuring serum concentrations or other responses, hopefully obtained at optimally chosen times, not only to see the raw results, but to also make an individualised (Bayesian posterior) model of how the drug is behaving in that patient. Only then can one see the relationship between the dose and the absorption, distribution, effect and elimination of the drug, and the patient’s clinical sensitivity to it; one must always look at the patient. Only by looking at both the patient and the model can it be judged whether the target goal was correct or needs to be changed. The adjusted dosage regimen is again developed to hit that target most precisely starting with the very next dose, not just for some future steady state.Nonparametric population models have discrete, not continuous, parameter distributions. These lead naturally into the multiple model method of dosage design, specifically to hit a desired target with the greatest possible precision for whatever past experience and present data are available on that drug — a new feature for this goal-oriented, model-based, individualised drug therapy. As clinical versions of this new approach become available from several centres, it should lead to further improvements in patient care, especially for bacterial and viral infections, cardiovascular therapy, and cancer and transplant situations.

Improved clinical outcome of paediatric bone marrow recipients using a test dose and Bayesian pharmacokinetic individualization of busulfan dosage regimens.

In order to control busulfan pharmacokinetic variability and toxicity, a specific monitoring protocol was instituted in our bone marrow transplant BMT paediatric patients including a test dose, daily Bayesian forecasting of busulfan plasma levels, and Bayesian individualization of busulfan dosage regimens. Twenty-nine children received BMT after a busulfan-based conditioning regimen. Individual pharmacokinetic parameters were obtained following a 0.5 mg*kg test dose and were used for daily individualization of dosage regimens during the subsequent 4-day course of treatment. Doses were adjusted to reach a target mean AUC per 6 h between 4 and 6 μg.h.ml+1. Plasma busulfan assays were performed by liquid chromatography. Pharmacokinetic analysis used the USC*PACK software. The performance of the test dose to predict AUC during the busulfan regimen was evaluated. Incidence of toxicity, chimerism and relapse, overall Kaplan–Meier survival, and VOD-free survival were compared after matching our patients (group A) with patients conditioned by using standard doses of busulfan (group B). Busulfan doses were decreased in 69% of patients compared to conventional doses. Expected AUC was significantly correlated with observed AUC and predictability of the test dose was 101.9 ± 17.9%. Incidence of VOD in group A was 3.4% vs 24.1% in group B, while the incidence of stomatitis was similar. Engraftment was successful in all patients in group A. The rate of full engraftment at 3 months post-BMT was higher in group A (P = 0.012). Long-term overall survival did not differ between the two groups, in contrast to the 90-day survival. VOD-free survival was higher in group A (P = 0.026). Pharmacokinetic monitoring and individualization of busulfan dosage regimen are useful in improving clinical outcome and reducing early mortality in paediatric bone marrow transplant recipients. Bone Marrow Transplantation (2001) 28, 743–751.