Chapter 29 Weighting Data

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Combining Individual and Population Data

Once a drug is on the market and even before release pharmacokinetic models and parameter values should be well developed. Linear model or nonlinear. Numerous covariates would have been studied. This information can be very useful for developing suitable dosing regimens. In some cases customized for individual patients. One example is the development of dosing regimens for warfarin on warfarindosing.org. Other examples are included in resources such as FDA: Find Information about a Drug and NIH-NIAID: Search for Package Inserts.

A drug nomogram may be used to determine an initial dosing regimen. The calculation of this initial dosing regimen may be based on the patient weight or height. Other covariates such as renal function, cardiac function, liver status or smoking status might be considered. Mullen (1978) proposed a direct linear plot method (Figure 21.5.1) using data collected after two phenytoin steady state dosing regimens.

Another approach is the use of therapeutic drug monitoring (TDM). Briefly, this involves collecting one or more blood samples from the patient after their initial dose or dosing regimen. These samples are quickly assayed and analyzed for pharmacokinetic parameters. These parameter values may be supported by Bayesian estimation which includes population parameter values and their uncertainty (standard deviation or variance) as well as the individual subject data in the analysis.

Bayesian Analysis

Bayesian estimation of pharmacokinetic parmeters values is similar to ordinary nonlinear regression with a few differences.

Prior information of the pharmacokinetic model
Populations values and their uncertainty and
Some data from the individual patient of interest is necessary

A modified objective function is used for this analysis containing components related to the data and the population values, Equation 22.2.1.

Equation 29.7.3.1 Objective Function - Bayesian Estimation

where CalcD and ObsD are the calculated and observed concentration values. CalcP and PopP are the calculated and observed population parameter values. DVariance and PVariance are the variance in the concentration values and the population parameter values. Pharmacokinetic programs such as Boomer optimizes the objective function by calculating concentration values by adjusting the pharmacokinetic parameter values, CalcP. Note, the calculated concentration values are a function of the parameter values and time. The optimization procedure minimizes both the concentration residual between observed and calculated concentration and parameter value residual between the estimated parameter and the population parameter values.

References

Mullen, P. W. 1978 Optimal phenytoin therapy: a new technique for individualizing dosage. Clin. Pharmacol. Ther., 23(2), 228–232

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