Multiple dosing pharmacokinetic models

Modeling to Predict Single- and Multiple-Dose Pharmacokinetic Profiles 98... 

MODELING TO PREDICT SINGLE- AND MULTIPLE-DOSE PHARMACOKINETIC PROFILES... 

M.C. Wacholtz, N. Minton, and W.J. Jusko. 2004. Pharmacokinetic and pharmacodynamic modeling of recombinant human erythropoietin after single and multiple doses in healthy volunteers. 

The statistical submodel characterizes the pharmacokinetic variability of the mAb and includes the influence of random - that is, not quantifiable or uncontrollable factors. If multiple doses of the antibody are administered, then three hierarchical components of random variability can be defined inter-individual variability inter-occasional variability and residual variability. Inter-individual variability quantifies the unexplained difference of the pharmacokinetic parameters between individuals. If data are available from different administrations to one patient, inter-occasional variability can be estimated as random variation of a pharmacokinetic parameter (for example, CL) between the different administration periods. For mAbs, this was first introduced in sibrotuzumab data analysis. In order to individualize therapy based on concentration measurements, it is a prerequisite that inter-occasional variability (variability within one patient at multiple administrations) is lower than inter-individual variability (variability between patients). Residual variability accounts for model misspecification, errors in documentation of the dosage regimen or blood sampling time points, assay variability, and other sources of error. 

The pharmacokinetic evaluation of biopharmaceuticals is generally simplified by the usual metabolism of products to small peptides and to amino acids, and thus classical biotransformation and metabolism studies are rarely necessary. Routine studies to assess mass balance are not useful. However, both single- and multiple-dose toxicokinetic data are essential in safety pharmacology asessments, and these can be complicated by two factors (1) biphasic clearance with a saturable, initial, receptor-dependent clearance phase, which may cause nonlinearity in dose-exposure relationships and doseresponses [14] and (2) antibody production against an antigenic biopharmaceutical that can alter clearance or activity in more chronic repeat-dose safety studies in the preclinical model. 

If possible, these developability pharmacology studies should be conducted with dosing to steady state unless the candidate is to be used as a singledose therapeutic. The number of doses required to reach steady state depends on the compound s pharmacokinetic profile in the same animal model. These multiple-dose studies provide information on the frequency of dosing necessary to maximize the biological response. This is particularly important for compounds that inhibit an enzymatic system or are effective only during certain phases of a cell cycle. 

Dose-response models describe a cause-effect relationship. There are a wide range of mathematical models that have been used for this purpose. The complexity of a dose-response model can range from a simple one-parameter equation to complex multicompartment pharmacokinetic/pharmacodynamic models. Many dose-response models, including most cancer risk assessment models, are population models that predict the frequency of a disease in a population. Such dose-response models typically employ one or more frequency distributions as part of the equation. Dose-response may also operate at an individual level and predict the severity of a health outcome as a function of dose. Particularly complex dose-response models may model both severity of outcome and population variability, and perhaps even recognize the influence of multiple causal factors. 

These linear kinetic models and diffusion models of skin absorption kinetics have a number of features in common they are subject to similar constraints and have a similar theoretical basis. The kinetic models, however, are more versatile and are potentially powerful predictive tools used to simulate various aspects of percutaneous absorption. Techniques for simulating multiple-dose behavior evaporation, cutaneous metabolism, microbial degradation, and other surface-loss processes dermal risk assessment transdermal drug delivery and vehicle effects have all been described. Recently, more sophisticated approaches involving physiologically relevant perfusion-limited models for simulating skin absorption pharmacokinetics have been described. These advanced models provide the conceptual framework from which experiments may be designed to simultaneously assess the role of the cutaneous vasculature and cutaneous metabolism in percutaneous absorption. 

In addition to the species and model differences in these two studies, only the latter was done following multiple dosing. These differences could be resolved by calculation of the appropriate pharmacokinetic parameters. Bergan has made such calculations for cefazolin and several other cephalosporins in humans and found cefazolin to be the drug of choice in distributing to tissue fluids. 0 This conclusion was based on the apparent volume of tissue compartment, calculated from V j (steady state) and a comparison of the magnitudes of the transfer rate constants ki2 (entry into tissue) and k2i (exit from tissue). Of the cephalosporins studied, only cefazolin had a ratio greater than unity,... 

Figure 10.2 Pharmacokinetics of intravenous T-20 administration. The graphs show the expected changes in plasma concentration vs time after intravenous administration of a single injection (dashed line) or multiple injections (solid line) of intravenous T-20 (lOOmg/dose). The curves are based on the half-life (1.8 h) and volume of distribution (4.7 L) measured in 17 human volunteers [4] using a one-compartment model (see Equation 7-3). Because of its rapid elimination, multiple doses are needed to maintain the peptide level in the effective range.

---