PKPD Model

As an example, Hsieh et al. identified toxicodynamic biomarkers in monkey semm that demonstrated a quantitative relationship with drug exposure (Cr iax, AUC) and related pathological events [148], The biomarkers were used for a more precise calculation of the no observed adverse effect level (NOAEL). The safety of three different dosing schedules was predicted using pharmacokinetic pharmacodynamic (PKPD) modeling and biomarker analysis. 

There are a number of sources of variability in human drug response which do not fit into either of the above two categories. These include the disease state of the individual, their compliance with the prescribed drug regimen, and any exercise which the patient may or may not undertake. These variables will not be discussed in detail here since they are not considered as sources of variability in the PKPD models used within this chapter. The in vivo studies which the PKPD models are chosen to represent are usually carried out either under controlled conditions in healthy individuals where such variables do not apply, or in hospitalized patients where compliance should not be an issue. 

Limn D, Best N, Spiegelhalter D, Graham G, Neuenschwander B (2009) Combining MCMC with sequential PKPD modelling. J Pharmacokinet Pharmacodyn 36 19-38... 

V. Luckow and O. Della Paschoa, PKPD modeling of high-dose ditliazem—absporption-rate dependency of the hysteresis loop. Int J Clin Pharmacol Ther 35 418-425 (1997). 

D. R. Mould, PKPD models for white cell responses to hematopoietic stimulation with and without chemotherapy. American Society of Clinical Pharmacology and Therapeutics Annual Meeting, Orlando, FL, March 2-5, 2005. 

Pharmacokinetic-pharmacodynamic (PKPD) modeling makes a quantitative link between the pharmacokinetic profile of the drug and the concentration required to significantly occupy the target receptor and drive efficacy. The free... 

For some dmgs, we can link the parameters and equations of pharmacokinetics to those of pharmacodynamics, resulting in a PKPD model which can predict pharmacological effect over time. This concept is discussed in more detail later in this chapter. (Equation 17.7 is a typical PKPD equation.) Figure 17.3 depicts the relationship of effect versus time for the dmg albuterol (salbuta-mol) and contrasts this with a superimposed plot of plasma dmg concentration versus time. 

The function sim.pkpd.muit simulates a clinical response R) on the basis of a PK/PD model. It incorporates a combined placebo (P) effect and a drug (D) effect. The placebo effect at time t is defined as... 

The data frame pkpdi is generated according to the PK-PD model above, using the following call to the function sim.pkpd.muit. Figure 4.2 shows a trellis display of the corresponding time profiles for the simulated PD response. 

---