Pharmacokinetics useful parameters

Exposure is represented by pharmacokinetic parameters demonstrating the local and systemic burden on the test species with the test compound and/or its metabolites. The area under the matrix level concentration-time curve (AUC) and/or the measurements of matrix concentrations at the expected peak-concentration time Cmax, or at some other selected time C(llme, are the most commonly used parameters. Other parameters might he more appropriate in particular cases. 

Although not perfect, Hansch s lipophilicity parameter and log P values are the most widely used parameters in QSAR studies. In addition to their effectiveness in predicting biological activity through target binding (pharmacodynamics), both parameters also affect pharmacokinetics. The pharmacokinetic applications of log P and 7r-values can be seen in Lipinski s rules and a Case Study (Carboxylate Antifungals) later in this chapter. 

Interpretation of findings from these studies will be aided by a good understanding of dose/concen-tration and concentration/response relationships for both desirable and undesirable drug effects. In certain instances, reliance on endpoints other than pharmacokinetic measures/parameters may be useful... 

Clearance is a parameter that has, perhaps, the greatest potential of any pharmacokinetic parameter for clinical applications. Furthermore, it is the most useful parameter available for the evaluation of the elimination mechanism and of the eliminating organs (kidney and liver). The utility of the clearance measurement lies in its intrinsic model independence. 

Allometric scaling (allometry) is the discipline that predicts human pharmacokinetics using preclinical data [16]. This approach is based on empirical observations that various physiological parameters are functions of body size. The most widely used equation in allometry is a one-term power function ... 

Lead optimization using drug metabolism and pharmacokinetics (DMPK) parameters has become one of the primary focuses of research organizations involved in drug discovery in the last decade. Using a combination of rapid in vivo and in vitro DMPK screening procedures on a large array of... 

Several review articles in recent years have described the role that a drug metabolism and pharmacokinetics (DMPK) department can play in the process of new drug discovery [1, 2, 4-11]. As shown in Figure 1, DMPK provides the tools and the assays to assess various new chemical entities (NCEs) in terms of their absorption, distribution, metabolism and excretion (ADME) properties as well as their pharmacokinetic (PK) parameters. In addition, DMPK scientists may also use various screens to understand the potential of NCEs for preclinical or clinical toxicity [12]. The goal of these efforts is to find a compound that is suitable for development. 

The intended use of a chemical probe will necessarily dictate its desirable characteristics. Probes of cellular processes used for epistatic perturbations will be subject to some of the same limitations of an in vivo probe of zebrafish developmental patterning however, drug metabolism and pharmacokinetic (DMPK) parameters essential for the action of an in vivo probe used in mouse or rat will not necessarily apply to the function of a cellular probe. Indeed, these differences will alter priorities for the beneficial characteristics of an in vitro probe when compared to an in vivo probe. For example, Lipinski s rule of five remains a central tenet of medicinal chemistry in drug discovery which serves as a useful limit of molecular characteristics for the development of orally bioavailable drugs, and while these guidelines generally describe preferable probe molecule properties, the rule of five may be... 

Lack of favorable ADME properties (absorption, distribution, metabolism, elimination) can preclude therapeutic use of an otherwise active molecule. The clinical pharmacokinetic parameters of clearance, half-life, volume of distribution, and bioavailability can be used to characterize ADME properties. 

What are called physiologically based pharmacokinetic (PBPK) and pharmacodynamic (PBPD) models are more mechanistically complex and often include more compartments, more parameters, and more detailed expressions of rates and fluxes and contain more mechanistic representation. This type of model is reviewed in more detail in Section 22.5. Here, we merely classify such models and note several characteristics. PBPK models have more parameters, are more mechanistic, can exploit a wider range of data, often represent the whole body, and can be used both to describe and interpolate as well as to predict and extrapolate. Complexity of such models ranges from moderate to high. They typically contain 10 or more compartments, and can range to hundreds. The increase in the number of flux relationships between compartments and the related parameters is often more than proportional to compartment count. 

Cronin WJ, Oswald EJ, Shelley ML, et al. 1995. A trichloroethylene risk assessment using a Monte Carlo analysis of parameter uncertainty in conjunction with physiologically-based pharmacokinetic modeling. Risk Anal 15 555-565. 

In practice, one will seek to obtain an estimate of the elimination constant kp and the plasma volume of distribution Vp by means of a single intravenous injection. These pharmacokinetic parameters are then used in the determination of the required dose D in the reservoir and the input rate constant k (i.e. the drip rate or the pump flow) in order to obtain an optimal steady state plasma concentration... 

The contents of this handbook should be utilized as a guide and in addition to sound clinical judgment. Consult full prescribing information and take into consideration each drug s pharmacokinetic profile, contraindications, warnings, precautions, adverse reactions, potential drug interactions, and monitoring parameters before use. 

Although most CF patients have shorter half-lives and larger volumes of distribution than non-CF patients, some patients exhibit decreased clearance. Possible causes include concomitant use of nephrotoxic medications, presence of diabetic nephropathy, history of transplantation (with immunosuppressant use and/or procedural hypoxic injury), and age-related decline in renal function in older adult patients. Additionally, CF patients are repeatedly exposed to multiple courses of IV aminoglycosides, which can result in decreased renal function. Evaluation of previous pharmacokinetic parameters and trends, along with incorporation of new health information, is key to providing appropriate dosage recommendations. 

Drugs can be cleared from the body by metabolism as well as renal excretion, and when this occurs it is not possible to measure directly the amount cleared by metabolism. However, the total clearance rate (TCR), or total body clearance, of the drug can be calculated from its pharmacokinetic parameters using the following equation ... 

The RCR can be determined from urine and plasma data using Eq. (18), and the TCR can be determined from the pharmacokinetic parameters using Eq. (19). Alternately, the RCR can be calculated by multiplying the TCR by the fraction of the dose excreted unchanged into urine,/), ... 

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