Biopharmaceutics. Группа авторов

Amiodarone 1.0–2.5 mg L⁻¹ Digoxin 0.5–2.0 mcg L⁻¹ Theophylline 10–20 mg L⁻¹

2.13 Compartmental Concepts in Pharmacokinetics

      The compartmental concepts in pharmacokinetics are used to ensure accurate estimation of pharmacokinetic parameters, such as elimination half‐life, the volume of distribution and elimination rate constant of a drug. The knowledge and understanding of compartmental concepts enable fitting of the pharmacokinetic profile into appropriate models to ensure the dosage regimens are predicted correctly in clinical settings.

The compartmental behaviour of a drug strongly depends on its distribution characteristics in the body and how quickly a drug achieves a distribution equilibrium. Many drugs follow a simple one‐compartmental model, where the whole body is treated as one single compartment and the distribution equilibrium is achieved instantaneously, see Figure 2.12. Achieving distribution equilibrium implies that the rate of transfer of drug from the blood to all body tissues and the rate of drug transfer from the body tissues back to the blood become equal instantaneously.

For some drugs, the distribution equilibrium takes time (several minutes to hours) depending upon the physicochemical properties of the drug. Often, the distribution of these drugs to the body tissues is very slow and the drug is distributed to highly perfused organs first, such as brain, heart, lung, liver and kidneys, which together with systemic circulation forms the first or the central compartment. The drug distribution to other tissues, such as muscles, bones and adipose tissues, is slower. These tissues can be grouped and referred to as the second compartment, also known as peripheral or the tissue compartment. For such drugs, the distribution equilibrium between the two compartments can take several minutes to hours to establish. Therefore, it requires the fitting of plasma concentration–time profile data into appropriate models for accurate estimation of pharmacokinetic parameters that could enable clinically relevant predictions of the dosage regimens. This is shown in Figure 2.13.

      Advanced in silico tools that can also predict drug absorption, metabolism, distribution and elimination in the body using inputs on physicochemical properties and ADME parameters and they are described in detail in Chapter 12.

Figure 2.12 One‐compartmental pharmacokinetic model, distribution equilibrium is achieved instantaneously.

Figure 2.13 Two‐compartmental pharmacokinetic model, distribution equilibrium is slow and takes time.

2.14 Concept of Linearity in Pharmacokinetics

For drugs that follow the first‐order kinetics, the pharmacokinetic parameters such as the plasma concentration at the steady state (C_ss) and the area under the curve (AUC) of a plasma concentration–time profile is linearly related to the administered dose. An increase in the dose, therefore, can result in a linear increase in the C_ss or the AUC (Figure 2.14). This linear relationship helps in simple dosage adjustment to achieve desired blood concentrations in the body.

Often for some drugs, one of the pharmacokinetic processes, i.e., t_½, k, V, Cl_, is not governed by the simple first‐order kinetics, instead it follows non‐linear pharmacokinetics. This is when one of the absorption, distribution, metabolism or excretion processes in the body are saturable on increasing the dose. Most drugs still follow first‐order pharmacokinetics in practice as the saturation in ADME processes is attained beyond clinical dose ranges. However, this can be a problem for some drugs where saturation is observed at a clinically relevant dose, for instance, phenytoin (Figure 2.15). This non‐linear behaviour in phenytoin pharmacokinetics is explained by the saturable hepatic metabolism of the drug. The pharmacokinetics of such drugs can be explained by the Michaelis–Menten model which can be used to calculate dosages required to achieve a desired steady state for a patient.

The saturable processes in drug distribution, for instance, plasma protein binding, can also lead to non‐linear pharmacokinetics for certain drugs. For instance, the volume of distribution of disopyramide increases with the dose due to increased free fraction of the drug once plasma protein binding sites are saturated at higher dosages. For drugs that are actively secreted into the renal tubule by active transport, for instance, dicloxacillin, the renal clearance decreases when transport proteins at the renal tubules are saturated on increasing the dose. The decreased clearance leads to disproportional increase in circulatory concentration of the drug when the dose is increased.

Figure 2.14 The linear relationship of the administered dose with the area‐under‐the‐curve (AUC) and plasma concentration of a drug. Increase in the dose proportionally increases the steady‐state concentration and the AUC.

Figure 2.15 Illustration showing non‐linear increase in steady state concentration of phenytoin on increasing the dose.

      Dose‐dependent saturation in drug absorption can also be responsible for the non‐linear pharmacokinetics for some drugs. For example, amoxicillin relies on transporters in the gut for its absorption (influx or active transport) that can be saturated on increasing the dose. Therefore, drug absorption does not increase proportionally on increasing the dose from a point when absorption transporters are saturated. The drugs exhibiting saturable pharmacokinetics are often prone to more drug–drug or drug–food interactions when co‐administered drug or food competes for the similar molecular pathway involved in its absorption, distribution, metabolism or elimination. Some excipients and formulation strategies can manipulate this interaction and can affect drug’s binding to the transport proteins or enzymes at the gut, liver or kidney and therefore can manipulate drug’s pharmacokinetics. The underpinning biopharmaceutical principles are therefore key considerations in the dosage form design.

2.15 Conclusions

Pharmacokinetic studies are useful to study the absorption, metabolism, distribution and elimination of drugs. For biopharmaceutics, they are used predominantly to better