15.6: Pharmacokinetic–Pharmacodynamic Relationship: Problems

The empirical approach to drug therapy optimization relies on correlating pharmacological response with administered dosage. Such an approach can be costly, time-consuming, and often yields poor correlation due to variables like formulation factors and drug elimination characteristics. A more precise approach correlates response with plasma drug concentration or the amount of drug in the body, rather than dosage. This is achieved through pharmacokinetic-pharmacodynamic (PK/PD) modeling, which posits that response is proportional to drug concentration at the site of action, mirrored by plasma drug concentration.

However, developing a PK/PD relationship comes with challenges:

1. Delay in Drug Distribution: Sites of action are typically in extravascular tissues, where drug equilibration can take time, causing a delay in response observation. For example, the anticoagulant effect of dicoumarol is an indirect measure of the drug effect, leading to long delays. In some cases, the therapeutic action outlasts the plasma drug concentration, as with reserpine.
2. Protein Binding: Correlating pharmacological response with unbound drug concentration in plasma would be ideal, but quantifying unbound drug is challenging. Variations in the degree of binding can obscure the relationship when based on total plasma drug concentration.
3. Active Metabolites: Some drugs produce active metabolites that can confuse the concentration-response relationship if based solely on parent drug concentration, such as imipramine, amitriptyline, and propranolol.
4. Tolerance: Chronic use of some drugs can lead to acquired tolerance, either pharmacokinetic (enhanced metabolism, like carbamazepine) or pharmacodynamic (diminished response, like nitroglycerine).
5. Racemates: Many drugs are administered as a racemic mixture of two optically active enantiomers, usually with one active isomer. A change in the active to inactive isomers ratio can lead to significant differences in pharmacological response.

In conclusion, while PK/PD modeling offers a more precise approach than empirical methods, it's not without its complexities. These challenges necessitate a comprehensive understanding of drug dynamics for effective application.