No conclusive studies
Fig. 6.11. Pharmacogenetics & Pharmacogenomics
Source: Influences on Pharmacologic Responses. http://medicine.iupui.edu/flockhardt/
achieve the safe and effective use of the drug. Pharmacogenetics and pharmacogenomics are the sciences of understanding the correlation between an individual patient's genetic makeup (genotype) and their response to drug treatment. They already have influenced therapeutics. For a drug that is primarily metabolized by CYP2D6, approximately 7% of Caucasians will not be able to metabolize the drug, but the percentage for other racial populations is generally far lower. Similar information is known for other pathways, prominently, CYP2C19 and ^-acetyl transferase. For example, codeine is metabolized to its active molecule, and about 10% of the population are rapid metabolizers and only need a much smaller dose for the same pharmacodynamic outcome. Omeprazole, used to treat peptic ulcers, is poorly metabolized related to SNPs in the CYP2C19 liver enzyme in 2.5-6% of Caucasians and 15-23% of Asians. For thiopurine, an antimetabolite used in cancer chemotherapy, the dose is 1/10 for the poor metabo-lizers, which constitute about 10% of patients related to SNPs in the ^-acetyl transferase (phase II) liver enzyme [8, 9].
Genetic polymorphism is almost predominantly associated with drug metabolism and transporters; renal excretion of drugs does not appear to show genetic polymorphism. Drugs that are predominantly excreted unchanged tend to show much less inter-individual variability in disposition kinetics than extensively metabolized ones. Drug targets (receptors, enzymes, and signal transduction proteins) can have genetic variations and different drug sensitivities (e.g., ACE [angiotensin converting enzyme inhibitors], dopamine 1, 2, and 3, glycoprotein Ilia, and beta adrenergic receptors [BAR]). For BAR and the adrenergic bronchodilators, a fivefold difference in forced expiratory volume is possible because of SNPs [8, 9]. Some drugs work well in some patient populations and not as well in others. Studying the genetic basis of patient response to therapeutics allows drug developers to more effectively design therapeutic treatments. Characterization of genetic polymorphism can (1) improve candidate drug selection, (2) aid in developing new sets of biomarkers to eventually minimize animal studies, (3) help in predicting responders to a drug for enhancing desired effects and minimizing undesired serious side effects, (4) help to rationalize drug dosing, (5) improve patient selection process in studies, (6) reduce variability in drug responses in a study by excluding outliers in drug metabolism, and (7) reduce the number of subjects needed for establishing efficacy helping accelerate drug approval. These features will move from current empirical process to hypothesis-driven mechanism-based process, and thus lower cost and speed up the drug development process. However, the routine use of PG is not yet current medical practice, costs of genotyping adds to health care costs, diagnostic labs need to be better set up for this testing, PG tests need clinical validation, and legal ramifications of genetic information, its availability and use, remain a dilemma. In the field of oncology, genetic testing for responders has been encouraged as in the case of using HER-2 protein overexpression for identifying Herceptin responders.
Several definitions warrant attention on this subject.
• Pharmacogenetics: Study of hereditary variations in drug response.
• Genotype: The fundamental assortment of genes of an individual, the blueprint. Gene typing is a relatively new technique that involves the identification of genes whose expression results in a particular phenotype, such as rapid metabolites and poor metabolizers.
• Phenotype: Outward characteristic expression of an individual. Phenotyping is the expression of a genotype and usually involves ingestion of a test compound followed by serial blood or urine analysis.
• Genetic polymorphism: Defines monogenic traits that exist in the normal population in at least two phenotypes, neither of which is rare (less than 1%).
• Allele: One of two or more different genes containing a specific inheritable characteristic that occupy corresponding positions (loci) on paired chromosome. Dominant allele is expressed and recessive is not expressed.
Population-based PK/PD modeling is conducted to pool several studies with different sampling schemes (rich or sparse) and dose regimens and to describe the typical PK/PD behavior or central tendency of a population of interest. In Fig. 6.12, separate pieces of information (rich PK data, sparse PK data, efficacy data, and safety data, as well as covariate data) are combined into a pooled "mixed data set" for a population. Population-based modeling can produce unbiased estimates of PK or PD parameters, inter-individual variability, inter-occasional variability, as well as random residual variability, and can evaluate the effects of patient demographics, disease conditions, and concomitant medications on the PK/PD of the drug. Population approach allows sample numbers per subject and sample times varying from patient to patient, which fits better to the routine clinical practice or large phase III clinical trials and therefore makes it easier to obtain PK/PD information in the target patient population. Mixed effect modeling is the most commonly applied population-based approach, and
it is well established. It is a fundamental tool to characterize the exposure-response relationship and help select the dosage regimen in phase III trials and labeling.
In order to determine an appropriate dose, it is necessary to establish a range of concentrations from minimally to maximally efficacious with tolerable toxicity (minimal effective concentration, MEC, and maximal safe concentration, MSC, or maximal tolerable concentration, MTC, respectively). This range of concentrations, or therapeutic window, usually is determined from a concentration-time curve and a dose-response curve generated from a population of patients who have been examined closely for therapeutic and toxic effects (Fig. 6.13). The graphs also may be used to determine the therapeutic index (TI), comparing the response versus plasma concentration curves for efficacy and toxicity on the same graph at a 50% response rate (EC50). This useful measure of drug toxicity is calculated by dividing the 50% value from the toxicity curve by the 50% value of the efficacy curve. For example, in this slide, the TI is 6,500 ng/mL divided by 1,000 ng/mL, respectively, or 6.5, which is quite good for a TI. Because these curves are generated from population data, the values may not be applicable for all individuals.
One of the most important goals of PK/PD studies in drug development is to guide the determination of therapeutic dosage regimens in the clinical trials and for labeling of an NCE. To realize this goal, a number of clinical studies are required to be conducted systematically from maximal tolerated dose study (MTD) in phase I, dose ranging study in phase II, and large-scale efficacy and safety studies in phase III. In addition, PK/PD studies are often conducted in special populations for deriving dosage regimen adjustments for these patients. Drug-drug interaction or other interaction studies are also commonly conducted to guide the dosage for special conditions. An appropriate therapeutic dosage regimen is basically derived from the kinds of information
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