**5. Pharmacogenetic developments**

216 Pharmacology

cost-effectiveness is very disease-specific, it is difficult, if not impossible, to compare the cost-effectiveness of different treatments for different diseases with each other and this comparability is valuable when making budget allocation decisions. For this reason, some authorities or health insurance companies require a cost-utility analysis. In a cost-utility analysis (CUA), the health gains acquired by a new treatment are expressed in Quality Adjusted Life Years (QALYs), which can be compared more easily with other treatments,

Several economic evaluations (such as CEAs and CUAs) have been performed for coumarin derivatives. The problem with these analyses is that no robust data on the effectiveness of genotyping are available yet; the large RCTs that can provide this data are still ongoing (van Schie et al., 2009; French et al., 2010). This current lack of evidence results in a wide variability in cost-effectiveness ratios among the studies that have been done, ranging from dominance (where use of genotyping reduces costs and increases health) to a very high incremental cost of \$347,000 per QALY gained (Verhoef et al., 2010). The costs of genotyping are also not clear yet. In literature, the estimated cost of genotyping for *CYP2C9* ranges from \$67 to \$350 and the estimated cost of genotyping both *CYP2C9* and *VKORC1* ranges from \$175 to \$575. Recently, a Point-Of-Care Test (POCT) for genotyping *CYP2C9* and *VKORC1*  has been developed. With this test, the patient's genotype can be determined in the physician's office within 2 hours and this is estimated to cost less than \$50 per patient for both *CYP2C9* and *VKORC1* (Howard et al., 2011). The costs of genotyping are expected to decrease even further, with increased usage. This will also influence the chance that

Decisions about whether or not to implement pharmacogenetic testing in clinical practice will differ among different countries. This difference can be caused by several factors. Firstly, the amount of money society is willing to pay varies among different countries. For example, this 'willingness to pay' is approximately \$50,000 per QALY gained in the US or £20,000–30,000 (approximately \$33,000-50,000) per QALY gained in the UK (National Institute for Health and Clinical Excellence [NICE], 2008). Secondly, the costs, not only of genotyping but also of the consequences like bleeding events, are not identical in all countries. Next to this, the effectiveness of genotyping can also be higher in one country than in another. This is for example possibly the case with coumarin derivatives. In some countries the standard care is already of very high quality, with specialized anticoagulation clinics to monitor the effect of the drug, while in other countries this is not the case and there

As mentioned before, the use of pharmacogenetics in treatment with a certain drug can only be recommended if information on effectiveness and costs of genotyping is available, although it is not clear what level of evidence is needed for a valid decision. Obviously, it is impossible to obtain perfect evidence. Therefore, value of information (VOI) analyses could be performed to establish the cost–effectiveness of further research on the efficiency of the strategy. If the costs of performing this research are greater than the benefits of the additional information, then it would not be worthwhile to conduct this research (Sculpher & Claxton, 2005). The parameters that have the greatest influence on the uncertainty regarding the cost–effectiveness of genotyping should be the main focus of future studies in this area. The costs of conducting these studies should also be considered. However, this will also depend upon the regulatory

also in other diseases, than the cost per adverse event avoided.

pharmacogenetic testing is cost-effective.

is still room for further improvement.

environment, and VOI forms only a part of the picture.

Until now, only the most obvious gene-drug interactions have been detected since these are least complicated to detect when researchers are looking for causal SNPs. However, rare SNPs with large effects might as well be of importance, but it is a challenge to find large numbers of cases that are required to obtain enough power in pharmacogenetic studies when looking at smaller effects or lower allele frequencies (Daly, 2010). A trend is observed that larger studies are being performed and meta-analyses are carried out to investigate these less frequent genetic profiles. Several techniques are further developed and might lead to new insights in the pharmacogenetic research field. We will discuss them in this paragraph.

#### **5.1 Candidate-gene studies**

This type of study investigates the association between drug response and previously identified candidate genes. These candidate genes might play a relevant role in the pharmacokinetics or pharmacodynamics of the drug and might therefore be, for example, the metabolizing enzyme or the target protein. An example is the use of candidate gene approaches for the understanding of the overall drug response to coumarins. (Daly, 2010). In 1992, Rettie *et al*. indicated *CYP2C9* as main metabolizing enzyme of warfarin (Rettie et al., 1992). A few years later, Furuya *et al.* first reported that SNPs in this gene affect the stable coumarin maintenance dose (Furuya et al., 1995). A decade later, VKORC1 was identified as the target enzyme of the coumarins (Rost et al., 2004; Li et al., 2004) and studies confirming the association between *VKORC1* genotypes and stable coumarin maintenance dose followed. Another example is the role of the *CYP2C19* genotype on the clopidogrel (Hulot, 2006) therapy response and how the treatment with tamoxifen is influenced by the *CYP2D6* genotype (Hoskins, 2009).

#### **5.2 Genome-wide association studies**

Since 2007, genonome wide association (GWA) studies have become more frequently applied in the pharmacogenetics field. This resulted in novel identified associations between drug response and variations in DNA (Daly, 2010). In CVD, GWA studies resulted in confirmation of the already available knowledge, rather than in newly identified interactions. For clopidogrel, the influence of *CYP2C19* was confirmed (Schuldiner et al., 2009) and for statin induced muscle symptoms an association with *SLCO1B1* was found (SEARCH Collaborative Group, 2008) in a GWA study. In a GWA study on acenocoumarol maintenance dose, an additional effect was found for polymorphisms in *CYP4F2* and *CYP2C18* (Teichert et al., 2009b). These GWA studies led to more knowledge about several drug-gene interactions, but the causality of the relationship is not always clear in these studies. Another difficulty with this type of analyses is the need of large patient numbers because of the correction for multiple testing.

#### **5.3 Sequencing**

DNA sequencing is the determination of the nucleotide bases in DNA. In contrast to GWA studies, where tag SNPs are used to cover as much of the variation within the gene as possible, this technique will determine the exact order of nucleotides in DNA. Instead of tag SNPs that are usually markers for the causal SNP - and thereby introduce noise because they

Future of Pharmacogenetics in Cardiovascular Diseases 219

investigate less frequent genetic profiles. Analysis of GWA studies and sequencing is

In the field of oncology, pharmacogenetic testing already is part of daily practice. We expect

Anderson, C., Biffi, A., Greenberg, S. & Rosand, J. (2010). Personalized approaches to clopidogrel therapy: are we there yet? *Stroke* 41, 12, (Dec 2010), 2997-3002. Ansell, J., Hirsh, J., Hylek, E., Jacobson, A., Crowther, M. & Palareti, G. (2008).

Arnett, D. & Claas, S. (2009). Pharmacogenetics of antihypertensive treatment: detailing disciplinary dissonance. *Pharmacogenomics* 10, 8, (Aug 2009), 1295-1307. Collet, J. & O'Connor, S. (2011). Clinical effects and outcomes with new P2Y12 inhibitors in

Crespin, D., Federspiel, J., Biddle, A., Jonas, D. & Rossi, J. (2011). Ticagrelor versus

Custodio das Dores, S., Booth, S., Martini, L., de Carvalho Gouvea, V., Padovani, C., de

Daly, A. (2010). Genome-wide association studies in pharmacogenomics. *Nat. Rev. Genet.* 11,

European Medicines Agency [EMA]. (2006). Guideline on pharmacogenetics briefing

European Medicines Agency [EMA]. (2007). ICH Topic E15 Definitions for genomic

Food and Drug Administration [FDA]. (2007). Transcript of the FDA press conference on

Food and Drug Administration [FDA]. (2008). Guidance for Industry E15 Definitions for

French, B., Joo, J., Geller, N., Kimmel, S., Rosenberg, Y., Anderson, J., Gage, B., Johnson, J.,

Furuya, H., Fernandez-Salguero, P., Gregory, W., Taber, H., Steward, A,, Gonzalez, F. &

Goodsaid, F. (2006). 42nd annual meeting; Joint USFDA-EU Pharmacogenomic Initiatives.

Pharmacology and management of the vitamin K antagonists: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines (8th Edition). *Chest* 

genotype-driven antiplatelet therapy for secondary prevention after acute coronary syndrome: a cost-effectiveness analysis. *Value Health.* 14, 4, (Jun 2011), 483-491

Abreu Maffei, F., Campana, A. & Rupp de Paiva, S. (2007). Relationship between diet and anticoagulant response to warfarin: a factor analysis. *Eur J Nutr* 46, 3, (Apr

biomarkers, pharmacogenomics, pharmacogenetics, genomic data and sample

Genomic Biomarkers, Pharmacogenomics, Pharmacogenetics, Genomic Data and

Ellenberg, J. & COAG investigators. (2010). Statistical design of personalized medicine interventions: the Clarification of Optimal Anticoagulation through

Idle, J. (1995) Genetic polymorphism of CYP2C9 and its effect on warfarin maintenance dose requirement in patients undergoing anticoagulation therapy.

challenging due to the enormous amount of data obtained by this technique.

133, 6 suppl, (Jun 2008), 160S-198S.

ACS. *Fundam. Clin. Pharmacol.* (Sep 2011).

**7. References** 

(2011).

2007), 147-154.

meetings.

4, (Apr 2010), 241-246.

coding categories.

Warfarin held on 16 August.

Sample Coding Categories

Genetics (COAG) trial. *Trials* 11, (Nov 2010), 108.

*Pharmacogenetics*. 5(6), (dec 1995), 389-392.

that pharmacogenetic testing will also be implemented in CVD in the near future.

are not always in complete linkage disequilibrium - the causal SNPs can be identified. Therefore, this technique might provide new insights in associations between drug response and pharmacogenetic parameters that are not observed when performing a candidate-gene study or a GWA study. It is possible to sequence a whole genome or whole exome. In addition, there is an option 'targeted sequencing' which means that a candidate gene is sequenced. This technique is relatively new and gaining interest in the last few years, but the same issues (i.e. causality of the relationship is not always clear and large patient numbers are needed) as with the GWA studies occur with sequencing. This warrants that the functionality of the SNP should be studied (Sadee, 2011).

#### **5.4 Point-of-care testing**

As discussed earlier, point-of-care tests can be used as mobile genotyping instruments in different settings, including the pharmacy, anticoagulation clinic and physician's office. It avoids the need to collect multiple samples and the genotyping results are available within 2 hours. This technique might be used to genotype the patient before the start of the therapy. However, the applicability of a point-of-care test may be different from centralized laboratory testing because of different sensitivity and specificity parameters. Also, it is not attractive to use such a test in research where large patient groups are needed to find a pharmacogenetic interaction, since that would be very labor intensive.

#### **6. Conclusion**

There is considerable potential for pharmacogenetic based drug dosing in CVD, but at the moment, these are not widely implemented in clinical practice. Convincing evidence was found for several CVD drugs. Carriers of a variant allele of the *SLCO1B1* gene could be treated with a *SLCO1B1* independent statin to increase the safety of the treatment. Clopidogrel is less metabolized into its active form by patients carrying a variant allele of *CYP2C19*, resulting in a less effective therapy. Information about the patient's *VKORC1* and *CYP2C9* genotype could be used when defining the appropriate dose during the anticoagulation therapy with coumarins to enhance the efficacy and increase the safety of the treatment. However, implementation of this knowledge is challenging and depends on multiple factors. First, clinical trials are needed to provide evidence for and enhance the implementation of pharmacogenetic testing. However, it is not feasible to perform a clinical trial for every newly found gene-drug interaction. Therefore it is desirable to develop guidelines to which observational studies should apply before implementing the gene-drug interaction in clinical practice. Secondly, multiple parties are involved, such as patients, health care professionals, regulatory authorities, health insurance companies and researchers. We discussed the different parties involved and their rationales. Thirdly, several facilities should be in place before pharmacogenetic testing can be implemented in clinical practice, such as availability of genotyping results and authority guidelines. Lastly, before it comes to implementation, the cost-effectiveness of the pharmacogenetic approach should be investigated. Health insurance companies may require proof of cost-effectiveness before considering reimbursement and therefore implementation of pharmacogenetic testing.

For the coming years, researchers will continue to develop the different genotyping methods. Larger studies will be performed and meta-analyses will be carried out to investigate less frequent genetic profiles. Analysis of GWA studies and sequencing is challenging due to the enormous amount of data obtained by this technique.

In the field of oncology, pharmacogenetic testing already is part of daily practice. We expect that pharmacogenetic testing will also be implemented in CVD in the near future.

#### **7. References**

218 Pharmacology

are not always in complete linkage disequilibrium - the causal SNPs can be identified. Therefore, this technique might provide new insights in associations between drug response and pharmacogenetic parameters that are not observed when performing a candidate-gene study or a GWA study. It is possible to sequence a whole genome or whole exome. In addition, there is an option 'targeted sequencing' which means that a candidate gene is sequenced. This technique is relatively new and gaining interest in the last few years, but the same issues (i.e. causality of the relationship is not always clear and large patient numbers are needed) as with the GWA studies occur with sequencing. This warrants that

As discussed earlier, point-of-care tests can be used as mobile genotyping instruments in different settings, including the pharmacy, anticoagulation clinic and physician's office. It avoids the need to collect multiple samples and the genotyping results are available within 2 hours. This technique might be used to genotype the patient before the start of the therapy. However, the applicability of a point-of-care test may be different from centralized laboratory testing because of different sensitivity and specificity parameters. Also, it is not attractive to use such a test in research where large patient groups are needed to find a

There is considerable potential for pharmacogenetic based drug dosing in CVD, but at the moment, these are not widely implemented in clinical practice. Convincing evidence was found for several CVD drugs. Carriers of a variant allele of the *SLCO1B1* gene could be treated with a *SLCO1B1* independent statin to increase the safety of the treatment. Clopidogrel is less metabolized into its active form by patients carrying a variant allele of *CYP2C19*, resulting in a less effective therapy. Information about the patient's *VKORC1* and *CYP2C9* genotype could be used when defining the appropriate dose during the anticoagulation therapy with coumarins to enhance the efficacy and increase the safety of the treatment. However, implementation of this knowledge is challenging and depends on multiple factors. First, clinical trials are needed to provide evidence for and enhance the implementation of pharmacogenetic testing. However, it is not feasible to perform a clinical trial for every newly found gene-drug interaction. Therefore it is desirable to develop guidelines to which observational studies should apply before implementing the gene-drug interaction in clinical practice. Secondly, multiple parties are involved, such as patients, health care professionals, regulatory authorities, health insurance companies and researchers. We discussed the different parties involved and their rationales. Thirdly, several facilities should be in place before pharmacogenetic testing can be implemented in clinical practice, such as availability of genotyping results and authority guidelines. Lastly, before it comes to implementation, the cost-effectiveness of the pharmacogenetic approach should be investigated. Health insurance companies may require proof of cost-effectiveness before

considering reimbursement and therefore implementation of pharmacogenetic testing.

For the coming years, researchers will continue to develop the different genotyping methods. Larger studies will be performed and meta-analyses will be carried out to

the functionality of the SNP should be studied (Sadee, 2011).

pharmacogenetic interaction, since that would be very labor intensive.

**5.4 Point-of-care testing** 

**6. Conclusion** 


Future of Pharmacogenetics in Cardiovascular Diseases 221

Peters, B., Klungel, O., Visseren, F., de Boer, A. & Maitland-van der Zee, A. (2009).

Peters, B. (2010). Thesis: "Methodological approaches to the pharmacogenomics of statins" Rettie A., Korzekwa, K., Kunze, K. , Lawrence, R. Eddy, A., Aoyama, T., Gelboin, J.,

Romaine, S., Bailey, K., Hall, A. & Balmforth, A. (2010). The influence of SLCO1B1

Rost, S., Fregin, A., Ivaskevicius, V., Conzelmann, E., Hörtnagel, K., Pelz, H., Lappegard, K.,

Sadee, W., (2011). Pharmacogenomic biomarkers: validation needed for both the molecular genetic mechanism and clinical effect. *Pharmacogenomics*, 12, 5, (May 2011), 675-80. Schalekamp, T., Oosterhof, M., van Meegen, E., van Der Meer, F., Conemans, J., Hermans,

Schalekamp, T. & de Boer, A. (2010). Pharmacogenetics of oral anticoagulant therapy. *Curr* 

van Schie, R., Wadelius, M., Kamali, F., Daly, A., Manolopoulos, V., de Boer, A., Barallon, R.,

(EU-PACT) trial design. *Pharmacogenomics* 10, 10, (Oct 2009), 1687-1695. van Schie, R., Wessels, J., le Cessie, S., de Boer, A., Schalekamp, T., van der Meer, F.,

Sculpher, M. & Claxton, K. (2005). Establishing the cost-effectiveness of new

SEARCH Collaborative Group. (2008). SLCO1B1 variants and statin-induced myopathy--a

Shuldiner, A., O'Connell, J., Bliden, K., Gandhi, A., Ryan, K., Horenstein, R., Damcott, C.,

pharmacogenetic data. *Eur Heart J*. 32,15, (Aug 2011), 1909-1917.

genomewide study. *N. Engl. J. Med.* 359, 8, (Aug 2008), 789-799.

evidence? *Value Health,* 8, 4, (Jul 2005), 433-446.

myopathy. *Genome Med.* 1, 1, (Dec 2009), 120.

drug interactions. *Chem. Res. Toxicol.* 5, 54-59.

factor deficiency type 2. *Nature*, 427, 537-541.

451-457.

10, 1, (Feb 2010), 1-11.

76, 5, (Nov 2004), 409-417.

8, (Aug 2009), 849-857.

*Pharm Des* 16, 2, (2010) 187-203.

predominantly concern antibacterial drugs. *Clin Pharmacol Ther* 69, 6, (Jun 2001),

Pharmacogenomic insights into treatment and management of statin-induced

Gonzalez, F. & Trager, W. (1992) Hydroxylation of warfarin by human cDNAexpressed cytochrome P-450: A role for P-4502C9 in the etiology of (S)-warfarin-

(OATP1B1) gene polymorphisms on response to statin therapy. *Pharmacogenomics J.* 

Seifried, E., Scharrer, E., Tuddenham, E., Müller, C., Strom, T. & Oldenburg, J. (2004). Mutations in VKORC1 cause warfarin resistance and multiple coagulation

M., Meijerman, I. & de Boer, A. (2004). Effects of cytochrome P450 2C9 polymorphisms on phenprocoumon anticoagulation status. *Clin. Pharmacol. Ther.*

Verhoef, T., Kirchheiner, J., Haschke-Becher, E., Briz, M., Rosendaal, F., Redekop, W., Pirmohamed, M. & van der Zee, A. (2009) Genotype-guided dosing of coumarin derivatives: the European pharmacogenetics of anticoagulant therapy

Verhoef, T., van Meegen, E., Rosendaal, F. & Maitland-van der Zee, A., for the EU-PACT Study Group (2011) Loading and maintenance dose algorithms for phenprocoumon and acenocoumarol using patient characteristics and

pharmaceuticals under conditions of uncertainty--when is there sufficient

Pakyz, R., Tantry, U., Gibson, Q., Pollin, T., Post, W., Parsa, A., Mitchel, B., Faraday, N., Herzog, W. & Gurbel, P. (2009). Association of cytochrome P450 2C19 genotype with the antiplatelet effect and clinical efficacy of clopidogrel therapy. *JAMA*, 302,


Harmsze, A., van Werkum, J., Ten Berg, J., Zwart, B., Bouman, H., Breet, N., van 't Hof, A.,

Harmsze, A., van Werkum, J., Bouman, H., Ruven,H., Breet, N., Ten Berg, J., Hackeng, C.,

Howard, R., Leathart, J., French, D., Krishan, E., Kohnke. H., Wadelius, M., van Schie, R.,

Hoskins, J., Carey, L. & McLeod, H. (2009). CYP2D6 and tamoxifen: DNA matters in breast

Huang, S. (2008). Warfarin Pharmacogenetic Testing is Now Ready for Prime Time, AACC

Hulot, J., Bura, A., Villard, E., Azizi, M., Remones, V., Goyenvalle, C., Aiach, M., Lechat, P.

Jakubowski, J., Riesmeyer, J., Close, S., Leishman, A. & Erlinge, D. (2011). TRITON and Beyond: New Insights into the Profile of Prasugrel. *Cardiovasc. Ther.* (Feb 2011). James, A., Britt, R., Raskino, C. & Thompson, S. (1992). Factors affecting the maintenance

Law, M. & Rudnicka, A. (2006). Statin safety: a systematic review. *Am. J. Cardiol.* 97, 8A, (Apr

Levy, H. & Young, J. (2008). Perspectives from the clinic: will the average physician embrace personalized medicine? *Clin. Pharmacol. Ther.* 83, 3, (Mar 2008), 492-493. Li, T., Chang, C., Jin, D., Lin, P., Khvorova, A., & Stafford, D. (2004). Identification of the

Niemi, M., Pasanen, M. & Neuvonen, P. (2006). SLCO1B1 polymorphism and sex affect the

Niemi, M. (2007). Role of OATP transporters in the disposition of drugs. *Pharmacogenomics* 8,

Pasanen, M., Neuvonen, M., Neuvonen, P. & Niemi, M. (2006). SLCO1B1 polymorphism

Pearson, T., Laurora, I., Chu, H. & Kafonek, S. (2000). The lipid treatment assessment

Penning-van Beest, F., van Meegen, E., Rosendaal, F. & Stricker, B. (2001). Drug interactions

cholesterol goals. *Arch. Intern. Med.* 160, 4, (Feb 2000), 459-467.

pharmacokinetics of pravastatin but not fluvastatin. *Clin. Pharmacol. Ther.* 80, 4,

markedly affects the pharmacokinetics of simvastatin acid. *Pharmacogenet Genomics* 

project (L-TAP): a multicenter survey to evaluate the percentages of dyslipidemic patients receiving lipid-lowering therapy and achieving low-density lipoprotein

as a cause of overanticoagulation on phenprocoumon or acenocoumarol

implantation. *Pharmacogenet Genomics* 20, 1, (Jan 2010), 18-25.

*Eur. Heart J.* 31, 24, (Dec 2010) 3046-3053.

probes. *Clin. Chim. Acta,* (Jul 2011).

2244-2247

2006), 52C-60C.

(Oct 2006), 356-366.

7, (Jul 2007), 787-802.

16, 12 (Dec 2006), 873-879.

cancer. *Nature Rev. Cancer*, 9, 576-586.

Annual Meeting, Washington DC, July 28, 2008.

dose of warfarin. *J Clin Pathol* 45, 8, (Aug 1992), 704-6.

gene for vitamin K epoxide reductase. *Nature*, 427, 541-544.

Nice. (2008). Guide to the methods of technology appraisal.

Ruven, H., Hackeng, C., Klungel, O., de Boer, A. & Deneer, V. (2010a). CYP2C19\*2 and CYP2C9\*3 alleles are associated with stent thrombosis: a case-control study.

Tjoeng, M., Klungel, O., de Boer, A. & Deneer, V. (2010b). Besides CYP2C19\*2, the variant allele CYP2C9\*3 is associated with higher on-clopidogrel platelet reactivity in patients on dual antiplatelet therapy undergoing elective coronary stent

Verhoef, T., Maitland-van der Zee, A., Daly, A. & Barallon, R. (2011). Genotyping for CYP2C9 and VKORC1 alleles by a novel point of care assay with HyBeacon(R)

& Gaussem, P. (2006) Cytochrome P450 2C19 loss-of-function polymorphism is a major determinant of clopidogrel responsiveness in healthy subjects. *Blood* 108, predominantly concern antibacterial drugs. *Clin Pharmacol Ther* 69, 6, (Jun 2001), 451-457.


**1. Introduction** 

Japanese patients is warranted.

CYP2C19 genotypes.

**11** 

*Japan* 

**Warfarin Enantiomers** 

Yumiko Akamine and Tsukasa Uno

*University of the Ryukyus, Okinawa,* 

**Pharmacokinetics by CYP2C19** 

*Department of Hospital Pharmacy, Faculty of Medicine,* 

Warfarin, a coumarin vitamin K antagonist, is the most widely prescribed anticoagulant agent for the control and prevention of atrial fibrillation-related thrombus formation, stroke, and arterial and venous thrombembolism (Hirsh J et al., 1998). The recommend warfarin therapy consists of the lowest dose required to maintain the target international normalized ratio (INR) because of the drug's narrow therapeutic window. However, there can be a 20 fold difference in the dose required by patients to achieve this target INR. It is well known that cytochrome P450 (CYP), predominantly CYP2C9, activity is an important source of variability (Kaminsky LS and Zhang ZY, 1997) . Additionally, Rieder et al. (2005) have reported that an effect of the vitamin K epooxide reductase complex subunit 1 gene (VKORC1) has an important role on dose requirement. However, Takahashi et al. (2006) shows that Caucasians and African-Americans have high frequencies of VKORC1 and CYP2C9 genotypes, which lead to either reduced metabolic activity or attenuated sensitivity to warfarin, whereas only about 20% of the Japanese population possesses these genotypes. Therefore, further study of sources of variability in warfarin dose requirements among

Warfarin is administered clinically as a racemic mixture of the *S*- and *R*-enantiomer (Fig. 1), however *S*-warfarin is 3–5 times more potent than *R*-enantiomer. Both enantiomers are extensively metabolized in the liver (Chan E et al., 1994; Takahashi H and Echizen H, 2001). The more potent *S*-enantiomer is metabolized mainly to *S*-7-hydroxywarfarin by CYP2C9, whereas *R*-enantiomer is metabolized to *R*-6, *R*-7, *R*-8 and *R*-10-hydroxywarfarin by several CYPs involving CYP1A2, CYP3A4 and CYP2C19 (Kaminsky LS and Zhang ZY, 1997). Among these CYPs, it has been shown that both CYP2C9 and CYP2C19 are subject to single nucleotide polymorphisms (SNPs). In Japanese, because the heterozygous frequency of the CYP2C9 Leu359 allele is 3.5% (Takahashi H et al., 1998) and the frequency of the defective CYP2C19 alleles is 18.8% (Kubota T et al., 1996), the latter may be more closely associated with the clinical effect of warfarin. In this chapter, we therefore focus on the effect of CYP2C19 genotypes on the pharmacokinetics and pharmacodynamics of warfarin enantiomers. In addition, we characterize the impact of omeprazole, a CYP2C19 inhibitor, on the stereoselective pharmacokinetics and pharmacodynamics of warfarin between

