Optimizing clopidogrel dose response: a new clinical algorithm comprising CYP2C19 pharmacogenetics and drug interactions

Abstract

Purpose

Response to clopidogrel varies widely with nonresponse rates ranging from 4% to 30%. A reduced function of the gene variant of the CYP2C19 has been associated with lower drug metabolite levels, and hence diminished platelet inhibition. Drugs that alter CYP2C19 activity may also mimic genetic variants. The aim of the study is to investigate the cumulative effect of CYP2C19 gene polymorphisms and drug interactions that affects clopidogrel dosing, and apply it into a new clinical-pharmacogenetic algorithm that can be used by clinicians in optimizing clopidogrel-based treatment.

Method

Clopidogrel dose optimization was analyzed based on two main parameters that affect clopidogrel metabolite area under the curve: different CYP2C19 genotypes and concomitant drug intake. Clopidogrel adjusted dose was computed based on area under the curve ratios for different CYP2C19 genotypes when a drug interacting with CYP2C19 is added to clopidogrel treatment. A clinical-pharmacogenetic algorithm was developed based on whether clopidogrel shows 1) expected effect as per indication, 2) little or no effect, or 3) clinical features that patients experience and fit with clopidogrel adverse drug reactions.

Results

The study results show that all patients under clopidogrel treatment, whose genotypes are different from *1*1, and concomitantly taking other drugs metabolized by CYP2C19 require clopidogrel dose adjustment. To get a therapeutic effect and avoid adverse drug reactions, therapeutic dose of 75 mg clopidogrel, for example, should be lowered to 6 mg or increased to 215 mg in patients with different genotypes.

Conclusion

The implementation of clopidogrel new algorithm has the potential to maximize the benefit of clopidogrel pharmacological therapy. Clinicians would be able to personalize treatment to enhance efficacy and limit toxicity.

Keywords:

• pharmacogenetics
• genotype
• genetic testing
• individualized therapy

Acknowledgments

We would like to acknowledge the Lebanese American University for the financial support.

Disclosure

The authors report no conflicts of interest in this work.