Pharmacogenetics in Pain Management

Variation in response to pain medication may be explained or predicted by the patient’s genetics. How a patient handles a drug often depends on genetic differences that affect pharmacokinetics (i.e.what the body does to the drug, such as metabolic activation or inactivation of drugs), or pharmacodynamics (i.e. the response of the body to the drug, whether positive or negative). Variation in drug handling may also be dose-related, or not related to dose.

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One of the best characterized genes involved in the pharmacokinetics of drugs is cytochrome P450 2D6
. Codeine, hydrocodone and oxycodone are metabolized into active metabolites by the action of CYP2D6. Therefore, knowing the patient’s CYP2D6 genotype prior to initiation of drug may be useful. Many laboratories currently offer clinical testing to determine a patient’s CYP2D6 genotype. Tests are usually performed on blood, buccal swabs or saliva, and will indicate whether the patient is a normal metabolizer (also called "extensive metabolizer"), a poor metabolizer, an intermediate metabolizer (metabolizing at a rate between poor and normal metabolizers), or a rapid metabolizer. Adjustment in drug dosage may be indicated particularly for poor and rapid metabolizers.

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While genotype information may be useful for pre-therapeutic evaluation of drug selection and dose, drug-drug interactions and non-genetic factors are also important to consider. Therapeutic drug monitoring is a good way to evaluate the post-therapeutic phenotype, and can be used to optimize the pharmacological approach further.


The field of pharmacodynamics continues to evolve for pain management and for the selection of the best drug. While genetic factors are known to impact pharmacodynamics, genetic testing for pharmacodynamics is not routine. An example of a gene involved in pharmacodynamics of pain is the gene for mu-opioid receptor (OPRM1). OPRM1 is the primary binding site of action for many opioid drugs and for binding of beta-endorphins. Variants in this gene could be used to predict efficacy of opioid addiction treatment (naltrexone, an opioid antagonist used to treat abuse of opiates) or opioid sensitivity.

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