Background: A major challenge for effective pharmacotherapy in pain management is to provide the
drug best suited to the patient’s innate characteristics.
Objective: The article illustrates pharmacogenetic principles to optimize treatments for patients and
increase the likelihood of pain relief without dependence. Genetic variances are particularly relevant to
opioid drugs used in pain control, and can now be harvested for predictive clinical decision support.
Study Design: Clinically actionable polymorphisms in CYP2D6 (cytochrome p450 2D6) and OPRM1
(μ1 opioid receptor), the most important gene coding, respectively, for a metabolizing enzyme and
receptor for opioids are reviewed, and functional effects described.
Methods: Risk of dysfunction is calculated from the frequency of the alleles with null function for
CYP2D6, and from the low function polymorphism for OPRM1. Integration of genetic variability was
performed for 9 combinatorial scenarios for CYP2D6 and OPRM1. Each combination was quantified
in frequency and classified for clinical impact. A rational and pharmacological basis for personalized
pain management based on pharmacokinetic and pharmacodynamic modeling is extracted from the
frequency of the combinations.
Results: Patients can be classified in 3 broad risk categories for opioid side effects and dependence.
Patients at high-risk with dysfunctional CYP2D6 or OPRM1 account for ~14% of the population and are
best managed with non-opioids. Patients at medium risk with subnormal CYP2D6 or OPRM1 account for
~48% of the population and can be managed with dose monitoring. Patients at low risk with functional
CYP2D6 and OPRM1 account for ~38% of the population and should be availed to opioid therapy.
Limitations: Heuristic clinical decision support considerations are not validated yet by deployment in
large clinical practices. Environmental modifiers such as other drugs and dietary supplements interact
with innate characteristics to modify the genetic predictions.
Conclusion: Through clinical decision support interpreting the genotyping data, drug choices and
doses can then be tailored to provide safe and effective therapy for individual patients. This precision
affords personalized medicine to be practiced in pain treatment. Genetic factors could help determine
why some patients seem more vulnerable than others to opioid side effects and dependence.
Key words: Pain management, opioids, CYP2D6, OPRM1, clinical decision support, pharmacokinetics,
pharmacodynamics, pharmacogenetics, combinatorial genotypes