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Case Report

Pharmacogenomics and Drug-Induced Phenoconversion Informed Medication Safety Review in the Management of Pain Control and Quality of Life: A Case Report

1
Office of Translational Research and Residency Programs, Tabula Rasa HealthCare, Moorestown, NJ 08057, USA
2
Precision Pharmacotherapy Research & Development Institute, Tabula Rasa HealthCare, Orlando, FL 32827, USA
3
Faculty of Pharmacy, Université de Montréal, Montreal, QC H3T 1J4, Canada
4
VieCare Beaver, Program of All-Inclusive Care for the Elderly (PACE), Lutheran Senior Life, Aliquippa, PA 15001, USA
5
Research Center of Centre Hospitalier de l’Université de Montréal (CRCHUM), Montreal, QC H2X 0A9, Canada
*
Author to whom correspondence should be addressed.
J. Pers. Med. 2022, 12(6), 974; https://doi.org/10.3390/jpm12060974
Submission received: 20 May 2022 / Revised: 8 June 2022 / Accepted: 10 June 2022 / Published: 15 June 2022

Abstract

:
Utilizing pharmacogenomics (PGx) and integrating drug-induced phenoconversion to guide opioid therapies could improve the treatment response and decrease the occurrence of adverse drug events. Genetics contribute to the interindividual differences in opioid response. The purpose of this case report highlights the impact of a PGx-informed medication safety review, assisted by a clinical decision support system, in mitigating the drug–gene and drug–drug–gene interactions (DGI and DDGI, respectively) that increase the risk of an inadequate drug response and adverse drug events (ADEs). This case describes a 69-year-old female who was referred for PGx testing for uncontrolled chronic pain caused by osteoarthritis and neuropathy. The clinical pharmacist reviewed the PGx test results and medication regimen and identified several (DGIs and DDGIs, respectively) at Cytochrome P450 (CYP) 2C19 and CYP2D6. The recommendations were to: (1) switch tramadol to buprenorphine transdermal patch, an opioid with lower potential for ADEs, to mitigate a CYP2D6 DDGI; (2) gradually discontinue amitriptyline to alleviate the risk of anticholinergic side effects, ADEs, and multiple DDGIs; and (3) optimize the pregabalin. The provider and the patient agreed to implement these recommendations. Upon follow-up one month later, the patient reported an improved quality of life and pain control. Following the amitriptyline taper, the patient experienced tremors in the upper and lower extremities. When the perpetrator drug, omeprazole, was stopped, the metabolic capacity was no longer impeded; the patient experienced possible amitriptyline withdrawal symptoms due to the rapid withdrawal of amitriptyline, which was reinitiated and tapered off more slowly. This case report demonstrates a successful PGx-informed medication safety review that considered drug-induced phenoconversion and mitigated the risks of pharmacotherapy failure, ADEs, and opioid misuse.

Graphical Abstract

Jpm 12 00974 i001

1. Introduction

Chronic pain is a debilitating condition that is prevalent in older adults [1]. Pain management strategies generally begin with non-opioid medications, such as the non-steroidal anti-inflammatory drugs (NSAIDs), then progress to opioids for refractory pain [2]. Adjuvant therapies, such as anticonvulsants or tricyclic antidepressants (TCAs), are often used to specifically manage neuropathic pain [2]. The gene polymorphisms that encode for CYP isoenzymes can alter the drug plasma concentrations, safety, and efficacy of certain analgesic medications (e.g., NSAIDs, opioids, TCAs) [2]. For example, CYP2D6 is a highly polymorphic gene that codes for CYP2D6, a major enzyme that metabolizes several opioids (e.g., tramadol, codeine, hydrocodone, oxycodone) [3]. The decision to initiate opioids in older adults requires careful consideration due to the increased risk of side effects (e.g., sedation, constipation, physical dependence), as well as changes in the renal and hepatic function that affect the dosing for many of the opioids [1]. The PGx results can help pharmacists personalize the opioid therapies, to achieve optimal efficacy and/or minimize adverse drug events (ADEs) [2].
Polypharmacy may complicate the interpretation of the PGx results, especially when co-administered medications share the same metabolic pathway and affect the drug-induced phenoconversion [4]. Phenoconversion occurs when nongenetic factors, such as concomitant medications, age, and comorbidities, alter the genotype-predicted phenotype of drug-metabolizing enzymes [4]. Assessing for the drug-induced phenoconversion, as opposed to solely relying on genetic results, allows for a more accurate prediction of medication response and an optimization of patient outcomes [4]. The clinical decision support systems (CDSSs) can help to identify drug–drug interactions (DDIs), DGIs, DDGIs, and drug-induced phenoconversion [5]. The CDSS generates a Medication Risk Score (MRS) based on several factors, including the drug interactions [6]. The MRS is associated with health outcomes, including the overall risk of ADEs, falls, and hospitalization [7,8]. The objective is to present a case report with a complex polypharmacy drug regimen supporting the value of a pharmacist-led medication safety review, assisted by a CDSS that incorporates the PGx results and drug-induced phenoconversion.

2. Case Presentation

A 69-year-old female patient presented to her healthcare provider with a chief complaint of persistent, severe pain (average = 8, worst = 10), based on the numeric rating scale (NRS) and with an MRS classified as “very high.” The clinical pharmacist reviewed the patient’s medical history and assessed the appropriateness of her current medication regimen, which included tramadol for osteoarthritis and amitriptyline for neuropathic pain (Table 1). The patient scored a 12 on the health-related quality of life questionnaire (EuroQOL-5D; range: 5–15), which assesses health in five dimensions, revealing moderate mobility and self-care difficulties in addition to her extreme pain. A PGx test was proposed to help optimize the patient’s medication therapy. A DNA sample was collected via a buccal swab and was analyzed by a Clinical Laboratory Improvement Amendments-certified laboratory (OneOme, Minneapolis, MN, USA).
Upon review of the PGx results (Table 2) and the medication regimen (Table 3), the clinical pharmacist, aided by a CDSS (MedWise®), identified multiple DDGIs affecting the tramadol and perpetrated by the carvedilol, duloxetine, and hydroxyzine. Although the patient was a CYP2D6 normal metabolizer (NM), the plasma concentration of the tramadol’s active metabolite was likely to be lower than expected from the genetic results alone, due to the DDGIs. The drug-induced phenoconversion at CYP2D6 caused her to metabolize the tramadol as an intermediate metabolizer (IM), thereby decreasing the drug’s analgesic effects.
The clinical pharmacist identified the DDGIs affecting the amitriptyline, perpetrated by omeprazole at CYP2C19 and carvedilol, duloxetine, and hydroxyzine at CYP2D6 (Table 3). Although the patient was genetically a CYP2C19 IM and CYP2D6 NM, her plasma concentrations of amitriptyline and its active metabolite nortriptyline were likely to be higher and lower, respectively, than predicted from the genetic results alone, due to the DDGIs. The drug-induced phenoconversion at CYP2C19 (to poor metabolizer (PM)) and CYP2D6 (to IM) increased the likelihood of pharmacotherapy failure and ADEs (e.g., cardiac arrythmias) for the amitriptyline. The clinical pharmacist performed a complete medication safety review; however, only recommendations regarding pain, the patient’s primary complaint, will be discussed in detail within this case report. Recommendations addressing the other clinical conditions can be reviewed in Table 4.
During a telephonic consultation, the provider accepted the clinical pharmacist’s recommendations to discontinue the tramadol and initiate the non-CYP2D6 opioid transdermal, buprenorphine. The clinical pharmacist also recommended to gradually taper off and discontinue the amitriptyline, as the risk of continued use outweighed the benefits. Therefore, the provider decided to gradually decrease the dose of amitriptyline over a two-week period until discontinuation (Table 4). The pregabalin and duloxetine were continued to manage the neuropathy pain, and the gabapentin was discontinued to streamline therapy. In addition to these changes, the provider accepted the alternate recommendation to change omeprazole to pantoprazole to mitigate the non-competitive inhibition affecting amitriptyline at CYP2C19 (Table 3).
One month after implementation of the clinical pharmacist’s recommendations, the patient’s pain scores improved by 1.5 points (average = 6.5, worst = 8.5). Her score on the EuroQOL-5D also improved by two points, which indicated improved pain and an ability to perform self-care activities. Her MRS decreased from “very high” to “high,” which was attributed to the mitigated DDGIs, as well as the discontinuation of anticholinergic and sedative medications (amitriptyline, tramadol, gabapentin). Approximately five weeks after the initiation of the amitriptyline taper (Table 4), the patient reported tremors in the arms and legs. The amitriptyline was re-started at 10 mg, and the patient’s symptoms improved.

3. Discussion

Despite the significant advances in clinical implementation of PGx and the studies demonstrating inter-individual differences in the safety and efficacy for analgesic medications, a trial-and-error approach when initiating medications is still commonly used by providers [2]. In addition to the genetic variations, DDIs further complicate the pain management in older adults with polypharmacy [2]. Opioids are commonly used to manage osteoarthritic pain that is unsuccessfully managed with first-line analgesics (e.g., NSAIDs) [2].
Tramadol, a prodrug, is a weak µ-opioid agonist that inhibits the reuptake of norepinephrine and serotonin [9]. Tramadol is generally considered an acceptable treatment option for osteoarthritis in certain circumstances, including when NSAIDs are contraindicated or when the patients have an inadequate response to first-line therapies [10]. An NSAID was not initiated due to the patient’s renal and cardiovascular comorbidities (Table 1). However, tramadol should be avoided in older adults due to the risks associated with cognitive impairment and gait disturbances [9]. Tramadol may also lower the seizure threshold, especially when taken in combination with a TCA, such as amitriptyline [9]. Therefore, continued use of tramadol in our patient, who has a history of epilepsy, could increase her risk for seizures. Based on patient-specific factors alone (i.e., age and comorbidities), tramadol is not appropriate for this patient.
Tramadol is metabolized by the CYP2D6 enzyme to an active metabolite, O-desmethyltramadol [3]. The CDSS identified carvedilol, duloxetine, and hydroxyzine as medications with a stronger affinity for the CYP2D6 enzyme than tramadol (Table 3). These interactions resulted in our patient’s CYP2D6 phenotype to be phenoconverted from a NM to an IM for tramadol. This DDGI causes the plasma concentration of tramadol’s active metabolite to be lower than expected from the genetic results alone, which may explain the patient’s uncontrolled pain [11]. According to the Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines, tramadol may be used at the recommended age, or weight, specific dosing in CYP2D6 IMs [3]. However, if the patient’s response is inadequate, CPIC recommends a non-codeine opioid [3]. Given that the patient had used other opioids (e.g., hydrocodone/acetaminophen) in the past with minimal success, the provider accepted the recommendation to discontinue the tramadol and initiate transdermal buprenorphine.
Buprenorphine is a schedule III synthetic opioid, with a low potential for physical or psychological dependence, that is used to treat either pain and/or opioid use disorder [12]. Buprenorphine can be safely administered at standard doses in older adults [12]. Furthermore, transdermal buprenorphine is associated with fewer ADEs due, in part, to a ceiling effect that protects against respiratory depression [12]. Buprenorphine is still associated with sedation; older adults should be carefully monitored, especially if they are concomitantly prescribed a benzodiazepine, as in this case [12]. Overall, transdermal buprenorphine may be a relatively safe and effective option for treating chronic pain in older adults.
In addition to replacing tramadol with an alternate opioid, the clinical pharmacist recommended gradually tapering off the amitriptyline. The patient in this case was genetically a CYP2C19 IM. However, because she was concomitantly taking omeprazole, a non-competitive inhibitor of CYP2C19, the CDSS identified a drug-induced phenoconversion to a CYP2C19 PM for the amitriptyline (Table 3). When this DDGI occurs, we expect that the plasma concentration of the amitriptyline is higher, and the concentration of its active metabolite (nortriptyline) is lower than predicted from the genetic results alone [13]. As a result, she is more likely to experience pharmacotherapy failure and/or ADEs (e.g., blurred vision, dizziness, cardiac arrythmias) [14]. Additionally, the carvedilol, duloxetine, and hydroxyzine have stronger affinities for CYP2D6 than the amitriptyline (Table 3), causing a drug-induced phenoconversion from a CYP2D6 NM to an IM for the amitriptyline. According to the CPIC Guidelines, and considering the phenoconversion of CYP2C19 and CYP2D6, amitriptyline should be avoided in this case [14].
Amitriptyline is a first-line medication for neuropathic pain [9]. However, due to the increased risk of anticholinergic side effects and ADEs (e.g., cognitive impairment and gait disturbances), the American Geriatric Society (AGS) recommends avoiding tertiary amines for patients older than 60 years [9]. Pregabalin and duloxetine, both of which were taken by this patient, are approved for neuropathic pain [9]. Since pain was the primary complaint, her dose of pregabalin was increased to further optimize the therapy for neuropathy. The CPIC recommendation, the AGS Guidelines, the increased risk of ADEs, and the presence of duloxetine and pregabalin, all provided support for the decision to deprescribe amitriptyline for this patient, as the risks outweighed the benefits. Discontinuing the amitriptyline also lowered her MRS, demonstrating a reduced likelihood of ADEs, a lower anticholinergic and sedative burden, and mitigated the DDGIs at CYP2C19 and CYP2D6 [7].
Some individuals experience discontinuation symptoms (e.g., flu-like symptoms, imbalance, nausea, tremors) within seven days of stopping an antidepressant; the onset of symptoms after one week is unusual [15]. To reduce the risk of withdrawal, gradual discontinuation is recommended [15]. The duration of the tapering period may vary, depending on the drug’s half-life [15]. Of note, when the amitriptyline taper was initiated, the omeprazole was also switched to pantoprazole, which is not a mechanism-based inhibitor of CYP2C19 [16]. The offset of the irreversible inhibition depends on the formation rate of a new CYP450 enzyme [17]. A CYP450 enzyme’s half-life is typically 36 h, so it may take three to five days for the enzyme function to return to baseline (for our patient, CYP2C19 IM) following the discontinuation of omeprazole [17]. Based on the PGx results and the assessment of the drug-induced phenoconversion, the health care team concluded that the simultaneous discontinuation of the omeprazole and the gradual tapering of the amitriptyline likely caused an accelerated decrease in the plasma concentration of the amitriptyline, which led to the patient experiencing antidepressant-related withdrawal symptoms. Therefore, a longer taper of the amitriptyline was deemed necessary for this patient, and the amitriptyline 10 mg was re-initiated.
In this case, it was crucial that the healthcare team could easily access and assess both the PGx results and the relevant drug-induced phenoconversion data. Ultimately, the patient’s perception of their quality-of-life and pain (i.e., NRS, EuroQOL-5D) were significantly improved.

4. Conclusions

Predicting the safety and efficacy of analgesic medications is complicated by the setting of polypharmacy, drug-induced phenoconversion, and interindividual differences in medication response. This patient case demonstrates the success of a PGx-informed medication safety review, assisted by the CDSS, while accounting for drug interactions and other patient-specific factors (i.e., age, comorbidities). Incorporating sophisticated science and interpretation tools into the medication safety review process can facilitate the individualization of therapy and, such as, in this case, improve the patient’s pain, safety, and quality of life. When implemented, the PGx-informed recommendations made by a clinical pharmacist can optimize medication therapy, ensure efficacy, and reduce the risk of medication-related problems and ADEs. The PGx-informed medication safety reviews that lead to the deprescribing of high-risk medications and the initiation of safer alternatives have the potential to significantly improve care for people with complex drug regimens.

Author Contributions

Writing—original draft preparation, S.M.; writing—review and editing, S.M., N.S.A., C.B., N.D.T.-P., K.P., D.T., J.T., C.T. and V.M.; supervision, J.T. and V.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This case study was authorized by the Biomedical Research Alliance of New York (BRANY) Internal Review Board (file #20-08-12-427).

Informed Consent Statement

Verbal informed consent was obtained.

Acknowledgments

The authors would like to thank Dana Filippoli and Pamela Dow for their comprehensive review and comments pertaining to the contents of this manuscript.

Conflicts of Interest

N.S.A., C.B., N.D.T.-P., K.P., D.T., J.T. and V.M. are employees and shareholders of Tabula Rasa Healthcare. S.M. and C.T. have no conflict of interests to declare.

References

  1. Tinnirello, A.; Mazzoleni, S.; Santi, C. Chronic Pain in the Elderly: Mechanisms and Distinctive Features. Biomolecules 2021, 11, 1256. [Google Scholar] [CrossRef] [PubMed]
  2. Ko, T.M.; Wong, C.S.; Wu, J.Y.; Chen, Y.T. Pharmacogenomics for personalized pain medicine. Acta Anaesthesiol. Taiwan 2016, 54, 24–30. [Google Scholar] [CrossRef] [PubMed]
  3. Crews, K.R.; Monte, A.A.; Huddart, R.; Caudle, K.E.; Kharasch, E.D.; Gaedigk, A.; Dunnenberger, H.M.; Leeder, J.S.; Callaghan, J.T.; Samer, C.F.; et al. Clinical Pharmacogenetics Implementation Consortium Guideline for CYP2D6, OPRM1, and COMT Genotypes and Select Opioid Therapy. Clin. Pharmacol. Ther. 2021, 110, 888–896. [Google Scholar] [CrossRef] [PubMed]
  4. Mostafa, S.; Polasek, T.M.; Sheffield, L.J.; Huppert, D.; Kirkpatrick, C.M.J. Quantifying the Impact of Phenoconversion on Medications with Actionable Pharmacogenomic Guideline Recommendations in an Acute Aged Persons Mental Health Setting. Front. Psychiatry 2021, 12, 724170. [Google Scholar] [CrossRef] [PubMed]
  5. Hicks, J.K.; Dunnenberger, H.M.; Gumpper, K.F.; Haidar, C.E.; Hoffman, J.M. Integrating pharmacogenomics into electronic health records with clinical decision support. Am. J. Health Syst. Pharm. 2016, 73, 1967–1976. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Bain, K.T.; Knowlton, C.H.; Turgeon, J. Medication Risk Mitigation: Coordinating and Collaborating with Health Care Systems, Universities, and Researchers to Facilitate the Design and Execution of Practice-Based Research. Clin. Geriatr. Med. 2017, 33, 257–281. [Google Scholar] [CrossRef] [PubMed]
  7. Bankes, D.L.; Jin, H.; Finnel, S.; Michaud, V.; Knowlton, C.H.; Turgeon, J.; Stein, A. Association of a Novel Medication Risk Score with Adverse Drug Events and Other Pertinent Outcomes Among Participants of the Programs of All-Inclusive Care for the Elderly. Pharmacy 2020, 8, 87. [Google Scholar] [CrossRef] [PubMed]
  8. Michaud, V.; Smith, M.K.; Bikmetov, R.; Dow, P.; Johnson, J.; Stein, A.; Finnel, S.; Jin, H.; Turgeon, J. Association of the MedWise Risk Score with health care outcomes. Am. J. Manag. Care 2021, 27, S280–S291. [Google Scholar] [CrossRef] [PubMed]
  9. McGeeney, B.E. Pharmacological management of neuropathic pain in older adults: An update on peripherally and centrally acting agents. J. Pain Symptom Manag. 2009, 38, S15–S27. [Google Scholar] [CrossRef] [PubMed]
  10. Kolasinski, S.L.; Neogi, T.; Hochberg, M.C.; Oatis, C.; Guyatt, G.; Block, J.; Callahan, L.; Copenhaver, C.; Dodge, C.; Felson, D.; et al. 2019 American College of Rheumatology/Arthritis Foundation Guideline for the Management of Osteoarthritis of the Hand, Hip, and Knee. Arthritis Care Res. 2020, 72, 149–162. [Google Scholar] [CrossRef] [PubMed]
  11. Long, T.; Cristofoletti, R.; Cicali, B.; Michaud, V.; Dow, P.; Turgeon, J.; Schmidt, S. Physiologically Based Pharmacokinetic Modeling to Assess the Impact of CYP2D6-Mediated Drug-Drug Interactions on Tramadol and O-Desmethyltramadol Exposures via Allosteric and Competitive Inhibition. J. Clin. Pharmacol. 2022, 62, 76–86. [Google Scholar] [CrossRef] [PubMed]
  12. Kumar, R.; Viswanath, O.; Saadabadi, A. Buprenorphine. In StatPearls; StatPearls Publishing: Treasure Island, FL, USA, 2021. [Google Scholar]
  13. Vadivelu, N.; Hines, R.L. Management of chronic pain in the elderly: Focus on transdermal buprenorphine. Clin. Interv. Aging. 2008, 3, 421–430. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Tylutki, Z.; Mendyk, A.; Polak, S. Physiologically based pharmacokinetic-quantitative systems toxicology and safety (PBPK-QSTS) modeling approach applied to predict the variability of amitriptyline pharmacokinetics and cardiac safety in populations and in individuals. J. Pharm. Pharm. 2018, 45, 663–677. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Hicks, J.K.; Swen, J.J.; Thorn, C.F.; Sangkuhl, K.; Kharasch, E.D.; Ellingrod, V.L.; Skaar, T.C.; Müller, D.J.; Gaedigk, A.; Stingl, J.C. Clinical Pharmacogenetics Implementation Consortium guideline for CYP2D6 and CYP2C19 genotypes and dosing of tricyclic antidepressants. Clin. Pharmacol. Ther. 2013, 93, 402–408. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. McHugh, B.; Krishnadas, R. Guide to safely withdrawing antidepressants in primary care. Prescriber 2011, 22, 36–40. [Google Scholar] [CrossRef]
  17. Zvyaga, T.; Chang, S.Y.; Chen, C.; Yang, Z.; Vuppugalla, R.; Hurley, J.; Thorndike, D.; Wagner, A.; Chimalakonda, A.; Rodrigues, A.D. Evaluation of six proton pump inhibitors as inhibitors of various human cytochromes P450: Focus on cytochrome P450 2C19. Drug Metab. Dispos. 2012, 40, 1698–1711. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Table 1. Patient’s medication list at the time of PGx testing.
Table 1. Patient’s medication list at the time of PGx testing.
Condition MedicationDoseDirections
AnxietyHydroxyzine50 mg1 tablet at bedtime
Alprazolam0.5 mg1 tablet as needed
Atrial fibrillationDiltiazem120 mg1 tablet in the morning
CirculationAspirin81 mg1 tablet in the morning
Apixaban5 mg1 tablet in the morning and evening
COPDAlbuterol90 mcg2 puffs every 6 h as needed
Ipratropium/albuterol0.5 mg–3 mg1 vial via nebulizer four times daily
Tiotropium1.25 mcg2 puffs once daily
EpilepsyPhenytoin100 mg1 tablet in the morning and bedtime
GERDOmeprazole40 mg1 tablet in the morning
HyperlipidemiaAtorvastatin40 mg1 tablet in the morning
HypertensionCarvedilol6.25 mg1 tablet in the morning and bedtime
HypokalemiaPotassium chloride20 mEq1 tablet in the morning
HypothyroidismLevothyroxine25 mcg1 tablet in the morning
Ischemic cardiomyopathyFurosemide80 mg1 tablet once daily
Nitroglycerin0.4 mg1 tablet every 5 min as needed
Sotalol120 mg1 tablet in the morning and evening
NeuropathyGabapentin100 mg1 capsule in the morning, evening and bedtime
Pregabalin150 mg1 capsule in the morning and evening
Duloxetine60 mg1 capsule in the morning
Amitriptyline75 mg1 tablet at bedtime
Nutrient deficiencyMultivitaminN/A1 tablet in the morning
OsteoarthritisTramadol50 mg1 tablet in the morning, evening, and bedtime
OsteoporosisAlendronate70 mg1 tablet once a week
Abbreviations: COPD = Chronic obstructive pulmonary disease; GERD = Gastroesophageal reflux disease; PGx = Pharmacogenomics.
Table 2. PGx results.
Table 2. PGx results.
GeneGenotypePhenotype Summary
CYP2C19*1|*2Intermediate Metabolizer
CYP2D6*2A|*9Normal Metabolizer
CYP2B6*1|*5Normal Metabolizer
CYP2C9*1|*1Normal Metabolizer
SLCO1B1*1B|*1BNormal Function
Abbreviations: CYP = Cytochrome P450; SLCO = Solute carrier organic anion transporter; PGx = Pharmacogenomics.
Table 3. Summary of affinity and CYP450 metabolic pathway.
Table 3. Summary of affinity and CYP450 metabolic pathway.
SubstanceCYP1A2CYP2B6CYP2C9
NM → pRM
CYP2C19
IM → pPM
CYP2D6
NM → pIM
CYP3A4
Alprazolam
Amitriptyline
Apixaban
Atorvastatin
Carvedilol
Diltiazem
Duloxetine
Hydroxyzine
Omeprazole
Phenytoin
Tramadol *
Affinity StrengthsWeak SubstrateMedium SubstrateStrong SubstrateInhibitorInducer
Abbreviations: Only CYP-metabolized oral medications are displayed; Derived phenotype → Phenoconverted phenotype; CYP = Cytochrome P450; NM = Normal Metabolizer; RM = Rapid Metabolizer; IM = Intermediate Metabolizer; PM = Poor Metabolizer; p = phenoconversion; * = Prodrug.
Table 4. Pharmacist’s recommendations and implementations during medication safety review.
Table 4. Pharmacist’s recommendations and implementations during medication safety review.
MedicationPharmacist’s RecommendationImplementation
Tramadol 50 mgDiscontinue tramadol and utilize a non-CYP2D6 opioidTramadol discontinued and buprenorphine transdermal patch 5 mcg/h weekly initiated
Amitriptyline 75 mgTaper off amitriptyline to mitigate risk of ADEs and pharmacotherapy failureAmitriptyline 50 mg for 1 week, 25 mg for 1 week, then discontinued
Omeprazole 40 mgSwitch to pantoprazole 40 mg to mitigate non-competitive inhibition at CYP2C19Switched to pantoprazole 40 mg
Amitriptyline 75 mg, Furosemide 80 mg, Hydroxyzine 50 mg, Omeprazole 40 mg, Sotalol 120 mg, Tramadol 50 mgRe-evaluate the need for QT-prolonging medications and obtain ECGWill monitor ECG
Atorvastatin 40 mgSwitch to pravastatin to mitigate drug interaction with phenytoinSwitched to pravastatin 40 mg
Pregabalin 150 mg and Gabapentin 100 mgUtilize either pregabalin or gabapentin to mitigate sedative burdenGabapentin discontinued and pregabalin dose increased from 150 mg to 225 mg
Alprazolam 0.5 mgSwitch to lorazepam to mitigate sedative burden and drug interaction at CYP3A4Patient declined
Hydroxyzine 50 mgTaper off hydroxyzine to mitigate anticholinergic and sedative burdenPatient declined
Diltiazem 120 mg, Carvedilol 6.25 mg, Sotalol 120 mgConsult cardiology to evaluate appropriateness of cardiovascular drug regimenCardiology consulted
Abbreviations: ADEs = Adverse drug events; CYP = Cytochrome P450; ECG = Electrocardiogram.
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MDPI and ACS Style

Muhn, S.; Amin, N.S.; Bardolia, C.; Del Toro-Pagán, N.; Pizzolato, K.; Thacker, D.; Turgeon, J.; Tomaino, C.; Michaud, V. Pharmacogenomics and Drug-Induced Phenoconversion Informed Medication Safety Review in the Management of Pain Control and Quality of Life: A Case Report. J. Pers. Med. 2022, 12, 974. https://doi.org/10.3390/jpm12060974

AMA Style

Muhn S, Amin NS, Bardolia C, Del Toro-Pagán N, Pizzolato K, Thacker D, Turgeon J, Tomaino C, Michaud V. Pharmacogenomics and Drug-Induced Phenoconversion Informed Medication Safety Review in the Management of Pain Control and Quality of Life: A Case Report. Journal of Personalized Medicine. 2022; 12(6):974. https://doi.org/10.3390/jpm12060974

Chicago/Turabian Style

Muhn, Selina, Nishita Shah Amin, Chandni Bardolia, Nicole Del Toro-Pagán, Katie Pizzolato, David Thacker, Jacques Turgeon, Crystal Tomaino, and Veronique Michaud. 2022. "Pharmacogenomics and Drug-Induced Phenoconversion Informed Medication Safety Review in the Management of Pain Control and Quality of Life: A Case Report" Journal of Personalized Medicine 12, no. 6: 974. https://doi.org/10.3390/jpm12060974

APA Style

Muhn, S., Amin, N. S., Bardolia, C., Del Toro-Pagán, N., Pizzolato, K., Thacker, D., Turgeon, J., Tomaino, C., & Michaud, V. (2022). Pharmacogenomics and Drug-Induced Phenoconversion Informed Medication Safety Review in the Management of Pain Control and Quality of Life: A Case Report. Journal of Personalized Medicine, 12(6), 974. https://doi.org/10.3390/jpm12060974

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