Clinically relevant insight into genetic makeup and phenotypic biomarkers, such as ADMET and treatment outcomes, would significantly improve predictability of individual response to medications. The combination of metabolomic and pharmacogenomic data from individual patients would offer better insight compared to genotyping alone, especially in patients who take multiple interacting drugs at a time.

 Opioid overdose

Adverse drug events (ADEs) account for an estimated one-third of hospital adverse events and approximately 280,000 hospital admissions annually. Three types of ADEs were selected as high-priority targets as common, clinically significant, preventable, and measurable: Anticoagulants (primary concern: bleeding), diabetes agents(hypoglycemia) and opioids (accidental overdoses/oversedation /respiratory depression) (National Action Plan for ADE prevention, 2014)

 Anticoagulants, antidiabetic agents, and opioid analgesics are responsible for ~60% of ED visits for adverse drug events among older adults (ADE Change Package, 2017)

  • The most common drugs involved in prescription opioid overdose deaths were Methadone, Oxycodone, and Hydrocodone (CDC, 2017)

  • Drug overdose is the leading cause of accidental death in the US, with 52,404 lethal drug overdoses in 2015 (ASAM, 2016).

  • In 2015, 20,101 overdose deaths related to prescription pain relievers, compared to 12,990 overdose deaths related to heroin (ASAM, 2016).

  • Four in five new heroin users started out misusing prescription painkillers. Over 90% said they chose to use heroin because prescription opioids were “far more expensive and harder to obtain.” (ASAM, 2016).

  • Abuse-deterrent opioid formulations

The abuse-deterrent technology does not change the addictive properties of the opioid itself, and while ADFs deter abuse, they are not abuse-proof. In online forums for abusing opioids, there are many instructions on how to circumvent certain abuse-deterrent technologies ( ICER, 2017)

Risk Evaluation and Mitigation Strategies 

Key components of the REMS program are prescriber training and providing educational materials for patients.

Opioid metabolism

Opioid metabolism produces both active and inactive metabolites. The speed of metabolism of opioids varies from one individual to another. Whilst in ultra-rapid metabolizers the drug level never reaches its therapeutic threshold, in individuals whose opioid metabolism is too slow the active metabolites stay in the system too long, producing toxic effects. Opioids and their formulations differ in ways in which they are metabolized by the body. In addition, individuals have varying amount and activity of enzymes that metabolize opioids, depending on their genetics. To make things even more complicated, the same enzymes are used in the metabolism of other drugs and xenobiotics, not just opioids, so different compounds compete for the same enzyme.

Most opioids are extensively metabolized in the liver upon absorption from the gut. This first-pass metabolism reduces the drug bioavailability by subjecting it to dealkylation, hydroxylation, sulfoxidation, deamination, dehalogenation, oxidation or hydrolysis. Metabolism of opioids mainly involves the CYP3A4 and CYP2D6 enzymes. The second phase of drug metabolism, that also takes place in the liver, is conjugation with glucuronic acid, sulfate, glycin or glutathione. Glucuronidation produces highly hydrophilic compounds that are easily excreted in the urine (Smith, 2009).

Genetic variability in the mitochondrial enzymatic system called cytochrome P450 (CYP450) is responsible for a significant percentage of patient casualties due to the heterogeneity of individual response to medications.

Whilst information on the interactions between drugs and CYP450 and other pharmacogenetics biomarkers is included in the prescribing information for physicians, very few patients are tested for high-risk genotypes prior to prescription of known CYP450 inhibitors or inducers.

CYP2D6 function and polymorphism

  • The consequence of altered metabolism can be either toxicity, an adverse drug reaction, or suboptimal therapeutic response.

  • CYP2D6 is largely non-inducible. Typical substrates for CYP2D6 are lipophylic bases. CYP2D6 metabolizes approximately 25% of current drugs, including antidepressants, antipsychotics, antiarrhythmics, antiemetics, beta-blockers, and opioids (Zhou, 2009)

  • Interindividual variation in CYP2D6 activity varies considerably and ranges from ultrarapid metabolizers (UMs), extensive metabolizers (EMs), intermediate metabolizers (IMs) to poor metabolizers (PMs) (Zhou, 2009)

  • There are currently 74 know allelic variants and subvariants of the CYP2D6 gene and the number of alleles is still growing, ranging from no function to ultrarapid metabolism (Zhou, 2009)

  • Substrate-dependent decreased activity: *10, *17, *36 and *41. CYP2D6*17 is generally associated with a reduced function, but its activity varies depending on the substrate (dextromethorphan, risperidone, codeine or haloperidol) (Zhou, 2009)

  • Null alleles, no enzymatic activity: *3, *4, *5, *6, *7, *8, *11, *12, *13, *14, *15, *16, *18, *19, *20, *21, *38, *40, *42, *44, *56 and *62 (poor metabolizers in homozygous and compound heterozygous constellations) (Zhou, 2009)

  • Copy number variations of the CYP2D6 gene associated with ultra-rapid metabolizers (Zhou, 2009)

  • CYP2D6 alleles (See SuperCYP)

  • CYP2D6 substrate: dihydrocodeine, methadone, nicotine (See SuperCYP)

  • CYP2D6 inhibitors: cimetidine, fluoxetine, simvastatin (See SuperCYP)

  • CYP2D6 inducers: loratadine, dexamethasone, paracetamol, rifampicin (See SuperCYP)

 CYP3A4 function and metabolism

  • CYP3A4 is involved in the metabolism of more than 50% of all drugs.

  • CYP3A4 is absent in newborns but reaches levels comparable to adults at about 1 year of age (Medsafe, 2014)

  • Presence: the liver and small intestine. Intestinal CYP3A4 is responsible for food-drug interactions (grapefruit, St. John’s Wort) (Medsafe, 2014)

  • CYP3A4 alleles, nucleotide changes, and effects still poorly mapped (See SuperCYP)

  • CYP3A4 substrate: mefloquine, omeprazol, pravastatin etc. (see SuperCYP)

  • CYP3A4 inhibitors: clarithromycin, erythromycin, diltiazem, itraconazole, ketoconazole, ritonavir, verapamil (See SuperCYP)

  • CYP3A4 inducers: ethanol, phenobarbital, phenytoin, rifampicin, glucocorticoids (See SuperCYP)

Actionable PGX biomarkers & existing clinical guidelines

The Clinical Pharmacogenetics Implementation Consortium (CPIC) published 44 guidelines how to interpret and apply PGX information in clinical practice, including, codeine, phenytoin, warfarin, citalopram, allopurinol, abacavir and others. Sadly, opioid painkillers do not seem to be getting the attention they deserve. The only actionable PGX biomarker is available for CYP2D6 for codeine. PGX Biomarkers for nervous system drugs (CPIC, 2017).