AUTHORS
Brian T. Hocum, PharmD, CGP, Adjunct Faculty Member, Washington State University College of Pharmacy, Spokane, WA
Elizabeth L. Black, MD, Blue Mountain Family Health, Clarkston, WA
Kevin J. Black, MAT, Clarkston, WA
PEER REVIEWER
Stuart J. Beatty, PharmD, BCACP, CDE, Associate Professor of Clinical Pharmacy, The Ohio State University College of Pharmacy, Columbus, OH
To reveal any potential bias in this publication, and in accordance with Accreditation Council for Continuing Medical Education guidelines, we disclose that Dr. Farel (CME question reviewer) owns stock in Johnson & Johnson. Dr. Stapczynski (editor) owns stock in Pfizer, Johnson & Johnson, Walgreens Boots Alliance Inc., GlaxoSmithKline, Bristol Myers Squibb, and AxoGen. Dr. Hocum (author) reports he is an employee of United Therapeutics. Dr. Greg Wise (editor) is involved in sales for CNS Vital Signs. Dr. Schneider (editor), Ms. Fessler (nurse planner), Dr. E. Black (author), Kevin Black (author), Dr. Beatty (peer reviewer), Ms. Mark (executive editor), and Ms. Coplin (executive editor) report no financial relationships with companies related to the field of study covered by this CME activity.
Introduction
Drug-to-drug interactions (DDI) are a concern of increasing significance at all levels of healthcare. This article will provide examples and illustrations to demonstrate the metabolic processes that underlie many of these interactions. An understanding of the fundamental mechanisms of drug metabolism and transport is important for understanding DDI in the emergency setting.
The mechanisms of drug metabolism have an interesting evolutionary history. The metabolic systems that are relied on to transmit drugs through the body were not developed to introduce beneficial substances into the body, but rather to keep harmful substances out. As animal ancestors diverged from plants and began relying on them as a food source, plants developed phytoalexins that could poison and deter the animals that fed on them. Through selective pressures, animals with more robust enzymatic systems that could neutralize those toxins thrived. This back and forth “animal and plant warfare” resulted in diversification of enzymes that now metabolize drugs in the body.1
Medications increasingly are being developed specifically either to avoid or exploit particular metabolic processes to achieve better efficacy or decrease the potential for interaction with other medications that use the same metabolic pathways. These metabolic points of interaction between drugs are the primary focus of this article.
Emergency physicians are well aware that the number of elderly seeking care in the ED is increasing. As patients age and the number of comorbid conditions increases, more medications will be employed to meet multiple treatment goals. Inevitably, this will increase the risk of polypharmacy in these patients.
DDIs represent one of the most significant risks of polypharmacy. As the number of medications involved in a patient’s treatment regimen increases, the likelihood of any two of those medications having an interaction that significantly affects the action of one or both of the medications involved increases dramatically.
Providers with access to electronic medical records (EMRs) and electronic prescribing (ERx) software are becoming increasingly familiar with interaction alerts that are automatically generated by such systems to help anticipate DDIs. Before the widespread adoption of these software tools, healthcare providers were not ideally successful at anticipating or evaluating DDIs on their own. One study showed that a group of physicians was able to recognize or classify such interactions only just over half the time, even with strongly contraindicated medication pairings.2 Clearly, these software tools are a necessary adjunct to successful management of pharmacotherapy. As polypharmacy becomes more endemic, however, these alerts may become so frequent that providers may no longer be able to easily discern which alerts are most likely to dramatically affect the overall safety and efficacy of the medications involved. This is especially important, as alerts generated by these systems do not always represent DDI of sufficient clinical significance to avoid certain medication combinations. A more recent study showed that providers’ understanding of the relative clinical significance of DDI was “generally poor.”3 This further highlights the importance of improving provider understanding of the mechanisms underlying DDI.
Guidance is even less clear in interactions that may affect the potential efficacy of a medication in the patient, but are not clearly contraindicated. Coadministration of a particular pair of medications may adversely affect the effectiveness of one or both of the medications, but not to the point where they are entirely ineffective in achieving desired goals. Alternatively, some drug combinations actually may reinforce the effectiveness of one medication to the point that they can be used at lower doses than are usually necessary to achieve the desired therapeutic results.
Absorption
An excellent place to begin the discussion of drug interactions is with the absorption of orally administered medications. Before oral medications can reach systemic circulation and their site of action, they must be absorbed. Multiple factors, including gastric pH and motility, gut pathology, and the chemical structure and formulation of the medication itself, can influence this.4 These factors can be manipulated to achieve increased or decreased blood levels of drugs and desired therapeutic outcomes. For example, the presence or absence of food may dramatically influence gastrointestinal (GI) motility.
GI motility is more rapid on an empty stomach.5 When taken on an empty stomach, some medications (like diazepam) reach the small intestine more rapidly, where they are absorbed into the bloodstream (see Table 1). This may result in a faster time to reach the maximum concentration (Cmax) and, thus, maximum effectiveness, compared to taking the same medications with food. The presence of food tends to slow gastric motility. Although this may delay the time it takes for the drug to reach Cmax, the increased time in the gut may allow more time for the medication to enter into solution, which is required for absorption. Thus, the overall exposure to the drug, as measured by the area under the curve (AUC), may be greater. Composition of foods also can alter the absorption of drugs. Foods rich in fat, fiber, or calcium have a significant effect on the absorption of many medications.
Table 1. Gastrointestinal/Absorption Interaction Examples
Drug Combination |
Mechanism |
Effect |
|
|
|||
|
1 |
diazepam + food |
food interaction |
Diazepam and a moderate fat meal resulted in a 27% decrease to diazepam AUC, a 20% decrease in Cmax, and a 30-minute delay in absorption (15 minutes vs. 45 minutes).1 |
|
2 |
metformin + food |
food interaction |
Single-dosed metformin 500 mg to 2500 mg with either a low-fat or high-fat meal resulted in a 38% or 73% increase to metformin AUC, respectively, relative to fasting.2 |
|
3 |
amphetamines + GI acidifiers |
pH interaction |
GI acidifiers (e.g. non-diet soda, ascorbic acid, cranberry and other fruit juices) increase ionization of amphetamines and lower absorption of amphetamines.3 |
|
4 |
amphetamines + GI alkalinizers |
pH interaction |
GI alkalinizers decrease ionization of amphetamines and increase absorption of amphetamines.3 |
|
5 |
levothyroxine + calcium carbonate |
formation of insoluble complex |
Multidosed calcium carbonate 1200 mg daily added to a previously stabilized dose of levothyroxine x 3 months resulted in a 9% decrease in mean free T4 and a 7% decrease in mean total T4 levels. 20% of patients had serum TSH levels higher than the normal range during calcium carbonate coadministration.4 |
|
6 |
statins + grapefruit |
CYP3A4 inhibition |
Single-dosed atorvastatin 40 mg and multidosed grapefruit juice 240 mL daily resulted in a 37% increase in atorvastatin AUC.5 Multidosed grapefruit juice 200 mL double strength TID x 3 days and single-dosed lovastatin 80 mg resulted in a 1400% increase in lovastatin AUC and a 400% increase in metabolite lovastatin acid AUC.6 Multidosed grapefruit juice single-strength 8 ounces x 3 days and single-dosed simvastatin 20 mg on day 3 resulted in 90% increase in simvastatin AUC and 30% increase in metabolite simvastatin acid AUC.7 |
|
7 |
cyclosporine + diltiazem |
CYP3A4 & P-gp inhibition |
Multidosed diltiazem 90 mg to 120 mg PO BID and oral cyclosporine resulted in a 51% increase in cyclosporine AUC and a 34% increase in Cmax.10 In another study the dose of cyclosporine was decreased such that an estimated 28% cost savings per patient was achieved.8 |
|
8 |
protease inhibitors (e.g., saquinavir) + ritonavir |
CYP3A4 & P-gp inhibition |
Saquinavir and ritonavir resulted in up to a 592% increase in saquinavir AUC and 424% increase in Cmax.9 |
|
Tables may not include entire mechanisms or studies with conflicting findings. Interaction severity and management recommendations are not included as they may be highly dependent on the patient and clinical scenario. |
|||
Another factor that contributes to drug bioavailability is the acidic environment of the stomach. This harsh environment can destroy drugs before they ever make it to the small intestine for absorption, and some drugs must be specially formulated (e.g., delayed-release omeprazole) to reach the small intestine intact. For further information on food-drug interactions, consider reading article 1 in the provider resource tool kit included at the end of this article.
First Pass
“First pass” refers to the initial passage of a medication, after absorption from the gut, as it passes through the liver to the bloodstream. First pass concludes when a medication or its metabolites enter systemic circulation and is used as a baseline for determining bioavailability. Bioavailability is defined as the fraction of unchanged drug that reaches systemic circulation or the molecular site of action.4 Once absorbed into the cells of the small intestine (i.e., enterocytes), drugs encounter the body’s next line of defense against xenobiotics, the drug metabolism and transport system. Understanding this system is an important basis for discussing drug interactions. We will be using illustrations to depict a slightly simplified physiology of drug transport and metabolism in the body. This will facilitate a deeper understanding of the mechanism of drug interactions.
As outlined in Figure 1, the drug efflux transporter p-glycoprotein (p-gp) and the drug metabolizing enzyme cytochrome P450 3A4 (CYP3A4) are highly expressed in enterocytes. These work together as an intestinal “tag team” (Jessica Oesterheld, MD, e-mail communication, December 2014). Drugs are continually absorbed into the enterocyte. P-gp effluxes the drug molecule out of the enterocyte. Inside the cell, drugs encounter CYP3A4 and undergo extensive metabolism. These processes happen over and over during GI transit so that the amount of drug that reaches the portal vein will be significantly decreased if it is a substrate for either of these pathways. See Table 1 for several examples of interactions that take place at this juncture.
Figure 1. Intestinal Enterocytes
In this example, under normal conditions, the amount of drug reaching the portal venous system is about one-third unchanged drug and about two-thirds metabolite. With inhibition of CYP, a greater amount of the drug reaches the portal venous system. With inhibition of P-gp, a greater amount of both the drug and metabolite reaches the portal venous circulation.
Understanding Inhibition and Induction
For some drugs that have active metabolites, interactions involving inhibition may shift the metabolic ratio such that less of the active metabolite is formed and effectiveness is lost. When the parent molecule is inert relative to the active metabolite, the drug can be classified as a prodrug. Codeine, clopidogrel, and tamoxifen are three examples of prodrugs. Many drugs fall into a category in which there is activity in both the parent and metabolite form.
Competitive Inhibition. This can function in two ways. One molecule (inhibitor) may have a higher affinity for the metabolic enzyme so that it binds more readily to the enzyme, and the interacting medication (drug) is displaced and metabolized less readily. Another way this type of inhibition occurs is that the inhibitor molecule may have a greater concentration at the site of metabolism, saturating it and outcompeting the interacting medication for the metabolic action of the enzyme. This may be a similar function at the transporter level, but this is less well-understood.
Mechanism-based Inhibition. In this type of inhibition, the inhibiting substance (inhibitor) binds irreversibly to the enzyme, rendering the enzyme functionally inert. This removes the potential for the enzyme to metabolize the interacting drug (drug). In theory, the effects of mechanism-based inhibition may last longer. The permanent nature of the alteration of the enzyme requires that more enzyme must be produced by the body to replace the enzyme rendered inert by the inhibiting reaction. The difference between competitive and mechanism-based inhibition may not be clinically significant. The end result is that the medication that is less readily metabolized is more likely to have increased systemic exposure and effect.
Induction. This occurs when a drug signals nuclear receptors of cells to increase expression of a particular drug-metabolizing enzyme. Classic examples of inducers include the enzyme-inducing anticonvulsants phenobarbital, primidone, phenytoin, and carbamazepine. Rifampin is another classic enzyme-inducing drug, and smoking also has significant enzyme-inducing effects. The effects of induction would actually be opposite of the effects seen in Figure 1. Increased transporter and cytochrome activity would ultimately lead to decreased amounts of drug reaching the bloodstream.
Predicting interactions on the basis of inhibition or induction of transporter proteins can be more challenging than those based on enzymatic inhibition or induction.
To adequately understand transporter-based interactions, it is important to have specific knowledge of both the function and location of the transporter proteins involved. For example, inhibition of the effluxing transporter p-gp in the enterocytes (see Figure 1) will result in increased drug available to reach systemic circulation and, therefore, increased drug exposure. Likewise, inhibition of a hepatic influx transporter, such as SLCO1B1 (see the basolateral border of Figure 2), will result in less exposure of the drug to CYPs and, therefore, increased systemic exposure due to decreased metabolism. Also, inhibiting influx transporters OAT1 and OAT3 on the basolateral side of the proximal renal tubule will result in increased drug exposure due to decreased renal elimination (see Figure 3).
Figure 2. Hepatocytes
Figure 3. Renal Proximal Cell
In theory, inhibition of p-gp efflux in hepatocytes could actually result in a “trapping” of the drug in the hepatocyte and increased metabolism of the drug, resulting in decreased systemic exposure, rather than the drug entering into the bile and undergoing enterohepatic recirculation. Lastly, inhibition of the efflux transporter p-gp in the blood-brain barrier (BBB) would not be expected to change systemic exposure of a drug to any clinically significant extent, but it may increase the amount of drug that reaches the CNS and, therefore, increase the risk of toxicity. The difference between these potential effects and the effect of p-gp inhibition in the enterocyte illustrates the importance of considering the location of action as well as the affected transporter in anticipating the clinical impact of inhibition or induction on transporter-based interactions.
Phase I Drug Metabolism
Once beyond the gut, drugs and their respective metabolites enter the portal vein en route to the liver. Here they are metabolized through the hepatocytes before they either enter back into systemic circulation via the central vein or are cleared via the bile. Drug molecules can enter hepatocytes by transporters, as already discussed, or by other means, such as passive diffusion (see Figure 2). For drugs that rely on transporters, like statins, clinically significant interactions may exist if their influx transporter (SLCO1B1) is inhibited. In this case, the blood levels of the statin may significantly increase. This would increase the risk for adverse effects, such as myalgias and rhabdomyolysis (see Table 3).
Highly expressed as well as highly polymorphic, the various families of cytochrome P450 enzymes (CYPs) are also encountered within the hepatocytes. Although the discussion will focus on these enzymes, it is important to note that many others metabolize drugs during phase I and phase II metabolism. However, CYPs are among the most studied and well understood in terms of clinically significant interactions.
Phase I metabolism is the term used to describe the process of adding or exposing hydrophilic functional groups (functionalization) to drug molecules.1 From a drug interaction standpoint, CYP2D6, CYP2C9, CYP2C19, CYP3A4, and CYP3A5 are the most important, as they are involved in the metabolism of the majority of all hepatically cleared drugs.8 Examples of common drugs and drug classes metabolized by these pathways can be found in Table 2. The types of reactions that cytochromes have with drugs is oxidative in nature. Reactions can result in inactivation or activation of drugs as well as a change in structure that makes the drug molecule more amenable to conjugation via phase II drug-metabolizing enzymes and/or more amenable to elimination. Because so many medications are metabolized by the CYP450s and because these enzymes can dramatically influence the exposure of drugs, this system is highly vulnerable to interactions. One useful example to illustrate the impact of this mechanism is the interaction between dextromethorphan and quinidine.
Table 2. Common Drugs by CYP Enzyme
CYP2D6 |
CYP2C9 |
CYP2C19 |
CYP3A4/5 |
|
Antiarrhythmics |
NSAIDs |
Antidepressants |
Benzodiazepines |
Dextromethorphan, an opioid analog that is commonly used to treat cough,4 recently was discovered to be an effective medication for pseudobulbar affect, a neurologic disorder that can increase emotional instability.9 Dextromethorphan is also a CYP2D6 and p-gp substrate. To be effective at treating pseudobulbar affect, high concentrations of the drug must pass through the BBB and into the CNS. For most individuals, this is not possible without giving very high doses of dextromethorphan. Coadministration with low-dose quinidine, a potent CYP2D6 inhibitor, boosts systemic exposure of dextromethorphan up to 20-fold (see Table 3). An interesting fact about this interaction is that coadministration with quinidine is not required in individuals who are genetically deficient in the CYP2D6 enzymes (CYP2D6 poor metabolizers). This is because dextromethorphan exposure is sufficiently high in these patients. Exposing them to quinidine, which has its own profile of adverse effects such as QTc prolongation, is unnecessary.10
Other examples of phase I interactions are included in Table 3 and include the use of disulfiram to deter alcoholics from drinking and the use of ethanol or fomepizole to treat methanol and ethylene glycol poisoning (see Table 3).
Another example is treatment of bacterial vaginosis in heavy alcohol drinkers. Metronidazole has resulted in cases of disulfiram-like reactions with alcohol. This is likely due to metronidazole-possessing aldehyde dehydrogenase (ALDH)-inhibiting properties. This increases plasma levels of acetaldehyde and causes unpleasant side effects: flush, vasodilatation, throbbing head and neck pain, respiratory difficulties, vomiting, sweating, and thirst. Although this interaction would probably be less likely with intravaginal administration of metronidazole, there has been a case report of such an interaction.
Table 3. Hepatic Interaction Examples
Drug Combination |
Mechanism |
Effect |
|
|
|||
|
1 |
dextromethorphan + quinidine |
CYP2D6 & P-gp inhibition |
Dextromethorphan/quinidine 30 mg/10 mg PO BID resulted in up to a 20-fold increase in dextromethorphan exposure compared to dextromethorphan alone.1 |
|
2 |
warfarin + amiodarone |
CYP2C9 inhibition |
Warfarin and amiodarone resulted in a 55% decrease in warfarin clearance.2 |
|
3 |
citalopram + omeprazole |
CYP2C19 inhibition |
Multidosed omeprazole 20 mg daily x 18 days and single dosed citalopram 20 mg on day 8 resulted in a 120% increase to s-citalopram plasma concentrations and no statistically significant change for r-citalopram.3 |
|
4 |
ethinyl estradiol/ levonorgestrel + phenytoin |
CYP3A4 induction |
Multidosed phenytoin 200 mg to 300 mg daily x 8 to 12 weeks and single-dosed ethinyl estradiol 50 mcg/levonorgestrel 250 mcg resulted in a 49% decrease in ethinyl estradiol AUC and a 42% decrease in levonorgestrel AUC.4 |
|
5 |
clozapine + cigarette smoking |
CYP1A2 induction |
Smoking and clozapine resulted in 50% decrease in clozapine levels, and when smoking was discontinued up to 300% increase in clozapine levels have been reported.5,6 |
|
6 |
alcohol + disulfiram |
aldehyde dehydrogenase (ALDH) inhibition |
Disulfiram and its active metabolite inhibit the conversion of acetaldehyde to acetate through inhibition of ALDH. Acetaldehyde blood levels increase five to ten-fold. Symptoms of hyperacetaldehydemia include flush, vasodilatation, throbbing head and neck pain, respiratory difficulties, vomiting, sweating, and thirst.7 |
|
7 |
methanol or ethylene glycol + ethanol or fomepizole |
alcohol dehydrogenase (ADH) inhibition |
Ethanol and fomepizole both serve as an antidote by competitively inhibiting the metabolism of methanol or ethylene glycol at ADH resulting in the decreased formation of either of these drugs to their toxic metabolites.8,9 |
|
8 |
methylphenidate + carbamazepine |
CES1 induction |
Coadministration has resulted in several cases of decreased methylphenidate exposure and decreased effectiveness.10,11 |
|
9 |
rosuvastatin + gemfibrozil |
SLCO1B1 inhibition |
Multidosed gemfibrozil 600 mg BiD x 7 days and single-dosed rosuvastatin 80 mg resulted in an 88% increase in rosuvastatin AUC and a 121% increase in Cmax.12 |
|
10 |
rosuvastatin + cyclosporine |
SLCO1B1 inhibition |
Multidosed cyclosporine 75 mg to 200 mg BiD and multidosed rosuvastatin 10 mg to 20 mg daily x 10 days resulted in a 610% increase to rosuvastatin AUC and a 960% increase to rosuvastatin Cmax.13 |
|
11 |
cyclosporine + repaglinide |
SLCO1B1 + CYP3A4 inhibition |
Multidosed cyclosporine 100 mg daily x 2 days and single-dosed repaglinide 0.25 mg resulted in an 140% increase in repaglinide AUC and 80% increase in Cmax. This may enhance the blood glucose-lowering effects of repaglinide and increase the risk of hypoglycemia.14 |
|
12 |
digoxin + ritonavir |
P-gp inhibition |
Multidosed ritonavir 300 mg BiD x 11 days and single-dosed digoxin IV 500 mcg resulted in an 86% increase to digoxin AUC.15 |
|
13 |
lamotrigine + ethinyl estradiol |
UGT2B7 induction |
Multidosed ethinyl estradiol 30 mcg/ levonorgestrel 150 mcg daily and multidosed lamotrigine 300 mg daily resulted in a 52% decrease in lamotrigine AUC and 39% decrease in lamotrigine Cmax.16 There have been cases of breakthrough seizures with this combination.17 |
|
14 |
zidovudine + probenecid |
UGT2B7 inhibition |
Coadministration resulted in a 106% increase in zidovudine AUC.18 |
|
15 |
lorazepam + valproic acid |
UGT2B7 & UGT2B15 inhibition |
Coadministration has resulted in a 20% to 67% increase in lorazepam AUC.19,20 |
|
16 |
valproic acid + ethinyl estradiol |
UGT2B7 induction |
Coadministration has resulted in valproic acid plasma concentration decreases of up to 46% with increased seizure frequency in one report.21,22,23 |
|
17* |
azathioprine + sulfasalazine |
TPMT inhibition |
Multidosed sulfasalazine mean dose 2.1 grams daily and multidosed azathioprine mean dose 92.8 mg daily resulted in a 55% discontinuation rate due to rash, gastrointestinal upset, leucopenia, and nephrotic syndrome.24 |
|
Tables may not include entire mechanisms or studies with conflicting findings. Interaction severity and management recommendations are not included as they may be highly dependent on the patient and clinical scenario. *TPMT is a phase II enzyme but its location may not be primarily hepatic. |
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Phase II Drug Metabolism
Phase II metabolism is the term used to describe secondary drug metabolism and is usually conjugative in nature.1 This usually occurs after phase I metabolism, but this is not always the case. It may happen in the same cell or tissue immediately after phase I metabolism. It also may occur after the drug has re-entered systemic circulation and again entered into tissues like the liver for further metabolism.
The most important phase II enzymes from a drug metabolism and interaction standpoint are the uridine 5’- diphosphate glucuronosyltransferases (UGTs). This enzyme family functions via glucuronidation — the addition (or conjugation) of glucuronic acid, which is highly water soluble — to a drug molecule.
Figure 3 can be used to visualize the mechanisms of interactions that occur in phase II metabolism. Lamotrigine is a non-enzyme inducing anticonvulsant that undergoes glucuronidation to inactive metabolites. The known UGTs that metabolize lamotrigine include UGT2B7, UGT1A3, and UGT1A4. Ethinyl estradiol is known to induce glucuronidation and has been shown to result in clinically significant decreases in lamotrigine blood levels (see Table 3). Using Figure 2, one can infer that the induction of UGT metabolism of lamotrigine with ethinyl estradiol could result in increased conversion of lamotrigine to inactive metabolites. This would decrease blood levels of the active drug and, therefore, decrease effectiveness.
Thiopurine methyltransferase (TPMT) is another example of a phase II drug-metabolizing enzyme, although it is unique in that it conjugates drugs with methyl groups (methylation), which is a process that actually decreases water solubility. It is important for the inactivation of thiopurine drugs like azathioprine, 6-mercaptopurine, and 6-thioguanine.
Although the known interactions are fewer in numbers than phase I interactions, their clinical importance should not be overlooked. Article 3 in the provider resource tool kit at the end of this article provides a comprehensive review of the enzymes covered here, as well as others that are involved in drug metabolism. Article 4 provides a specific review on UGTs.
Table 4. Examples of UGT Substrates, Inhibitors, and Inducers34,35
UGT1A1 |
UGT2B7 |
UGT2B15 |
|
Substrates
Inhibitors
Inducers
|
Substrates
Inhibitors
Inducers |
Substrates
Inhibitors
Inducers |
Distribution
As with CYP metabolism, UGT glucuronidation usually inactivates drugs but there are some glucuronide metabolites that are active or more potent than the original parent molecule. The glucuronide metabolite of morphine, morphine-6-glucuronide, is one example of this.12 Table 4 lists some of the of UGT metabolized drugs, inhibitors, and inducers.
Although this article will not go into a great deal of review on drug distribution, this is also an important concept for understanding drug interactions. As a drug reaches systemic circulation, it will begin to distribute into tissues. As with absorption, distribution of a drug is dependent on a host of factors, such as its blood concentration (a direct result of factors such as dose, bioavailability, and clearance), protein binding, lipophilicity (fat solubility), the patient’s body weight, fat distribution, and renal function.
Interactions involving distribution tend to be more difficult to identify because they don’t necessarily result in a change to the systemic exposure of the drug. One type of distribution-based interaction affects how much of the free drug (i.e., unbound from plasma protein) is available to distribute into tissues and/or bind to a molecular site of action (bound drug is considered unavailable for either of these). The interaction between phenytoin and valproic acid is a classic example that demonstrates this (see Table 5).
Interactions that deal with protein displacement are actually controversial, and some experts claim that any change in unbound free drug by protein displacement would be buffered by redistribution, metabolism, and elimination of the newly freed/unbound drug.13 According to one expert, for a protein displacement interaction to be clinically significant, it must meet the following criteria: the victim drug must be > 90% protein-bound, have a narrow therapeutic index, have a high hepatic extraction ratio, and be administered as an IV formulation.13
Another distribution type of interaction is that between loperamide and quinidine (see Table 5). Loperamide is an antidiarrheal agent with potent mu opioid binding affinity but poor penetration into the central nervous system.4 Under normal circumstances, loperamide is effluxed out of the brain by p-gp and does not have a significant CNS effect. However, when combined with a p-gp inhibitor like quinidine, the loperamide may begin to accumulate in the brain, resulting in adverse effect and toxicity.
Table 5. Distribution Interaction Examples
Drug Combination |
Mechanism |
Effect |
|
|
|||
|
1 |
loperamide + quinidine |
p-gp inhibition |
Loperamide 16 mg and quinidine 600 mg resulted in statistically significant respiratory depression compared to loperamide alone.1 |
|
2 |
phenytoin + valproic acid |
albumin binding displacement |
A complex interaction. Valproate 400 mg TID and phenytoin 250 mg resulted in a 60% increase in the free fraction of phenytoin,2 which may be associated with transient increases in phenytoin toxicity.3 |
|
3 |
warfarin + valproic acid |
albumin binding displacement |
Valproic acid loading dose may displace warfarin from protein binding site increasing the free unbound warfarin levels and increase INR to a clinically significant extent.3 |
|
Tables may not include entire mechanisms or studies with conflicting findings. Interaction severity and management recommendations are not included as they may be highly dependent on the patient and clinical scenario. |
|||
Excretion
As drugs and their respective metabolites circulate, they are eventually eliminated from the body. The primary elimination site for most drugs is the kidneys, but other elimination routes include the hepatobiliary system, the lungs, skin, saliva, and breast milk. Providers commonly adjust for delays in renal elimination by estimating the glomerular filtration rate via use of the creatinine clearance calculation. This estimate is used to dose many drugs, especially antibiotics. However, anticipating dose adjustments for drug interactions that take place at the kidneys may be less familiar to most providers. Even more so than the other sites covered in this article, renal clearance is a complex process and this review only addresses the highlights of this system. For more information on this system, consider reading article 7 in the provider resource tool kit at the end of this article.
During kidney elimination, many drugs will be passively filtered through the glomerulus and eliminated this way. However, many drug/metabolite molecules also undergo renal tubular secretion, which is an extremely important site for drug interactions since this is a predominantly transporter-mediated process.14 Renal tubular secretion happens in the proximal tubule of nephrons and again involves a highly complex network of transporters, some of them energy dependent, that move drugs and other electrolytes in and out of the collecting tubule (urine) and blood. Glucuronidation and sulfation (via sulfotransferases [SULTs]) also occur in the renal proximal tubule. It is believed that the contribution to overall drug metabolism in the kidneys is much less clinically significant compared to that which occurs in the intestine and liver.14
Two of the most well-understood transporters from a drug interaction standpoint are the organic anion transporters OAT1 and OAT3. These transporters work by exchanging intracellular endogenous molecules with extracellular anions.15 Probenecid, used as an antigout agent because of its ability to inhibit reabsorption of uric acid from the collecting tubule, is a classic inhibitor of these transporters. (See Table 6.)
Table 6. Kidney Elimination Interaction Examples
Drug Combination |
Mechanism |
Effect |
|
|
|||
|
1 |
penicillin + probenecid |
OAT3 inhibition |
Coadministration results in a 100% to 300% increase in penicillin plasma levels.1 |
|
2 |
oseltamivir + probenecid |
OAT1 inhibition |
Single-dosed oseltamivir 150 mg and multidosed probenecid 500 mg resulted in a 150% increase in oseltamivir active metabolite AUC and 100% increase in Cmax.2 |
|
3 |
cidofovir + probenecid |
OAT1 inhibition |
Probenecid and cidofovir 5 mg/kg resulted in a 44% increase in cidofovir AUC and a 34% decrease in cidofovir renal clearance.3 |
|
4 |
famotidine + probenecid |
OAT3 inhibition |
Multidosed probenecid 1500 mg and single-dosed famotidine 20 mg resulted in an 81% increase in famotidine AUC.4 |
|
Tables may not include entire mechanisms or studies with conflicting findings. Interaction severity and management recommendations are not included as they may be highly dependent on the patient and clinical scenario. |
|||
An interaction that could occur in the ED is if oseltamivir is prescribed to a patient taking probenecid for gout. This interaction results in elevated serum levels for oseltamivir (see Figure 4) and increased potential for adverse effects. As with the drug-metabolizing enzymes, by understanding the drug’s route of elimination, providers can avoid harmful interactions and sometimes promote beneficial ones.
Figure 4. Blood Levels of Oseltamivir (Tamiflu®)
Adapted from: Butler D. Wartime tactic doubles power of scarce bird-flu drug. Nature 2005;438:6.
Summary and Discussion
As pharmaceutical sciences advance, one certainty is that the constellation of medications that patients may be taking at the time of their ED visit is likely to expand. To further complicate this issue, aging patient populations will only increase the incidence of comorbidities that make polypharmacy a common situation. While software tools can help facilitate the recognition of current or potential DDI in the polypharmacy patient, the software cannot always provide adequate information about managing DDI while still meeting treatment goals.
The best solution to this DDI dilemma is to seek out and capitalize on the expanding knowledge of the fundamental mechanisms of drug metabolism. This understanding can accomplish much more than simply avoiding DDI or mitigating its dangers and effects when it is encountered.
It is important to remember that community resources, especially pharmacists, have more extensive training that can and should be fully utilized to facilitate understanding and management of pharmaceutical therapies, including metabolism-related DDI.
Provider Resource Tool Kit
|
1 |
Review of food and drug interactions |
Winstanley PA, Orme ML. The effects of food on drug bioavailability. Br J Clin Pharmacol 1989;28:621-628. |
|
2 |
Review of gut wall interactions |
Thelen K, Dressman JB. Cytochrome P450-mediated metabolism in the human gut wall. |
|
3 |
Comprehensive review of metabolic pathways and drug interactions |
Wynn G, Oesterheld J, Cozza K, Armstrong S. Clinical Manual of Drug Interaction Principles for Medical Practice. Arlington, VA: American Psychiatric Publishing, Inc.; 2009. |
|
4 |
Review of UGTs |
Rowland A, Miners JO, Mackenzie PI. The UDP-glucuronosyltransferases: Their role in drug metabolism and detoxification. Int J Biochem Cell Biol 2013;45:1121-1132. |
|
5 |
Discussion of protein binding displacement interactions |
Rolan PE. Plasma protein binding displacement interactions — why are they still regarded as clinically important? Br J Clin Pharmacol 1994;37:125-128. |
|
6 |
Review of transporters |
Han HK. Role of transporters in drug interactions. Arch Pharm Res 2011;34:1865-1877. |
|
7 |
Review of kidney-based drug elimination |
Tett SE, Kirkpatrick CM, Gross AS, McLachlan AJ. Principles and clinical application of assessing alterations in renal elimination pathways. Clin Pharmacokinet 2003;42:1193-1211. |
REFERENCES
- Gonzalez FJ, Nebert DW. Evolution of the P450 gene superfamily: Animal-plant ‘warfare,’ molecular drive and human genetic differences in drug oxidation. Trends Gen 1990;6:182-186.
- Glassman PA, Simon B, Belperio P, Lanto A. Improving recognition of drug interactions: Benefits and barriers to using automated drug alerts. Med Care 2002;40:1161-1171.
- Ko Y, Malone DC, Skrepnek GH, et al. Prescribers’ knowledge of and sources of information for potential drug-drug interactions: A postal survey of US prescribers. Drug Safety 2008;31:525-536.
- Brunton LL, Chabner BA, Knollmann BC, eds. Goodman & Gilman’s The Pharmacologic Basis of Therapeutics. 12th ed. New York: McGraw-Hill; 2011.
- Winstanley PA, Orme ML. The effects of food on drug bioavailability. Br J Clin Pharmacol 1989;28:621-628.
- Oramed Pharmaceuticals, Inc. June 2014. Available at http://oramed.com/userfiles/files/0801-clinical-trial-chart - 15_06_14.pdf. Accessed Jan. 2, 2015.
- Tapaninen T, Neuvonen PJ, Niemi M. Orange and apple juice greatly reduce the plasma concentrations of the OATP2B1 substrate aliskiren. Br J Clin Pharmacol 2011;71:718-726.
- Ingelman-Sundberg M. Pharmacogenetics of cytochrome P450 and its applications in drug therapy: The past, present and future. Trends Pharmacol Sci 2004;25:193-200.
- Rosen H. Dextromethorphan/quinidine sulfate for pseudobulbar affect. Drugs Today 2008;44:661-668.
- Nuedexta® [package insert]. Avanir Pharmaceuticals, Inc. Aliso Viejo, CA; December 2013. http://dailymed.nlm.nih.gov/dailymed/drugInfo.cfm?setid=484e0918-3442-49dc-8ccf-177f1f3ee9f3. Accessed Dec. 29, 2014. .
- Plosker GL. Possible interaction between ethanol and vaginally administered metronidazole. Clin Pharm 1987;6:189-193.
- Christrup LL. Morphine metabolites. Acta Anaesthes Scandinavica 1997;41(1 Pt 2):116-122.
- Rolan PE. Plasma protein binding displacement interactions — why are they still regarded as clinically important? Br J Clin Pharmacol 1994;37:125-128.
- Tett SE, Kirkpatrick CM, Gross AS, McLachlan AJ. Principles and clinical application of assessing alterations in renal elimination pathways. Clin Pharmacokinet 2003;42:1193-1211.
- Burckhardt G, Wolff NA, Bahn A. Molecular characterization of the renal organic anion transporter 1. Cell Biochem Biophys 2002;36:169-174.
MONOGRAPH: Drug-to-drug interactions represent one of the most significant risks of polypharmacy in our increasingly complex and aging populations.
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