How are drug metabolism and detection related?

How are drug metabolism and detection related?

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If someone is taking treatment for a psychiatric disorder (e.g. diazepine), then would traces of the metabolized drug be detectable in their sweat or saliva?

Any links to resources regarding this, or any help is greatly appreciated!

Short answer: Yes.

Diazepine is a ring-structure that forms the basis for the class of drugs called benzodiazepines. This class includes long acting and short acting agents. If you're actually talking about diazepam, it's one of the long acting agents, which means the half-life of the metabolite in your body (and it's detection) is long.

The National Highway Traffic Safety Administration has good reasons to want to collect samples of various drugs non-invasively, and, indeed, they're headed toward saliva for screening. A neat little item called a Drugwipe can pick up traces of diazepam from not only saliva and sweat, but from surfaces people have touched.*

The real kicker, though, is hair, from any part of your body. Drug use(including diazepam) can be detected in hair for months after (even single) use, and many employers are now going for hair sample testing to screen for drug use.

*Saliva and Sweat Testing With Drugwipe®.

Welcome To Current Drug Metabolism

Current Drug Metabolism aims to cover all the latest and outstanding developments in drug metabolism and disposition. The journal serves as an international forum for the publication of timely reviews and guest edited issues in drug metabolism. Current Drug Metabolism is an essential journal for academic, clinical, government and pharmaceutical scientists who wish to be kept informed and up-to-date with the latest and most important developments. The journal covers the following areas:

More specifically, in vitro and in vivo drug metabolism of phase I and phase II enzymes or metabolic pathways drug-drug interactions and enzyme kinetics pharmacokinetics, pharmacokinetic-pharmacodynamic modeling, and toxicokinetics interspecies differences in metabolism or pharmacokinetics, species scaling and extrapolations drug transporters target organ toxicity and interindividual variability in drug exposure-response extrahepatic metabolism bioactivation, reactive metabolites, and developments for the identification of drug metabolites. Preclinical and clinical reviews describing the drug metabolism and pharmacokinetics of marketed drugs or drug classes.

Drug discovery and development is a time-consuming and costly process. Based on the study by the Tufts Center for the Study of Drug Development (2016)1, on average, it takes more than 10 years and over $2.6 billion to develop a new drug. One of the biggest challenges for the pharmaceutical research community is therefore to execute an optimal process for drug discovery and development. Rational drug design represents an approach to expedite such a process with efficiency as one of the primary objectives, combining the latest science and technology to advance medicines rapidly from laboratory bench side to hospital bed side.

The disposition of a drug in the body involves absorption, distribution, metabolism, and excretion (ADME). ADME is an important component in the drug design process, which studies the fate of a drug molecule after administration. It is a complex process involving transporters and metabolizing enzymes with physiological consequences on pharmacological and toxicological effects, and can play a major role in drug design for identifying better drug molecules in a more efficient way. Metabolism of drugs in the body is a complex biotransformation process where drugs are structurally modified to different molecules (metabolites) by various metabolizing enzymes. Studies on drug metabolism are key processes to optimize lead compounds for optimal PK/PD properties, to identify new chemical entities based on the finding of active metabolites, to minimize potential safety liabilities due to formation of reactive or toxic metabolites, and to compare preclinical metabolism in animals with humans for ensuring potential adequate coverage of human metabolites in animals and for supporting human dose prediction, etc.2 This review focuses on the study of drug metabolism as a discipline for its roles in optimizing pharmacokinetics (PK), pharmacodynamics (PD), and safety profiles of drug candidates in drug discovery and development. The impact of protein binding and transporter on PK and PD properties of drug candidates are beyond the scope of this review.


Metabolism refers to the process of biotransformation by which drugs are broken down so that they can be eliminated by the body. Some drugs perform their functions and then are excreted from the body intact, but many require metabolism to enable them to reach their target site in an appropriate amount of time, remain there an adequate time, and then be eliminated from the body. This review refers to opioid metabolism however, the processes described occur with many medications.

Altered metabolism in a patient or population can result in an opioid or metabolite leaving the body too rapidly, not reaching its therapeutic target, or staying in the body too long and producing toxic effects. Opioid metabolism results in the production of both inactive and active metabolites. In fact, active metabolites may be more potent than the parent compound. Thus, although metabolism is ultimately a process of detoxification, it produces intermediate products that may have clinically useful activity, be associated with toxicity, or both.

Opioids differ with respect to the means by which they are metabolized, and patients differ in their ability to metabolize individual opioids. However, several general patterns of metabolism can be discerned. Most opioids undergo extensive first-pass metabolism in the liver before entering the systemic circulation. First-pass metabolism reduces the bioavailability of the opioid. Opioids are typically lipophilic, which allows them to cross cell membranes to reach target tissues. Drug metabolism is ultimately intended to make a drug hydrophilic to facilitate its excretion in the urine. Opioid metabolism takes place primarily in the liver, which produces enzymes for this purpose. These enzymes promote 2 forms of metabolism: phase 1 metabolism (modification reactions) and phase 2 metabolism (conjugation reactions).

Phase 1 metabolism typically subjects the drug to oxidation or hydrolysis. It involves the cytochrome P450 (CYP) enzymes, which facilitate reactions that include N-, O-, and S-dealkylation aromatic, aliphatic, or N-hydroxylation N-oxidation sulfoxidation deamination and dehalogenation. Phase 2 metabolism conjugates the drug to hydrophilic substances, such as glucuronic acid, sulfate, glycine, or glutathione. The most important phase 2 reaction is glucuronidation, catalyzed by the enzyme uridine diphosphate glucuronosyltransferase (UGT). Glucuronidation produces molecules that are highly hydrophilic and therefore easily excreted. Opioids undergo varying degrees of phase 1 and 2 metabolism. Phase 1 metabolism usually precedes phase 2 metabolism, but this is not always the case. Both phase 1 and 2 metabolites can be active or inactive. The process of metabolism ends when the molecules are sufficiently hydrophilic to be excreted from the body.


Most cannabinoids are lipophilic (fat soluble) compounds that easily store in fat, thus yielding a long elimination half-life relative to other recreational drugs. The THC molecule, and related compounds, are usually detectable in urine drug tests from 3 days up to 10 days according to Redwood Laboratories heavy users can produce positive tests for 30 days or longer after ceasing cannabis use. [1] [2] The length of time may vary to some degree according to metabolism, quantity, and frequency of use. [ citation needed ]

Urine testing Edit

Marijuana use can be detected up to 3–5 days after exposure for infrequent users for heavy users: 1–15 days for chronic users and/or users with high body fat: 1–30 days [3] [4]

Under the typical 50 ng/mL cutoff for THC in the United States, an occasional or on-off user would be very unlikely to test positive beyond 3–4 days since the last use, and a chronic user would be unlikely to test positive much beyond 7 days. Using a more sensitive cutoff of 20 ng/mL (less common but still used by some labs), the most likely maximum times are 7 days and 21 days, respectively. In extraordinary circumstances of extended marijuana use, detection times of more than 30 days are possible in some individuals at the 20 ng/mL cutoff. [5]

However, every individual is different, and detection times can vary due to metabolism or other factors. It also depends on whether actual THC or THC metabolites are being tested for, the latter having a much longer detection time than the former. THC (found in marijuana) may only be detectable in saliva/oral fluid for 2–24 hours in most cases. [ citation needed ]

The main metabolite excreted in the urine is 11-nor-delta9-tetrahydrocannabinol-9-carboxylic acid (delta9-THC-COOH). Most THC drug tests yield a positive result when the concentration of marijuana in urine exceeds 50 ng/mL. [6] Urine Testing is an immunoassay based test on the principle of competitive binding. Drugs which may be present in the urine specimen compete against their respective drug conjugate for binding sites on their specific antibody. During testing, a urine specimen migrates upward by capillary action. A drug, if present in the urine specimen below its cut-off concentration, will not saturate the binding sites of its specific antibody. The antibody will then react with the drug-protein conjugate and a visible colored line will show up in the test line region of the specific drug strip. [ citation needed ]

Cannabis use is included in the "10-panel urine screen", as well as the "SAMHSA-5", the five drugs tested for in standard NIDA approved drug tests.

False positives have been known to be triggered by consuming hemp-seed bars, low THC cannabis and CBD supplements, although the more detailed, more expensive gas chromatography-mass spectrometer (GCMS) test can tell the difference.

In 2011, researchers at John Jay College of Criminal Justice reported that dietary zinc supplements can mask the presence of THC and other drugs in urine. Similar claims have been made in web forums on that topic. [7] However, a 2013 study conducted by researchers at the University of Utah School of Medicine refute the possibility of self-administered zinc producing false-negative urine drug tests. [8]

Common known pharmaceutical drugs which cause false positives in instant THC dip tests include:

Duquenois–Levine reagent Edit

The Duquenois–Levine test is a simple chemical color reaction test initially developed in the 1930s by Pierre Duquénois.

To administer the test, a police officer simply has to break a seal on a tiny micropipette of chemicals, and insert a particle of the suspected substance if the chemicals turn purple, this indicates the possibility of marijuana. But the color variations can be subtle, and readings can vary by examiner.

It was adopted in the 1950s by the United Nations as the preferred test for cannabis.

Drug metabolism

The primary objective of drug metabolism is to facilitate a drug’s excretion by increasing its water solubility (hydrophilicity). The involved chemical modifications incidentally decrease or increase a drug’s pharmacological activity and/or half-life, the most extreme example being the metabolic activation of inactive prodrugs into active drugs, e.g. of codeine into morphine by CYP2D6. The principal organs of drug metabolism are the liver and (for orally taken drugs) the small intestine. Drugs completely inactivated during the first-pass through these organs must be given parenterally, similarly to poorly absorbed drugs.

Hepato-intestinal drug metabolism is highly variable not only among patients but even in one particular individual over time. It is lower immediately after birth, in carriers of inactivating mutations in drug metabolizing enzymes, in patients treated with drugs inhibiting these enzymes (e.g. macrolids and conazols), and in those with liver disease or insufficient hepatic blood flow. It is higher in patients treated with transcriptional inducers of drug metabolizing enzymes, e.g. with rifampin or carbamazepine and, in the case of CYP2D6, in the presence of additional gene copies. The induction and inhibition of drug metabolism constitute examples of pharmacokinetic drug interactions. As drug metabolizing enzymes also metabolize certain endobiotics, induction and inhibition may result in metabolic disorders.

Drug metabolizing enzymes have evolved primarily as a defense against non-medical chemicals taken up from the environment. They are therefore expressed also at other interfaces of the body with the environment such as the skin, lungs, and the kidney. The contribution of these organs to drug metabolism is incompletely understood, but certainly much smaller.

The principal effectors of drug metabolism are the cytochrome P450 (CYP450) enzymes.

Phases of drug metabolism

The usual classification of drug metabolism enzymes and reactions as Phase I or II is somewhat misleading, as these reactions affect some drugs in a reverse order (Phase II followed by Phase I, e.g. isoniazid) or separately (Phase I or Phase II). Type I and II would be therefore more appropriate. Note that some drugs (e.g. metformin) are not metabolized at all.

The most important difference between Phase I and II reactions is that the former one is molecule-autonomous whereas the latter one creates a covalent bond with another molecule or its part. Further, unlike Phase I, Phase II reactions almost invariably inactivate a given drug.

Most Phase I reactions are carried out by just several wide-spectrum monooxygenases of the CYP (cytochrome P450) subfamilies 1-3. The most important drug metabolizing enzyme is CYP3A4. Phase I reactions usually convert the parent drug to a more polar metabolite via the formation of –OH, -NH2, or –SH groups. Insufficiently polar drugs may be subsequently (or primarily) modified by Phase II enzymes. Phase I modifications may facilitate Phase II reactions. The most frequent Phase II reactions are conjugations with glucuronic acid. Drugs can be also conjugated with glutathione or glycine, or modified by the transfer of methyl, acetyl, or sulpha groups from donor compounds.

This web page provides a brief overview of the drug metabolism process, rate of metabolism, the cytochrome P450 enzymes of Phase I reactions and the effects of Phase II conjugation reactions. The information was written by Jennifer Le, PharmD, MAS, BCPS-ID.

The usual classification of drug metabolism enzymes and reactions as Phase I or II is somewhat misleading, as these reactions affect some drugs in a reverse order (Phase II followed by Phase I, e.g. isoniazid) or separately (Phase I or Phase II). Type I and II would be therefore more appropriate. Note that some drugs (e.g. metformin) are not metabolized at all.

The most important difference between Phase I and II reactions is that the former one is molecule-autonomous whereas the latter one creates a covalent bond with another molecule or its part. Further, unlike Phase I, Phase II reactions almost invariably inactivate a given drug.

Most Phase I reactions are carried out by just several wide-spectrum monooxygenases of the CYP (cytochrome P450) subfamilies 1-3. The most important drug metabolizing enzyme is CYP3A4. Phase I reactions usually convert the parent drug to a more polar metabolite via the formation of –OH, -NH2, or –SH groups. Insufficiently polar drugs may be subsequently (or primarily) modified by Phase II enzymes. Phase I modifications may facilitate Phase II reactions. The most frequent Phase II reactions are conjugations with glucuronic acid. Drugs can be also conjugated with glutathione or glycine, or modified by the transfer of methyl, acetyl, or sulpha groups from donor compounds.

1.5 Molecular Features of Importance for Transporter Interactions: Substrates Versus Inhibitors

Many substrates and inhibitors have been identified for transporters that are of importance for drug distribution into and out of cells. For a selection of these, see Table 1.5. While a substrate of the transporter can also be an inhibitor of the transport protein and block transport of other compounds, compounds that have been identified as inhibitors may not be transported. The latter is related to the inactivation of the transport protein by binding to sites other than the one crucial for mediating transport. Interaction with the transport-mediating site allows the drug compound (or its metabolite) to traverse the lipophilic membrane. Hence, the molecular requirements of the different transporters have been studied to better understand what physicochemical properties of a compound will result in them being actively transported by a particular transport protein. While metabolism is a chemical reaction that turns a substrate into a product that is chemically different, the substrates of transport proteins remain the same no chemical reaction occurs. However, the terminology of transporters and experimental procedures to study transport have been inspired by those in the metabolism field. So, for example, the Michaelis–Menten equation is often used to describe the efficiency of transporters to flux compounds across the membrane.

Transporters Gut Liver Selected substrates Selected inhibitors
ASBT (SLC10A2) X Bile salts Cyclosporin A
MCT1 (SLC16A1) X Nateglinide Nateglinide
NTCP (SLC10A1) X Bile salts Bumetanide, chlorpropamide, cyclosporin A, furosemide, ketoconazole, progesterone
OAT2 (SLC22A7) X Methotrexate, tetracycline, theophylline Cefamandole, cefoperazone, cefotaxime, cephaloridine, cephalothin, cilastatin, clarithromycin, erythromycin, ganciclovir, minocycline, oxytetracycline, pravastatin, probenecid
OATP1A2 (SLCO1A2) X Enalapril, fexofenadine, pravastatin, rifampicin Dexamethasone, erythromycin, ketoconazole, lovastatin, naloxone, nelfinavir, quinidine, rifampicin, ritonavir, saquinavir, verapamil
OATP1B1 (SLCO1B1) X Atorvastatin, benzylpenicillin, cerivastatin, irinotecan, methotrexate, pitavastatin, pravastatin, rifampicin, simvastatin Cyclosporin A, indinavir, lovastatin, nelfinavir, pioglitazone, pravastatin, quinidine, rapamycin, ritonavir, rosiglitazone, saquinavir, troglitazone
OATP1B3 (SLCO1B3) X Digoxin, methotrexate, pioglitazone, pitavastatin, rifampicin Rifampicin
OATP2B1 (SLCO2B1) X X Benzylpenicillin, glibenclamide, ibuprofen, fexofenadine, pravastatin, rifampicin, tolbutamide Tangeretin, rifamycin
OCT1 (SLC22A1) X X Acyclovir, cimetidine, cisplatin, ganciclovir Amiloride, chlorpromazine, clonidine, desipramine, disopyramide, metformin, midazolam, prazosin, progesterone, quinidine, ranitidine, verapamil
OCT3 (SLC22A3) X Carboplatin, cimetidine, cisplatin Clonidine, desipramine, imipramine, prazosin, progesterone
OCTN2 (SLC22A5) X Cimetidine, valproic acid Aldosterone, amphetamine, ampicillin, cefadroxil, cefdinir, cefepime, cefixime, cefluprenam, cefoselis, cefsulodin, ceftazidime, cephalexin, cephalothin, clonidine, cyclacillin, desipramine, furosemide, lomefloxacin, norfloxacin, benzylpenicillin, probenecid, verapamil
PEPT1 (SLC15A1) X Benzylpenicillin, cefadroxil, cefixime, ceftibuten, enalapril, faropenem, lisinopril, temocapril, valacyclovir Amoxicillin, ampicillin, captopril, cefadroxil, cefluprenam, cefotaxime, cefpirome, cefsulodin, ceftazidime, ceftriaxone, cefuroxime, cephadroxil, cephalexin, cephaloridine, cloxacillin, cyclacillin, dicloxacillin, glycylsarcosine, l -dopa, metampicillin, moxalactam
BCRP (ABCG2) X X Cerivastatin, daunorubicin, glibenclamide, lamivudine, methotrexate, mitoxantrone, prazosin, pravastatin, tamoxifen, topotecan Cyclosporin A, doxorubicin, nelfinavir, novobiocin, omeprazole, pantoprazole, ritonavir, saquinavir, silybin, silymarin, verapamil
BSEP (ABCB11) X Daunorubicin, doxorubicin, vincristine Chlorpromazine, cimetidine, clofazimine, cyclosporin A, glibenclamide, ketoconazole, paclitaxel, progesterone, quinidine, reserpine, tamoxifen, troglitazone, valinomycin, verapamil, vinblastine
P-gp, MDR1 (ABCB1) X X Acetaminophen, acetylsalicylic acid, albendazole, aldosterone, atenolol, carbamazepine, chlorpromazine, ciprofloxacin, clozapine, cyclosporin A, daunorubicin, diazepam, digoxin, dipyridamole, docetaxel, emetine, fluconazole, flumazenil, fluoxetine, haloperidol, hydrocortisone, ibuprofen, imatinib, ivermectin, ketamine, loperamide, losartan, naloxone, neostigmine, nitrazepam, olanzapine, paclitaxel, quinidine, risperidone, scopolamine, sumatriptan, valinomycin, verapamil, vinblastine Amiodarone, amitriptyline, astemizole, atorvastatin, bromocriptine, buspirone, candesartan, captopril, cimetidine, clarithromycin, clofazimine, clotrimazole, desipramine, desloratadine, dexamethasone, diclofenac, erythromycin, felodipine, fentanyl, glibenclamide, indinavir, itraconazole, ketoconazole, lidocaine, lopinavir, loratadine, lovastatin, methadone, metoprolol, miconazole, morphine, nelfinavir, nicardipine, nifedipine, norverapamil, omeprazole, pantoprazole, ranitidine, reserpine, ritonavir, saquinavir, simvastatin, sirolimus, spironolactone, tamoxifen, terfenadine, verapamil, vincristine
MRP2 (ABCC2) X X Cerivastatin, etoposide, indinavir, methotrexate, pravastatin, ritonavir, saquinavir, vinblastine, vincristine Benzbromarone, cyclosporin A, daunorubicin, furosemide, lovastatin acid, probenecid, quinidine, reserpine, sulfinpyrazone, verapamil
MRP3 (ABCC3) X X Etoposide, glibenclamide, glutathione, methotrexate Benzbromarone, doxorubicin, indomethacin, probenecid, verapamil, vincristine
MRP4 (ABCC4) X Adefovir, methotrexate Benzbromarone, celecoxib, diclofenac, dipyridamole, ibuprofen, indomethacin, indoprofen, ketoprofen, probenecid, rofecoxib, sildenafil, verapamil
MRP6 (ABCC6) X Cisplatin, daunorubicin, doxorubicin, etoposide, teniposide Benzbromarone, indomethacin, probenecid, sulfinpyrazone
a Data on clinically relevant transporters were taken from ref. 70–73. Representative examples of substrates and inhibitors for each of the transport proteins were extracted from the database established by Prof. Sugiyama ( Substrates also being identified as inhibitors are not listed. Note that inhibitors listed may be substrates but to date only data on inhibition are available in the open literature.

The structural requirements for transport by influx and efflux transport proteins have been heavily studied. The majority of studies have been directed towards investigation of transport protein inhibition. The reason for this is mainly methodological issues associated with substrate assays. While analyses of molecular features of substrates require determination of the intracellular concentration of a large number of compounds, inhibition assays rely on screening a large number of compounds for their inhibition of the transport of one substrate. Hence, analytical demands for the latter are reduced and a higher throughput mode is possible. The most important transport proteins for clearance are discussed below.

1.5.1 Efflux Proteins P-gp Substrate Recognition Pattern

One of the most studied transport proteins is the efflux protein P-gp since it is important for drug distribution to several tissues, including the gut and liver. Drug–drug interactions (DDIs) have also been identified that are mediated by P-gp. Among the most well known are those that occur between digoxin and the P-gp inhibitors amiodarone, cyclosporin A, quinine and verapamil. 50 Seelig and coworkers were pioneers in the study of the recognition pattern of P-gp (cf. 51,52 ). Based on studies of ∼100 compounds, they suggested that a special spatial separation of electron donor groups is required for compounds to be transported by P-gp. Their work was followed by a number of structure–activity relationship (SAR) studies in which P-gp substrates are predicted on the basis of chemical information calculated from the molecular structure. The SAR models are typically classification models used to distinguish compounds that are substrates from those that are not transported by the P-gp. One classification model used the sum of atomic electrotopological states (MolES), a descriptor of molecular bulkiness, to predict substrates. 53 Compounds with a MolES >110 are regarded as substrates for P-gp whereas a MolES <49 indicates non-substrates. For compounds with a value between 49 and 110 other descriptors are needed to identify whether they would be substrates. 53 A similar study using a classification approach established the rule of four. 54 This rule states the following: compounds with (N + O) ≥ 8, molecular weight > 400 and acid pKa > 4 are likely to be P-gp substrates. Compounds with (N + O) ≤ 4, molecular weight < 400 and base pKa < 8 are likely to be non-substrates. Both of these SAR studies identified that P-gp transports larger molecules. Furthermore, it seems that compounds with many hydrogen bonds, and to some extent negative charges, are transportable by P-gp. The non-substrates have fewer hydrogen bond acceptors and are neutral, or at least not highly positively charged. The importance of N and O demonstrated by this study confirms the work by Seelig and colleagues. Finally, P-gp substrates are amphipathic and lipophilic. 55 It has been suggested that the substrate binding pocket sits inside the cellular membrane and needs to be accessed by distribution into the lipid bilayer. 56–58 Based on this, the lipophilic and amphiphilic nature of the substrates is to be expected. Inhibition of P-gp, BCRP, MRPs, BSEP: Specificity and Overlap

While it is important to understand molecular features that result in substances being substrates to efflux proteins, it is also of interest to look at which molecular features lead to inhibition of transport. Inhibition may result in severe DDIs. Inhibitors may be competitive (they bind to the same binding site as the substrate) or non-competitive (they bind to another site on the transport protein and thereby block the transport). Therefore, a substrate may inhibit the transport of another substrate, and an inhibitor is not necessarily transported by the protein. Artursson and colleagues have explored large compound series to identity inhibitors of the transport proteins most important for drug disposition. They identified specific molecular requirements of the different transporters and the extent to which the molecular requirements for inhibition of these transporters overlap. For example, the ABC transporters P-gp, breast cancer resistance protein (BCRP), multidrug resistance-associated protein 2 (MRP2) and bile salt export pump (BSEP), all of which are expressed in the canalicular membrane of the hepatocyte, have a significant overlap of inhibitors, i.e. the same compound may block several of these transporters at the same time. The impact on drug clearance, for instance from hepatocytes to bile, may therefore be greatly affected. Such inhibition may also result in reduced enterohepatic recycling of endogenous substances such as bile acids and bilirubin, which can result in, among others, fatal cholestasis. 59 In a study of 122 compounds, all tested for their inhibition of P-gp, BCRP and MRP2, molecular features of specific inhibitors (interacting with only one of the transporters) and of those that interacted with all three transporters were identified. 60 The inhibitors of P-gp were lipophilic, non-polar and had higher structure connectivity. BCRP inhibitors were also more lipophilic than non-inhibitors and the number of aromatic rings correlated positively with inhibition. Inhibitors of MRP2 had similar properties lipophilicity and unsaturated bonds (double bonds) positively correlated with inhibition, as did shape. Thus, inhibitors of P-gp, BCRP and MRP2 are all lipophilic and aromatic, but to different degrees. The specific inhibitors of P-gp are less aromatic than those of MRP2 and BCRP, and the BCRP inhibitors generally have more aromatic nitrogens than the P-gp inhibitors. P-gp inhibitors are the most lipophilic (logDpH7.4 of 2.3) followed by BCRP (logDpH7.4 of 1.9) and MRP2 (logDpH7.4 of 1.2). By contrast, multi-specific inhibitors, i.e. compounds that inhibit all three proteins, are 100- to 1000-fold more lipophilic (logDpH7.4 of 4.5). 60

Another study investigated 250 compounds for their inhibition of BSEP. Of the 86 inhibitors identified, 58% were neutral at physiological pH, 36% were negatively charged and only 6% were positively charged. By contrast, BSEP substrates are typically monovalent, negatively charged bile acids. BSEP inhibition is also favored by lipophilicity, hydrophobicity and number of halogens. Reciprocally, hydrophilicity and hydrogen bond acceptors negatively correlate with inhibition. 61

1.5.2 Uptake Transporters Inhibition of OATP1B1, OATP1B3, OATP2B1: Specificity and Overlap

There are a number of studies on the inhibition of OATP uptake transporters, particularly OATP1B1 (which is the most important hepatic OATP). Two studies by Karlgren et al. investigated the inhibition of OATP1B1 by 146 compounds and the inhibition of OATP1B1, OATP1B3 and OATP2B1 by 225 compounds. 62,63 In both studies, a significantly larger proportion of the inhibitors were negatively charged compounds compared with the non-inhibitors. This is not surprising given that OATPs are known to primarily transport anionic drugs. Furthermore, these studies showed that compared with the non-inhibitors, the OATP inhibitors had a significantly higher lipophilicity (mean NNLogP of 3.6–4.0 vs. 2.3–2.7), larger molecular weight (mean weight of 481–514 vs. 325–336 g mol −1 ) and a larger polar surface area (PSA mean PSA of 115–142 vs. 66–74 Å 2 ). 62,63 OATP1B1 inhibitors also displayed a lower mean square distance index (MSD), a topological distance descriptor normalized for size. 63 Inhibitors of OATP1B3—but not of OATP1B1 and OATP2B1—had more hydrogen bond donors than the non-inhibitors, whereas the OATP2B1 inhibitors were less dependent on polarity than those of OATP1B1 and OATP1B3. 62 These findings were confirmed by an in vitro study of 2000 compounds on OATP1B1 and OATP1B3. 64 It was also found that a low number of aromatic bonds (<7) correlated positively with OATP1B1 inhibition but negatively with OATP1B3 inhibition, whereas a logD value of >7.5 and 3–4 hydrogen bond donors correlated positively with OATP1B3 inhibition. Interestingly, due to the high number of compounds investigated, they could also identify substructures that favored inhibition of a specific transporter or favored inhibition of both OATP1B transporters.

The three OATP transporters share many inhibitors. Two examples are atazanavir and ritonavir, which are considered general OATP inhibitors. 62 In one study of 91 identified inhibitors, 42 were common for OATP1B1 and OATP1B3. Of these 42 inhibitors, 16 did not inhibit OATP2B1. By contrast, only 9 of the inhibitors were identified as inhibitors of OATP1B1 and OATP2B1 but not OATP1B3. Only one compound, nefazodone, interacted with both OATP1B3 and OATP2B1 but did not inhibit OATP1B1.

Many of the compounds identified as inhibitors of the OATP transporters are also inhibitors or substrates of other transporters or metabolizing enzymes. For example, the FDA and/or the European Medicines Agency (EMA) list that 67 of the 225 compounds included in the studies above are substrates, inhibitors or inducers of CYP enzymes. Of these 67 compounds, 21 compounds were also identified as inhibitors of one or more OATP transporters. 62 The largest overlap was for OATPs and CYP2C8, followed by OATPs and CYP3A4. Previously it was suggested that there was a substrate overlap between OATP1B1 and the efflux transporter MRP2. 65 However, an investigation of common inhibitors of OATP1B1 and MRP2 found no such corresponding overlap of inhibitors. 63 Inhibition of OCT1

Organic cation transporter 1 (OCT1) is the major cationic uptake transporter in the liver. An investigation of 191 compounds identified 62 as inhibitors of OCT1. 66 These inhibitors tended to be positively charged (66%) or neutral (32%) at physiological pH. They were more lipophilic (mean ClogP of 3.50 vs. 1.43), had a lower PSA (mean PSA of 42.9 vs. 95.5), and a lower number of both hydrogen bond donors (1.07 vs. 2.66) and acceptors (3.38 vs. 5.09) than the non-inhibitors. 66 These results agree with a previous study of OCT1 inhibition that used a more homogeneous dataset (n = 30). 67 The results also support previous observations that a positive charge is important for interactions with the OCT1 transporter. 68,69

1.3. Enzymes in hepatocytes

The most important hepatic enzymes are the cytochrome P450 (CYP450) superfamily. The CYP450s are a diverse group of heameproteins that catalyse the oxidation of endogenous and exogenous substances. They are primarily membrane-associated proteins, concentrated in the smooth endoplasmic reticulum of the liver and play a pivotal role in phase I biotransformation, in which a drug is either activated or inactivated by one of three types of reactions oxidation, reduction or hydrolysis (Ingelman-Sundberg, 2004). In a typical phase I reaction, a CYP450 enzyme requires both oxygen and a reducing agent (NADH) to add or unmask a reactive functional group, such as a -OH, -COOH, NH2 or SH. Subsequently reactive molecules are produced which may be inactive, have more active enhanced activity or more toxic than the parent drug.

The Evolving Role of Drug Metabolism in Drug Discovery and Development

Drug metabolism in pharmaceutical research has traditionally focused on the well-defined aspects of absorption, distribution, metabolism and excretion, commonly-referred to ADME properties of a compound, particularly in the areas of metabolite identification, identification of drug metabolizing enzymes (DMEs) and associated metabolic pathways, and reaction mechanisms. This traditional emphasis was in part due to the limited scope of understanding and the unavailability of in vitro and in vivo tools with which to evaluate more complex properties and processes. However, advances over the past decade in separate but related fields such as pharmacogenetics, pharmacogenomics and drug transporters, have dramatically shifted the drug metabolism paradigm. For example, knowledge of the genetics and genomics of DMEs allows us to better understand and predict enzyme regulation and its effects on exogenous (pharmacokinetics) and endogenous pathways as well as biochemical processes (pharmacology). Advances in the transporter area have provided unprecedented insights into the role of transporter proteins in absorption, distribution, metabolism and excretion of drugs and their consequences with respect to clinical drug–drug and drug–endogenous substance interactions, toxicity and interindividual variability in pharmacokinetics. It is therefore essential that individuals involved in modern pharmaceutical research embrace a fully integrated approach and understanding of drug metabolism as is currently practiced. The intent of this review is to reexamine drug metabolism with respect to the traditional as well as current practices, with particular emphasis on the critical aspects of integrating chemistry and biology in the interpretation and application of metabolism data in pharmaceutical research.

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Prediction of Drug Metabolism and Interactions on the Basis of in vitro Investigations

Author for correspondence: Olavi Pelkonen, Department of Pharmacology & Toxicology, University of Oulu, POB 5000, FIN-90014 Oulu, Finland (fax +358 8537 5247, e-mail [email protected] ).Search for more papers by this author

Department of Pharmacology and Toxicology, University of Oulu, Box 5000, FIN-90014 Oulu,

Department of Chemistry, University of Oulu, Box 3000, FIN-90014 Oulu, Finland

Department of Pharmacology and Toxicology, University of Oulu, Box 5000, FIN-90014 Oulu,

Department of Pharmacology and Toxicology, University of Kuopio, Box 1627, FIN-70211 Kuopio and

Department of Pharmacology and Toxicology, University of Oulu, Box 5000, FIN-90014 Oulu,

Author for correspondence: Olavi Pelkonen, Department of Pharmacology & Toxicology, University of Oulu, POB 5000, FIN-90014 Oulu, Finland (fax +358 8537 5247, e-mail [email protected] ).Search for more papers by this author

Department of Pharmacology and Toxicology, University of Oulu, Box 5000, FIN-90014 Oulu,

Department of Chemistry, University of Oulu, Box 3000, FIN-90014 Oulu, Finland

Department of Pharmacology and Toxicology, University of Oulu, Box 5000, FIN-90014 Oulu,

Department of Pharmacology and Toxicology, University of Kuopio, Box 1627, FIN-70211 Kuopio and


Abstract: Drug metabolism profoundly affects drug action, because almost all drugs are metabolised in the body and thus their concentrations and elimination rates are dependent on metabolic activity. Drug metabolism contributes substantially to interindividual differences in drug response and is also often involved in drug interactions, resulting in either therapeutic failure or adverse effects. Knowledge about the metabolism of a new chemical entity and its affinity to drug-metabolising enzymes helps in the drug development process by providing important information for the selection of a lead compound from among a number of substances pharmacologically equally effective in their therapeutic response. In drug development protocols, metabolism characteristics should be assessed very early during the development process. This has been made possible by the advances made especially in analytical capabilities and in in vitro technologies that are employed to predict in vivo metabolite profile, pharmacokinetic parameters and drug-drug interaction potential.


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