View Categories

Pharmacology Overview

33 min read

Introduction #

Pharmacology is the science of drug actions on biological systems, encompassing pharmacokinetics (what the body does to drugs) and pharmacodynamics (what drugs do to the body). Understanding fundamental pharmacologic principles is essential for rational drug therapy, predicting drug interactions, and managing adverse effects [1]. This review synthesizes high-yield concepts in general pharmacology.

Pharmacokinetics #

Absorption

Drug absorption is the process by which drugs enter the systemic circulation from the site of administration [2]. Bioavailability represents the fraction of administered drug reaching systemic circulation unchanged, with intravenous administration having 100% bioavailability by definition [3]. Oral bioavailability is reduced by incomplete absorption, first-pass metabolism in intestinal epithelium and liver, and chemical degradation in the gastrointestinal tract [4].

Passive diffusion is the primary mechanism for most drugs, following Fick’s law with rate proportional to concentration gradient and lipid solubility [5]. The Henderson-Hasselbalch equation predicts drug ionization based on pH and pKa, with non-ionized forms crossing membranes more readily [6]. Weak acids (aspirin) are better absorbed in acidic gastric pH, while weak bases (morphine) favor alkaline intestinal pH [7]. Active transport involves carrier-mediated processes requiring energy, exhibiting saturation kinetics and competitive inhibition, exemplified by levodopa absorption via large neutral amino acid transporter [8].

Factors affecting absorption include gastric emptying time, intestinal motility, splanchnic blood flow, food interactions, and pharmaceutical formulation [9]. First-pass effect significantly reduces bioavailability for drugs with extensive hepatic metabolism, including nitroglycerin, morphine, propranolol, and lidocaine [10].

Distribution

Drug distribution describes reversible transfer from systemic circulation to tissues, influenced by blood flow, tissue binding, and lipid solubility [11]. Volume of distribution (Vd) relates total drug amount to plasma concentration, with small Vd indicating plasma confinement and large Vd suggesting extensive tissue distribution [12]. Highly protein-bound drugs (warfarin, phenytoin) have small Vd, while lipophilic drugs (chloroquine, digoxin) demonstrate large Vd [13].

Plasma protein binding primarily involves albumin for acidic drugs and α1-acid glycoprotein for basic drugs, with only unbound (free) drug being pharmacologically active [14]. Drug displacement from protein binding sites increases free drug concentration, potentially causing toxicity for highly protein-bound drugs with narrow therapeutic indices [15].

Special barriers restrict drug distribution to certain compartments [16]. The blood-brain barrier, formed by tight junctions between cerebral endothelial cells, limits entry to lipophilic molecules and those with specific transporters [17]. Lipid-soluble drugs (diazepam, barbiturates) readily cross, while polar drugs (gentamicin) have minimal CNS penetration [18]. The placental barrier allows lipophilic drugs to reach fetal circulation, with considerations for teratogenicity and fetal effects [19]. P-glycoprotein, an ATP-dependent efflux pump, actively removes drugs from brain, placenta, and intestinal epithelium, affecting distribution of substrates including digoxin, cyclosporine, and chemotherapeutic agents [20].

Metabolism

Drug metabolism converts lipophilic compounds to more polar, water-soluble metabolites facilitating excretion, primarily occurring in hepatic smooth endoplasmic reticulum [21]. Phase I reactions introduce or expose functional groups through oxidation, reduction, or hydrolysis, often mediated by cytochrome P450 enzymes [22]. Phase II reactions conjugate drugs with endogenous substrates (glucuronic acid, sulfate, acetate, glutathione) producing highly polar metabolites [23].

The cytochrome P450 superfamily comprises the primary drug-metabolizing enzymes, with CYP3A4, CYP2D6, CYP2C9, CYP2C19, and CYP1A2 responsible for metabolism of most drugs [24]. Enzyme induction increases enzyme synthesis, requiring days to weeks for effect and persisting after inducer withdrawal [25]. Common inducers include rifampin, phenytoin, carbamazepine, phenobarbital, St. John’s wort, and chronic alcohol use, decreasing drug efficacy through enhanced metabolism [26]. Enzyme inhibition occurs rapidly through competitive, non-competitive, or mechanism-based (suicide) inhibition [27]. Important inhibitors include cimetidine, ketoconazole, erythromacin, grapefruit juice, and acute alcohol use, potentially causing drug toxicity through accumulation [28].

Genetic polymorphisms in cytochrome P450 enzymes create phenotypic variability in drug metabolism [29]. CYP2D6 polymorphisms classify individuals as ultrarapid, extensive (normal), intermediate, or poor metabolizers, affecting drugs including codeine, tramadol, metoprolol, and tricyclic antidepressants [30]. CYP2C19 polymorphisms influence clopidogrel activation, with poor metabolizers having reduced antiplatelet effects and increased cardiovascular events [31].

Prodrugs are inactive compounds requiring metabolic conversion to active forms, including enalapril to enalaprilat, codeine to morphine, and levodopa to dopamine [32]. First-pass metabolism may activate prodrugs before systemic distribution or inactivate parent compounds, affecting therapeutic efficacy [33].

Excretion

Renal excretion represents the primary elimination route for most drugs and metabolites through glomerular filtration, active tubular secretion, and passive tubular reabsorption [34]. Glomerular filtration is passive, determined by molecular size and protein binding, with only unbound drug filtered [35]. Active tubular secretion involves organic anion transporters (OAT) and organic cation transporters (OCT), with capacity for saturation and competition [36]. Probenecid competitively inhibits penicillin secretion, prolonging antibiotic effects [37]. Passive tubular reabsorption favors non-ionized, lipid-soluble drugs, influenced by urinary pH [38].

Urinary pH manipulation alters drug excretion through ion trapping [39]. Alkalinization with sodium bicarbonate enhances weak acid elimination (aspirin, methotrexate, phenobarbital) by increasing ionized species, while acidification with ammonium chloride promotes weak base excretion (amphetamines, phencyclidine) [40]. Renal impairment necessitates dose adjustments for drugs primarily eliminated unchanged, including aminoglycosides, vancomycin, lithium, and digoxin [41].

Biliary excretion eliminates large molecular weight compounds (>500 Da) and highly polar metabolites into bile, with potential enterohepatic recirculation prolonging drug action [42]. Drugs undergoing significant biliary excretion include rifampin, estrogens, and morphine glucuronides [43].

Pharmacokinetic Models

Zero-order kinetics describes constant drug elimination regardless of concentration, with fixed amount eliminated per unit time, characteristic of saturated enzyme systems [44]. Ethanol, phenytoin (at therapeutic concentrations), and aspirin (at high doses) exhibit zero-order elimination [45]. First-order kinetics represents concentration-dependent elimination with constant fraction eliminated per unit time, describing most drugs [46].

Clearance (CL) is volume of plasma completely cleared of drug per unit time, remaining constant in first-order kinetics [47]. Half-life (t½) is time required for plasma concentration to decrease by 50%, calculated as 0.693 × Vd/CL [48]. Steady state is achieved when drug input equals elimination, occurring after approximately 4-5 half-lives with repeated dosing [49]. Loading dose rapidly achieves therapeutic concentration, calculated as (Vd × target concentration)/bioavailability, while maintenance dose sustains steady state [50].

Time to steady state depends solely on half-life, independent of dose or dosing interval [51]. Doubling the dose doubles steady-state concentration but does not affect time to steady state [52]. Drugs with long half-lives require extended time to reach plateau, potentially necessitating loading doses for rapid therapeutic effect [53].

Pharmacodynamics #

Drug-Receptor Interactions

Receptors are macromolecular components with which drugs interact to produce cellular responses, including membrane receptors, enzymes, ion channels, and carrier molecules [54]. Receptor binding typically follows law of mass action, with drug-receptor complex formation proportional to drug concentration and receptor availability [55].

Affinity describes drug binding strength to receptors, determined by association and dissociation rate constants [56]. Efficacy (intrinsic activity) represents the ability of drug-receptor complex to produce maximal biological response [57]. Potency reflects drug concentration required to produce a given effect, determined by both affinity and efficacy [58]. The dissociation constant (Kd) represents drug concentration producing 50% receptor occupancy, inversely related to affinity [59].

Agonists bind receptors and produce maximal biological response, with full agonists achieving 100% maximal effect and partial agonists producing submaximal response even at full receptor occupancy [60]. Antagonists bind receptors without producing response, blocking agonist effects [61]. Competitive antagonists bind reversibly to active site, causing parallel rightward shift in dose-response curve without reducing maximal response, with effects overcome by increasing agonist concentration [62]. Non-competitive antagonists bind irreversibly or at allosteric sites, reducing maximal response with curve shifted rightward and downward [63].

Inverse agonists bind constitutively active receptors and reduce basal activity below baseline, distinguished from neutral antagonists that block both agonist and inverse agonist effects without intrinsic activity [64].

Dose-Response Relationships

Graded dose-response curves plot drug effect against concentration, characterized by potency (EC50, concentration producing 50% maximal effect) and efficacy (maximal effect) [65]. The therapeutic index (TI) compares median toxic dose (TD50) to median effective dose (ED50), calculated as TD50/ED50, with higher values indicating greater safety margin [66]. The therapeutic window represents range between minimum effective concentration and minimum toxic concentration [67].

Quantal dose-response curves describe all-or-none responses in populations, plotting percentage of individuals responding versus dose [68]. The median effective dose (ED50) produces desired effect in 50% of population, median toxic dose (TD50) causes toxicity in 50%, and median lethal dose (LD50) causes death in 50% [69]. Drugs with narrow therapeutic indices (digoxin, warfarin, lithium, phenytoin) require careful monitoring due to small margin between therapeutic and toxic concentrations [70].

Receptor Types

G-protein coupled receptors (GPCRs) represent the largest receptor family, containing seven transmembrane domains coupled to intracellular G-proteins that modulate second messengers [71]. Gs proteins stimulate adenylyl cyclase, increasing cAMP and activating protein kinase A, mediating effects of β-adrenergic agonists and glucagon [72]. Gi proteins inhibit adenylyl cyclase, decreasing cAMP, activated by α2-adrenergic agonists and opioids [73]. Gq proteins activate phospholipase C, generating IP3 and diacylglycerol, mediating α1-adrenergic and M1 muscarinic effects [74].

Ligand-gated ion channels open upon neurotransmitter binding, producing rapid membrane potential changes [75]. Nicotinic acetylcholine receptors are pentameric cation channels producing depolarization, while GABAA receptors are chloride channels mediating inhibition [76]. NMDA receptors are glutamate-gated calcium channels involved in synaptic plasticity and excitotoxicity [77].

Enzyme-linked receptors possess intrinsic enzymatic activity or are directly coupled to enzymes [78]. Receptor tyrosine kinases autophosphorylate upon ligand binding, activating intracellular signaling cascades, exemplified by insulin and growth factor receptors [79]. Cytokine receptors activate JAK-STAT pathways, regulating gene transcription [80].

Intracellular receptors bind lipophilic ligands that cross cell membranes, functioning as transcription factors regulating gene expression [81]. Nuclear hormone receptors mediate effects of steroid hormones, thyroid hormones, vitamin D, and retinoic acid, with responses developing over hours to days [82].

Second Messenger Systems

Cyclic AMP (cAMP) is synthesized by adenylyl cyclase and degraded by phosphodiesterase, activating protein kinase A to phosphorylate cellular proteins [83]. β-adrenergic agonists, glucagon, and histamine (H2) increase cAMP, while α2-agonists and opioids decrease levels [84]. Phosphodiesterase inhibitors (theophylline, milrinone) increase cAMP by preventing degradation [85].

Phospholipase C hydrolyzes phosphatidylinositol 4,5-bisphosphate (PIP2) into IP3 and diacylglycerol [86]. IP3 releases calcium from endoplasmic reticulum, while diacylglycerol activates protein kinase C [87]. α1-adrenergic agonists, M1/M3 muscarinic agonists, and angiotensin II utilize this pathway [88].

Calcium functions as ubiquitous second messenger, regulating muscle contraction, secretion, and enzyme activity through calmodulin [89]. Nitric oxide activates guanylyl cyclase, producing cGMP and causing smooth muscle relaxation, mediating effects of nitrates and sildenafil [90].

Drug Tolerance and Dependence #

Tolerance is decreased drug effect with repeated administration, requiring higher doses to achieve original response [91]. Pharmacokinetic tolerance results from increased drug metabolism through enzyme induction, while pharmacodynamic tolerance involves receptor downregulation, decreased receptor sensitivity, or exhaustion of mediators [92]. Tachyphylaxis represents rapid tolerance development occurring within minutes to hours, exemplified by repeated ephedrine administration depleting norepinephrine stores [93].

Physical dependence is adaptive state requiring continued drug presence to prevent withdrawal symptoms, characterized by rebound hyperactivity of suppressed systems [94]. Opioids, benzodiazepines, barbiturates, and alcohol produce physical dependence with potentially life-threatening withdrawal syndromes [95]. Psychological dependence (addiction) involves compulsive drug-seeking behavior despite harmful consequences, mediated by dopaminergic reward pathways [96].

Cross-tolerance occurs between drugs with similar mechanisms, allowing substitution therapy in managing withdrawal [97]. Benzodiazepines exhibit cross-tolerance with alcohol and barbiturates, enabling use in alcohol withdrawal management [98].

Drug Interactions #

Pharmacokinetic interactions alter drug absorption, distribution, metabolism, or excretion [99]. Absorption interactions include chelation (tetracycline with calcium), altered gastric pH (antacids decreasing ketoconazole absorption), and altered gut flora (antibiotics reducing vitamin K synthesis) [100]. Distribution interactions involve protein binding displacement, increasing free drug concentration of highly bound drugs with narrow therapeutic indices [101]. Metabolic interactions through cytochrome P450 induction or inhibition represent common clinically significant interactions [102]. Excretion interactions include competition for renal tubular secretion (probenecid with penicillin) and altered urinary pH [103].

Pharmacodynamic interactions occur when drugs act at same or different sites, producing additive, synergistic, or antagonistic effects [104]. Additive effects occur when combined response equals sum of individual effects, while synergism produces greater-than-additive response [105]. Antagonism reduces drug effects through direct receptor competition, physiologic antagonism (epinephrine countering histamine), or chemical antagonism (protamine neutralizing heparin) [106].

Adverse Drug Reactions #

Adverse drug reactions are unintended, harmful responses occurring at therapeutic doses, classified as predictable (type A) or unpredictable (type B) [107]. Type A reactions are dose-dependent, related to pharmacologic action, predictable, and common, accounting for 80% of adverse effects [108]. Examples include bleeding with anticoagulants, hypoglycemia with insulin, and sedation with antihistamines [109].

Type B reactions are dose-independent, unrelated to primary pharmacologic action, unpredictable, and rare but potentially severe [110]. Immunologic reactions include immediate hypersensitivity (penicillin anaphylaxis mediated by IgE), antibody-mediated cytotoxicity (methyldopa-induced hemolytic anemia), immune complex disease (serum sickness from antisera), and delayed hypersensitivity (contact dermatitis) [111]. Pseudoallergic reactions mimic hypersensitivity without immunologic mechanism, exemplified by radiocontrast reactions and red man syndrome with vancomycin [112].

Idiosyncratic reactions are genetically determined abnormal responses, including malignant hyperthermia with volatile anesthetics in susceptible individuals (ryanodine receptor mutations), and glucose-6-phosphate dehydrogenase deficiency causing hemolysis with oxidant drugs [113]. Drug-induced organ toxicity includes hepatotoxicity (acetaminophen, isoniazid), nephrotoxicity (aminoglycosides, NSAIDs), cardiotoxicity (doxorubicin, QT prolongation), and bone marrow suppression (chemotherapy agents) [114].

Developmental Pharmacology #

Teratogenesis is drug-induced fetal malformations, with critical periods of vulnerability varying by organ system development [115]. FDA pregnancy categories (replaced by Pregnancy and Lactation Labeling Rule) previously classified drugs from A (safest) to X (contraindicated) based on human and animal studies [116]. Major teratogens include isotretinoin (craniofacial and cardiac defects), thalidomide (limb reduction defects), valproic acid (neural tube defects), warfarin (skeletal abnormalities and CNS defects), ACE inhibitors (renal dysgenesis), and lithium (Ebstein’s anomaly) [117].

Pediatric pharmacology differs from adults due to developmental changes affecting pharmacokinetics and pharmacodynamics [118]. Neonates have decreased gastric acidity, prolonged gastric emptying, and immature blood-brain barrier allowing greater CNS drug penetration [119]. Hepatic metabolism is reduced in neonates, with decreased glucuronidation capacity causing chloramphenicol-induced gray baby syndrome [120]. Renal function is immature, requiring dose adjustments for renally eliminated drugs [121]. Volume of distribution is increased due to higher total body water, affecting loading doses [122].

Geriatric pharmacology involves age-related changes affecting drug disposition and response [123]. Decreased gastric acid and splanchnic blood flow may reduce absorption, while increased adipose tissue increases volume of distribution for lipophilic drugs [124]. Hepatic metabolism declines with reduced liver mass and blood flow, while renal clearance decreases with age-related nephron loss [125]. Altered receptor sensitivity, decreased homeostatic mechanisms, and polypharmacy increase adverse event risk in elderly populations [126].

Clinical Pharmacology Principles #

Therapeutic drug monitoring measures plasma concentrations for drugs with narrow therapeutic indices, significant pharmacokinetic variability, or where clinical response is difficult to assess [127]. Monitoring is essential for digoxin, lithium, theophylline, phenytoin, carbamazepine, valproic acid, vancomycin, and aminoglycosides [128]. Trough levels (immediately before next dose) assess adequacy of dosing interval, while peak levels (shortly after dose) evaluate toxicity risk [129].

Generic substitution replaces brand-name drugs with generic equivalents containing identical active ingredients [130]. Bioequivalence requires generic formulations to demonstrate similar rate and extent of absorption (area under curve and peak concentration within 80-125% of brand) [131]. Narrow therapeutic index drugs may require brand-to-generic substitution caution due to potential clinical consequences of small concentration differences [132].

Rational drug prescribing follows principles of selecting appropriate drug for diagnosed condition, using evidence-based guidelines, individualizing therapy based on patient characteristics, monitoring efficacy and toxicity, and educating patients about proper use [133]. Polypharmacy increases risks of drug interactions, adverse effects, decreased adherence, and medication errors, particularly in elderly patients [134].

Special Populations #

Hepatic disease alters drug metabolism, requiring dose reduction for drugs with high hepatic extraction ratios (first-pass metabolism drugs) and decreased protein synthesis affecting drug binding [135]. Child-Pugh score stratifies cirrhosis severity, guiding dose adjustments [136]. Portosystemic shunting reduces first-pass metabolism, increasing oral bioavailability [137].

Renal disease necessitates dose adjustments based on glomerular filtration rate for renally eliminated drugs and active metabolites [138]. Cockcroft-Gault equation estimates creatinine clearance, while newer equations (MDRD, CKD-EPI) estimate GFR [139]. Dialysis removes drugs based on molecular size, protein binding, and volume of distribution, with supplemental doses required for cleared drugs [140].

Pregnancy alters pharmacokinetics through increased blood volume, cardiac output, and glomerular filtration rate, decreased albumin concentration and gastric emptying, and induction of certain cytochrome P450 enzymes [141]. These changes generally decrease drug concentrations, potentially requiring dose increases for therapeutic effect [142]. Drug selection weighs maternal benefit against fetal risk, avoiding teratogens and choosing drugs with established safety profiles when possible [143].

Drug Development and Regulation #

Drug development progresses through preclinical testing (in vitro and animal studies evaluating pharmacology, toxicology, and pharmacokinetics) followed by clinical trials [144]. Phase I trials assess safety, tolerability, pharmacokinetics, and maximum tolerated dose in small numbers (20-100) of healthy volunteers [145]. Phase II trials evaluate efficacy and optimal dosing in 100-300 patients with target disease [146]. Phase III trials are large randomized controlled trials (1000-3000 patients) comparing new drugs to standard therapy or placebo, providing data for regulatory approval [147]. Phase IV trials represent post-marketing surveillance monitoring adverse effects in larger populations and long-term outcomes [148].

The FDA approval process requires New Drug Application submission with comprehensive preclinical and clinical data demonstrating safety and efficacy [149]. Accelerated approval pathways exist for drugs treating serious conditions with unmet medical needs, based on surrogate endpoints with post-approval confirmatory trials required [150]. Generic drug approval requires demonstration of bioequivalence without repeating clinical trials through Abbreviated New Drug Application [151].

Off-label prescribing involves using approved drugs for indications, populations, or dosages not included in FDA-approved labeling, representing 10-20% of prescriptions and being legal but requiring physician responsibility for evidence-based use [152].

Pharmacogenomics #

Pharmacogenomics studies genetic variations influencing drug response, enabling personalized medicine approaches [153]. Single nucleotide polymorphisms in drug-metabolizing enzymes, transporters, and drug targets affect efficacy and toxicity [154].

Cytochrome P450 polymorphisms significantly impact drug metabolism [155]. CYP2D6 poor metabolizers have increased adverse effects from codeine (lack of analgesic effect due to decreased morphine formation), metoprolol (excessive β-blockade), and tricyclic antidepressants (toxicity) [156]. CYP2C9 polymorphisms affect warfarin metabolism, with slow metabolizers requiring lower maintenance doses [157]. CYP2C19 polymorphisms influence clopidogrel activation, with poor metabolizers having reduced platelet inhibition and increased cardiovascular events [158].

VKORC1 polymorphisms affect warfarin sensitivity through altered vitamin K epoxide reductase, requiring lower doses in certain variants [159]. TPMT polymorphisms cause decreased thiopurine methyltransferase activity, predisposing to severe myelosuppression with azathioprine and mercaptopurine [160]. UGT1A1 polymorphisms reduce glucuronidation capacity, increasing irinotecan toxicity [161]. HLA alleles associate with hypersensitivity reactions, including HLA-B5701 with abacavir, HLA-B1502 with carbamazepine in Asians, and HLA-B*5801 with allopurinol [162].

Pharmacogenetic testing guides drug selection and dosing for warfarin, clopidogrel, abacavir, carbamazepine (in at-risk populations), thiopurines, and irinotecan, though clinical implementation remains variable [163].

Conclusion #

This overview encompasses fundamental pharmacologic principles including pharmacokinetics, pharmacodynamics, drug interactions, adverse reactions, and special population considerations. Mastery of these concepts provides essential foundation for understanding rational therapeutics, predicting drug behavior, and optimizing patient outcomes across all medical specialties.

References #

  1. Brunton LL, Hilal-Dandan R, Knollmann BC. Goodman & Gilman’s: The Pharmacological Basis of Therapeutics, 13th Edition. McGraw-Hill Education. https://doi.org/10.1036/9781259584732
  2. Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics: Concepts and Applications. Wolters Kluwer. https://doi.org/10.1002/phar.1210
  3. Benet LZ, Hosey CM, Ursu O, Oprea TI. BDDCS, the Rule of 5 and drugability. Adv Drug Deliv Rev. 2016;101:89-98. https://doi.org/10.1016/j.addr.2016.05.007
  4. Benet LZ. The drug transporter-metabolism alliance: uncovering and defining the interplay. Mol Pharm. 2009;6(6):1631-1643. https://doi.org/10.1021/mp900253n
  5. Kerns EH, Di L. Drug-like Properties: Concepts, Structure Design and Methods. Academic Press. https://doi.org/10.1016/B978-0-12-369520-8.X0001-X
  6. Manallack DT. The pK(a) Distribution of Drugs: Application to Drug Discovery. Perspect Medicin Chem. 2007;1:25-38. PMID: 19812734
  7. Smith DA, Di L, Kerns EH. The effect of plasma protein binding on in vivo efficacy: misconceptions in drug discovery. Nat Rev Drug Discov. 2010;9(12):929-939. https://doi.org/10.1038/nrd3287
  8. Fernstrom JD, Fernstrom MH. Tyrosine, phenylalanine, and catecholamine synthesis and function in the brain. J Nutr. 2007;137(6 Suppl 1):1539S-1547S. https://doi.org/10.1093/jn/137.6.1539S
  9. Darwich AS, Aslam U, Ashcroft DM, Rostami-Hodjegan A. Meta-analysis of the turnover of intestinal epithelia in preclinical animal species and humans. Drug Metab Dispos. 2014;42(12):2016-2022. https://doi.org/10.1124/dmd.114.058404
  10. Pond SM, Tozer TN. First-pass elimination. Basic concepts and clinical consequences. Clin Pharmacokinet. 1984;9(1):1-25. https://doi.org/10.2165/00003088-198409010-00001
  11. Poulin P, Theil FP. Prediction of pharmacokinetics prior to in vivo studies. 1. Mechanism-based prediction of volume of distribution. J Pharm Sci. 2002;91(1):129-156. https://doi.org/10.1002/jps.10005
  12. Toutain PL, Bousquet-Mélou A. Volumes of distribution. J Vet Pharmacol Ther. 2004;27(6):441-453. https://doi.org/10.1111/j.1365-2885.2004.00602.x
  13. Bohnert T, Gan LS. Plasma protein binding: from discovery to development. J Pharm Sci. 2013;102(9):2953-2994. https://doi.org/10.1002/jps.23614
  14. Trainor GL. The importance of plasma protein binding in drug discovery. Expert Opin Drug Discov. 2007;2(1):51-64. https://doi.org/10.1517/17460441.2.1.51
  15. Rolan PE. Plasma protein binding displacement interactions–why are they still regarded as clinically important? Br J Clin Pharmacol. 1994;37(2):125-128. https://doi.org/10.1111/j.1365-2125.1994.tb04251.x
  16. Pardridge WM. Drug transport across the blood-brain barrier. J Cereb Blood Flow Metab. 2012;32(11):1959-1972. https://doi.org/10.1038/jcbfm.2012.126
  17. Abbott NJ, Patabendige AA, Dolman DE, Yusof SR, Begley DJ. Structure and function of the blood-brain barrier. Neurobiol Dis. 2010;37(1):13-25. https://doi.org/10.1016/j.nbd.2009.07.030
  18. Saunders NR, Habgood MD, Møllgård K, Dziegielewska KM. The biological significance of brain barrier mechanisms: help or hindrance in drug delivery to the central nervous system? F1000Res. 2016;5:313. https://doi.org/10.12688/f1000research.7378.1
  19. Audus KL. Controlling drug delivery across the placenta. Eur J Pharm Sci. 1999;8(3):161-165. https://doi.org/10.1016/s0928-0987(99)00031-7
  20. Lin JH, Yamazaki M. Role of P-glycoprotein in pharmacokinetics: clinical implications. Clin Pharmacokinet. 2003;42(1):59-98. https://doi.org/10.2165/00003088-200342010-00003
  21. Parkinson A, Ogilvie BW. Biotransformation of xenobiotics. In: Casarett & Doull’s Toxicology. McGraw-Hill. https://doi.org/10.1036/0071470514
  22. Guengerich FP. Cytochrome P450 and chemical toxicology. Chem Res Toxicol. 2008;21(1):70-83. https://doi.org/10.1021/tx700079z
  23. Jancova P, Anzenbacher P, Anzenbacherova E. Phase II drug metabolizing enzymes. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2010;154(2):103-116. https://doi.org/10.5507/bp.2010.017
  24. Zanger UM, Schwab M. Cytochrome P450 enzymes in drug metabolism: regulation of gene expression, enzyme activities, and impact of genetic variation. Pharmacol Ther. 2013;138(1):103-141. https://doi.org/10.1016/j.pharmthera.2012.12.007
  25. Kliewer SA, Goodwin B, Willson TM. The nuclear pregnane X receptor: a key regulator of xenobiotic metabolism. Endocr Rev. 2002;23(5):687-702. https://doi.org/10.1210/er.2001-0038
  26. Lynch T, Price A. The effect of cytochrome P450 metabolism on drug response, interactions, and adverse effects. Am Fam Physician. 2007;76(3):391-396. PMID: 17708140
  27. Zhou SF. Drugs behave as substrates, inhibitors and inducers of human cytochrome P450 3A4. Curr Drug Metab. 2008;9(4):310-322. https://doi.org/10.2174/138920008784220664
  28. Bailey DG, Dresser G, Arnold JM. Grapefruit-medication interactions: forbidden fruit or avoidable consequences? CMAJ. 2013;185(4):309-316. https://doi.org/10.1503/cmaj.120951
  29. Zhou SF, Di YM, Chan E, et al. Clinical pharmacogenetics and potential application in personalized medicine. Curr Drug Metab. 2008;9(8):738-784. https://doi.org/10.2174/138920008786049302
  30. Ingelman-Sundberg M, Sim SC, Gomez A, Rodriguez-Antona C. Influence of cytochrome P450 polymorphisms on drug therapies: pharmacogenetic, pharmacoepigenetic and clinical aspects. Pharmacol Ther. 2007;116(3):496-526. https://doi.org/10.1016/j.pharmthera.2007.09.004
  31. Scott SA, Sangkuhl K, Stein CM, et al. Clinical Pharmacogenetics Implementation Consortium guidelines for CYP2C19 genotype and clopidogrel therapy: 2013 update. Clin Pharmacol Ther. 2013;94(3):317-323. https://doi.org/10.1038/clpt.2013.105
  32. Rautio J, Kumpulainen H, Heimbach T, et al. Prodrugs: design and clinical applications. Nat Rev Drug Discov. 2008;7(3):255-270. https://doi.org/10.1038/nrd2468
  33. Huttunen KM, Raunio H, Rautio J. Prodrugs–from serendipity to rational design. Pharmacol Rev. 2011;63(3):750-771. https://doi.org/10.1124/pr.110.003459
  34. Morrissey KM, Stocker SL, Wittwer MB, Xu L, Giacomini KM. Renal transporters in drug development. Annu Rev Pharmacol Toxicol. 2013;53:503-529. https://doi.org/10.1146/annurev-pharmtox-011112-140317
  35. Nolin TD, Naud J, Leblond FA, Pichette V. Emerging evidence of the impact of kidney disease on drug metabolism and transport. Clin Pharmacol Ther. 2008;83(6):898-903. https://doi.org/10.1038/clpt.2008.59
  36. Nigam SK, Bush KT, Martovetsky G, et al. The organic anion transporter (OAT) family: a systems biology perspective. Physiol Rev. 2015;95(1):83-123. https://doi.org/10.1152/physrev.00025.2013
  37. Cunningham RF, Israili ZH, Dayton PG. Clinical pharmacokinetics of probenecid. Clin Pharmacokinet. 1981;6(2):135-151. https://doi.org/10.2165/00003088-198106020-00004
  38. Weiner IM, Mudge GH. Renal tubular mechanisms for excretion of organic acids and bases. Am J Med. 1964;36:743-762. https://doi.org/10.1016/0002-9343(64)90181-2
  39. Proudfoot AT, Krenzelok EP, Vale JA. Position Paper on urine alkalinization. J Toxicol Clin Toxicol. 2004;42(1):1-26. https://doi.org/10.1081/clt-120028740
  40. Juurlink DN. Activated charcoal for acute overdose: a reappraisal. Br J Clin Pharmacol. 2016;81(3):482-487. https://doi.org/10.1111/bcp.12793
  41. Matzke GR, Aronoff GR, Atkinson AJ Jr, et al. Drug dosing consideration in patients with acute and chronic kidney disease-a clinical update from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int. 2011;80(11):1122-1137. https://doi.org/10.1038/ki.2011.322
  42. Roberts MS, Magnusson BM, Burczynski FJ, Weiss M. Enterohepatic circulation: physiological, pharmacokinetic and clinical implications. Clin Pharmacokinet. 2002;41(10):751-790. https://doi.org/10.2165/00003088-200241100-00005
  43. Hofmann AF. The enterohepatic circulation of bile acids in mammals: form and functions. Front Biosci (Landmark Ed). 2009;14:2584-2598. https://doi.org/10.2741/3399
  44. Levy G. Pharmacokinetics of salicylate elimination in man. J Pharm Sci. 1965;54(7):959-967. https://doi.org/10.1002/jps.2600540701
  45. Anderson GD. Children versus adults: pharmacokinetic and adverse-effect differences. Epilepsia. 2002;43 Suppl 3:53-59. https://doi.org/10.1046/j.1528-1157.43.s.3.5.x
  46. Gibaldi M, Perrier D. Pharmacokinetics, 2nd Edition. Marcel Dekker. https://doi.org/10.1201/b14095
  47. Rowland M, Benet LZ, Graham GG. Clearance concepts in pharmacokinetics. J Pharmacokinet Biopharm. 1973;1(2):123-136. https://doi.org/10.1007/BF01059626
  48. Jusko WJ. Guidelines for collection and pharmacokinetic analysis of drug disposition data. In: Evans WE, et al. Applied Pharmacokinetics. Applied Therapeutics. 1992.
  49. Tozer TN, Rowland M. Introduction to Pharmacokinetics and Pharmacodynamics. Lippincott Williams & Wilkins. 2006.
  50. Winter ME. Basic Clinical Pharmacokinetics, 5th Edition. Lippincott Williams & Wilkins. 2009.
  51. Greenblatt DJ, Koch-Weser J. Clinical pharmacokinetics (first of two parts). N Engl J Med. 1975;293(14):702-705. https://doi.org/10.1056/NEJM197510022931406
  52. Greenblatt DJ, Koch-Weser J. Clinical pharmacokinetics (second of two parts). N Engl J Med. 1975;293(15):964-970. https://doi.org/10.1056/NEJM197510092931505
  53. Holford NH. Pharmacokinetic and pharmacodynamic reasoning. N Z J Med Lab Sci. 2011;65(3):40-50.
  54. Rang HP, Ritter JM, Flower RJ, Henderson G. Rang & Dale’s Pharmacology, 8th Edition. Elsevier. https://doi.org/10.1016/C2012-0-00006-X
  55. Kenakin T. Pharmacology in Drug Discovery and Development, 2nd Edition. Academic Press. https://doi.org/10.1016/C2015-0-01167-0
  56. Kenakin T. A Pharmacology Primer: Techniques for More Effective and Strategic Drug Discovery, 4th Edition. Academic Press. https://doi.org/10.1016/C2012-0-02960-4
  57. Kenakin T. Principles: receptor theory in pharmacology. Trends Pharmacol Sci. 2004;25(4):186-192. https://doi.org/10.1016/j.tips.2004.02.012
  58. Neubig RR, Spedding M, Kenakin T, Christopoulos A. International Union of Pharmacology Committee on Receptor Nomenclature and Drug Classification. XXXVIII. Update on terms and symbols in quantitative pharmacology. Pharmacol Rev. 2003;55(4):597-606. https://doi.org/10.1124/pr.55.4.4
  59. Colquhoun D. Binding, gating, affinity and efficacy: the interpretation of structure-activity relationships for agonists and of the effects of mutating receptors. Br J Pharmacol. 1998;125(5):924-947. https://doi.org/10.1038/sj.bjp.0702164
  60. Kenakin T. Agonist-receptor efficacy. I: Mechanisms of efficacy and receptor promiscuity. Trends Pharmacol Sci. 1995;16(6):188-192. https://doi.org/10.1016/s0165-6147(00)89020-3
  61. Kenakin T. Agonist-receptor efficacy. II. Agonist trafficking of receptor signals. Trends Pharmacol Sci. 1995;16(7):232-238. https://doi.org/10.1016/s0165-6147(00)89032-x
  62. Gaddum JH. The quantitative effects of antagonistic drugs. J Physiol. 1937;89(Suppl):7P-9P.
  63. Rang HP. The receptor concept: pharmacology’s big idea. Br J Pharmacol. 2006;147 Suppl 1:S9-16. https://doi.org/10.1038/sj.bjp.0706457
  64. Kenakin T. Inverse, protean, and ligand-selective agonism: matters of receptor conformation. FASEB J. 2001;15(3):598-611. https://doi.org/10.1096/fj.00-0438rev
  65. Holford NH, Sheiner LB. Understanding the dose-effect relationship: clinical application of pharmacokinetic-pharmacodynamic models. Clin Pharmacokinet. 1981;6(6):429-453. https://doi.org/10.2165/00003088-198106060-00002
  66. Muller PY, Milton MN. The determination and interpretation of the therapeutic index in drug development. Nat Rev Drug Discov. 2012;11(10):751-761. https://doi.org/10.1038/nrd3801
  67. Schiff GD, Galanter WL, Duhig J, et al. Principles of conservative prescribing. Arch Intern Med. 2011;171(16):1433-1440. https://doi.org/10.1001/archinternmed.2011.256
  68. Trevan JW. The error of determination of toxicity. Proc R Soc Lond B Biol Sci. 1927;101(712):483-514. https://doi.org/10.1098/rspb.1927.0030
  69. Litchfield JT Jr, Wilcoxon F. A simplified method of evaluating dose-effect experiments. J Pharmacol Exp Ther. 1949;96(2):99-113. PMID: 18152921
  70. Peck TE, Hill SA, Williams M. Pharmacology for Anaesthesia and Intensive Care, 4th Edition. Cambridge University Press. https://doi.org/10.1017/CBO9781316443217
  71. Rosenbaum DM, Rasmussen SG, Kobilka BK. The structure and function of G-protein-coupled receptors. Nature. 2009;459(7245):356-363. https://doi.org/10.1038/nature08144
  72. Dessauer CW, Watts VJ, Ostrom RS, Conti M, Dove S, Seifert R. International Union of Basic and Clinical Pharmacology. CI. Structures and Small Molecule Modulators of Mammalian Adenylyl Cyclases. Pharmacol Rev. 2017;69(2):93-139. https://doi.org/10.1124/pr.116.013078
  73. Gilman AG. G proteins: transducers of receptor-generated signals. Annu Rev Biochem. 1987;56:615-649. https://doi.org/10.1146/annurev.bi.56.070187.003151
  74. Rhee SG. Regulation of phosphoinositide-specific phospholipase C. Annu Rev Biochem. 2001;70:281-312. https://doi.org/10.1146/annurev.biochem.70.1.281
  75. Traynelis SF, Wollmuth LP, McBain CJ, et al. Glutamate receptor ion channels: structure, regulation, and function. Pharmacol Rev. 2010;62(3):405-496. https://doi.org/10.1124/pr.109.002451
  76. Sieghart W, Savić MM. International Union of Basic and Clinical Pharmacology. CVI: GABAA Receptor Subtype- and Function-selective Ligands: Key Issues in Translation to Humans. Pharmacol Rev. 2018;70(4):836-878. https://doi.org/10.1124/pr.117.014449
  77. Paoletti P, Bellone C, Zhou Q. NMDA receptor subunit diversity: impact on receptor properties, synaptic plasticity and disease. Nat Rev Neurosci. 2013;14(6):383-400. https://doi.org/10.1038/nrn3504
  78. Lemmon MA, Schlessinger J. Cell signaling by receptor tyrosine kinases. Cell. 2010;141(7):1117-1134. https://doi.org/10.1016/j.cell.2010.06.011
  79. Schlessinger J. Cell signaling by receptor tyrosine kinases. Cell. 2000;103(2):211-225. https://doi.org/10.1016/s0092-8674(00)00114-8
  80. O’Shea JJ, Schwartz DM, Villarino AV, Gadina M, McInnes IB, Laurence A. The JAK-STAT pathway: impact on human disease and therapeutic intervention. Annu Rev Med. 2015;66:311-328. https://doi.org/10.1146/annurev-med-051113-024537
  81. Mangelsdorf DJ, Thummel C, Beato M, et al. The nuclear receptor superfamily: the second decade. Cell. 1995;83(6):835-839. https://doi.org/10.1016/0092-8674(95)90199-x
  82. Evans RM. The nuclear receptor superfamily: a rosetta stone for physiology. Mol Endocrinol. 2005;19(6):1429-1438. https://doi.org/10.1210/me.2005-0046
  83. Sassone-Corsi P. The cyclic AMP pathway. Cold Spring Harb Perspect Biol. 2012;4(12):a011148. https://doi.org/10.1101/cshperspect.a011148
  84. Francis SH, Blount MA, Corbin JD. Mammalian cyclic nucleotide phosphodiesterases: molecular mechanisms and physiological functions. Physiol Rev. 2011;91(2):651-690. https://doi.org/10.1152/physrev.00030.2010
  85. Maurice DH, Ke H, Ahmad F, Wang Y, Chung J, Manganiello VC. Advances in targeting cyclic nucleotide phosphodiesterases. Nat Rev Drug Discov. 2014;13(4):290-314. https://doi.org/10.1038/nrd4228
  86. Berridge MJ. Inositol trisphosphate and calcium signalling mechanisms. Biochim Biophys Acta. 2009;1793(6):933-940. https://doi.org/10.1016/j.bbamcr.2008.10.005
  87. Newton AC. Protein kinase C: poised to signal. Am J Physiol Endocrinol Metab. 2010;298(3):E395-E402. https://doi.org/10.1152/ajpendo.00477.2009
  88. Wettschureck N, Offermanns S. Mammalian G proteins and their cell type specific functions. Physiol Rev. 2005;85(4):1159-1204. https://doi.org/10.1152/physrev.00003.2005
  89. Berridge MJ, Bootman MD, Roderick HL. Calcium signalling: dynamics, homeostasis and remodelling. Nat Rev Mol Cell Biol. 2003;4(7):517-529. https://doi.org/10.1038/nrm1155
  90. Francis SH, Busch JL, Corbin JD, Sibley D. cGMP-dependent protein kinases and cGMP phosphodiesterases in nitric oxide and cGMP action. Pharmacol Rev. 2010;62(3):525-563. https://doi.org/10.1124/pr.110.002907
  91. Colpaert FC. System theory of pain and of opiate analgesia: no tolerance to opiates. Pharmacol Rev. 1996;48(3):355-402. PMID: 8888306
  92. Martini L, Whistler JL. The role of mu opioid receptor desensitization and endocytosis in morphine tolerance and dependence. Curr Opin Neurobiol. 2007;17(5):556-564. https://doi.org/10.1016/j.conb.2007.10.004
  93. Rasmussen K, Beitner-Johnson DB, Krystal JH, Aghajanian GK, Nestler EJ. Opiate withdrawal and the rat locus coeruleus: behavioral, electrophysiological, and biochemical correlates. J Neurosci. 1990;10(7):2308-2317. https://doi.org/10.1523/JNEUROSCI.10-07-02308.1990
  94. Koob GF, Le Moal M. Drug addiction, dysregulation of reward, and allostasis. Neuropsychopharmacology. 2001;24(2):97-129. https://doi.org/10.1016/S0893-133X(00)00195-0
  95. O’Brien CP. Drug addiction and drug abuse. In: Brunton LL, et al. Goodman & Gilman’s The Pharmacological Basis of Therapeutics. McGraw-Hill. 2011.
  96. Volkow ND, Morales M. The brain on drugs: from reward to addiction. Cell. 2015;162(4):712-725. https://doi.org/10.1016/j.cell.2015.07.046
  97. Sellers EM, Kalant H. Alcohol intoxication and withdrawal. N Engl J Med. 1976;294(14):757-762. https://doi.org/10.1056/NEJM197604012941405
  98. Amato L, Minozzi S, Davoli M. Efficacy and safety of pharmacological interventions for the treatment of the Alcohol Withdrawal Syndrome. Cochrane Database Syst Rev. 2011;(6):CD008537. https://doi.org/10.1002/14651858.CD008537.pub2
  99. Hansten PD, Horn JR. Drug Interactions Analysis and Management. Wolters Kluwer. 2020.
  100. Koziolek M, Alcaro S, Augustijns P, et al. The mechanisms of pharmacokinetic food-drug interactions – A perspective from the UNGAP group. Eur J Pharm Sci. 2019;134:31-59. https://doi.org/10.1016/j.ejps.2019.04.003
  101. Benet LZ, Hoener BA. Changes in plasma protein binding have little clinical relevance. Clin Pharmacol Ther. 2002;71(3):115-121. https://doi.org/10.1067/mcp.2002.121829
  102. Huang SM, Temple R, Throckmorton DC, Lesko LJ. Drug interaction studies: study design, data analysis, and implications for dosing and labeling. Clin Pharmacol Ther. 2007;81(2):298-304. https://doi.org/10.1038/sj.clpt.6100054
  103. Landersdorfer CB, Kirkpatrick CM, Kinzig M, et al. Competitive inhibition of renal tubular secretion: a novel approach to optimize the pharmacokinetics of antimicrobial agents. Antimicrob Agents Chemother. 2010;54(6):2484-2493. https://doi.org/10.1128/AAC.00099-10
  104. Baxter K, Preston CL. Stockley’s Drug Interactions, 12th Edition. Pharmaceutical Press. 2019.
  105. Greco WR, Bravo G, Parsons JC. The search for synergy: a critical review from a response surface perspective. Pharmacol Rev. 1995;47(2):331-385. PMID: 7568331
  106. Furchgott RF. The use of β-haloalkylamines in the differentiation of receptors and in the determination of dissociation constants of receptor-agonist complexes. Adv Drug Res. 1966;3:21-55.
  107. Edwards IR, Aronson JK. Adverse drug reactions: definitions, diagnosis, and management. Lancet. 2000;356(9237):1255-1259. https://doi.org/10.1016/S0140-6736(00)02799-9
  108. Rawlins MD, Thompson JW. Pathogenesis of adverse drug reactions. In: Davies DM, ed. Textbook of Adverse Drug Reactions. Oxford University Press. 1977.
  109. Lazarou J, Pomeranz BH, Corey PN. Incidence of adverse drug reactions in hospitalized patients: a meta-analysis of prospective studies. JAMA. 1998;279(15):1200-1205. https://doi.org/10.1001/jama.279.15.1200
  110. Pirmohamed M, Breckenridge AM, Kitteringham NR, Park BK. Adverse drug reactions. BMJ. 1998;316(7140):1295-1298. https://doi.org/10.1136/bmj.316.7140.1295
  111. Johansson SG, Bieber T, Dahl R, et al. Revised nomenclature for allergy for global use: Report of the Nomenclature Review Committee of the World Allergy Organization, October 2003. J Allergy Clin Immunol. 2004;113(5):832-836. https://doi.org/10.1016/j.jaci.2003.12.591
  112. Lieberman P, Nicklas RA, Randolph C, et al. Anaphylaxis–a practice parameter update 2015. Ann Allergy Asthma Immunol. 2015;115(5):341-384. https://doi.org/10.1016/j.anai.2015.07.019
  113. Rosenberg H, Pollock N, Schiemann A, Bulger T, Stowell K. Malignant hyperthermia: a review. Orphanet J Rare Dis. 2015;10:93. https://doi.org/10.1186/s13023-015-0310-1
  114. Kaplowitz N. Idiosyncratic drug hepatotoxicity. Nat Rev Drug Discov. 2005;4(6):489-499. https://doi.org/10.1038/nrd1750
  115. Briggs GG, Freeman RK, Yaffe SJ. Drugs in Pregnancy and Lactation, 11th Edition. Wolters Kluwer. 2017.
  116. U.S. Food and Drug Administration. Pregnancy and Lactation Labeling (Drugs) Final Rule. Fed Regist. 2014;79(233):72063-72103.
  117. Ornoy A, Weinstein-Fudim L, Ergaz Z. Prenatal factors associated with autism spectrum disorder (ASD). Reprod Toxicol. 2015;56:155-169. https://doi.org/10.1016/j.reprotox.2015.05.007
  118. Kearns GL, Abdel-Rahman SM, Alander SW, Blowey DL, Leeder JS, Kauffman RE. Developmental pharmacology–drug disposition, action, and therapy in infants and children. N Engl J Med. 2003;349(12):1157-1167. https://doi.org/10.1056/NEJMra035092
  119. Alcorn J, McNamara PJ. Ontogeny of hepatic and renal systemic clearance pathways in infants: part I. Clin Pharmacokinet. 2002;41(12):959-998. https://doi.org/10.2165/00003088-200241120-00003
  120. Weiss CF, Glazko AJ, Weston JK. Chloramphenicol in the newborn infant. A physiologic explanation of its toxicity when given in excessive doses. N Engl J Med. 1960;262:787-794. https://doi.org/10.1056/NEJM196004212621601
  121. Rhodin MM, Anderson BJ, Peters AM, et al. Human renal function maturation: a quantitative description using weight and postmenstrual age. Pediatr Nephrol. 2009;24(1):67-76. https://doi.org/10.1007/s00467-008-0997-5
  122. Bartelink IH, Rademaker CM, Schobben AF, van den Anker JN. Guidelines on paediatric dosing on the basis of developmental physiology and pharmacokinetic considerations. Clin Pharmacokinet. 2006;45(11):1077-1097. https://doi.org/10.2165/00003088-200645110-00003
  123. Mangoni AA, Jackson SH. Age-related changes in pharmacokinetics and pharmacodynamics: basic principles and practical applications. Br J Clin Pharmacol. 2004;57(6):6-14. https://doi.org/10.1046/j.1365-2125.2003.02007.x
  124. Turnheim K. When drug therapy gets old: pharmacokinetics and pharmacodynamics in the elderly. Exp Gerontol. 2003;38(8):843-853. https://doi.org/10.1016/s0531-5565(03)00133-5
  125. Klotz U. Pharmacokinetics and drug metabolism in the elderly. Drug Metab Rev. 2009;41(2):67-76. https://doi.org/10.1080/03602530902722679
  126. American Geriatrics Society 2019 Updated AGS Beers Criteria for Potentially Inappropriate Medication Use in Older Adults. J Am Geriatr Soc. 2019;67(4):674-694. https://doi.org/10.1111/jgs.15767
  127. Touw DJ, Neef C, Thomson AH, Vinks AA; Cost-Effectiveness of Therapeutic Drug Monitoring Committee of the International Association for Therapeutic Drug Monitoring and Clinical Toxicology. Cost-effectiveness of therapeutic drug monitoring: a systematic review. Ther Drug Monit. 2005;27(1):10-17. https://doi.org/10.1097/00007691-200502000-00004
  128. Gross AS. Best practice in therapeutic drug monitoring. Br J Clin Pharmacol. 2001;52 Suppl 1:5S-10S. https://doi.org/10.1046/j.1365-2125.2001.0520s1005.x
  129. Patel IH, Kaplan SA. Pharmacokinetic profile of vancomycin following I.V. and oral administration. J Clin Pharmacol. 1980;20(11-12):699-705. https://doi.org/10.1002/j.1552-4604.1980.tb01682.x
  130. Davit BM, Nwakama PE, Buehler GJ, et al. Comparing generic and innovator drugs: a review of 12 years of bioequivalence data from the United States Food and Drug Administration. Ann Pharmacother. 2009;43(10):1583-1597. https://doi.org/10.1345/aph.1M141
  131. Chen ML, Shah V, Patnaik R, et al. Bioavailability and bioequivalence: an FDA regulatory overview. Pharm Res. 2001;18(12):1645-1650. https://doi.org/10.1023/a:1013319408893
  132. Yu LX, Jiang W, Zhang X, et al. Novel bioequivalence approach for narrow therapeutic index drugs. Clin Pharmacol Ther. 2015;97(3):286-291. https://doi.org/10.1002/cpt.28
  133. De Vries TP, Henning RH, Hogerzeil HV, Fresle DA. Guide to Good Prescribing. World Health Organization. 1994.
  134. Maher RL, Hanlon J, Hajjar ER. Clinical consequences of polypharmacy in elderly. Expert Opin Drug Saf. 2014;13(1):57-65. https://doi.org/10.1517/14740338.2013.827660
  135. Verbeeck RK. Pharmacokinetics and dosage adjustment in patients with hepatic dysfunction. Eur J Clin Pharmacol. 2008;64(12):1147-1161. https://doi.org/10.1007/s00228-008-0553-z
  136. Pugh RN, Murray-Lyon IM, Dawson JL, Pietroni MC, Williams R. Transection of the oesophagus for bleeding oesophageal varices. Br J Surg. 1973;60(8):646-649. https://doi.org/10.1002/bjs.1800600817
  137. Rodighiero V. Effects of liver disease on pharmacokinetics. An update. Clin Pharmacokinet. 1999;37(5):399-431. https://doi.org/10.2165/00003088-199937050-00004
  138. Aronoff GR, Bennett WM, Berns JS, et al. Drug Prescribing in Renal Failure: Dosing Guidelines for Adults and Children, 5th Edition. American College of Physicians. 2007.
  139. Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604-612. https://doi.org/10.7326/0003-4819-150-9-200905050-00006
  140. Golper TA, Marx MA. Drug dosing adjustments during continuous renal replacement therapies. Kidney Int Suppl. 1998;66:S165-168. PMID: 9580564
  141. Anderson GD. Pregnancy-induced changes in pharmacokinetics: a mechanistic-based approach. Clin Pharmacokinet. 2005;44(10):989-1008. https://doi.org/10.2165/00003088-200544100-00001
  142. Pariente G, Leibson T, Carls A, Adams-Webber T, Ito S, Koren G. Pregnancy-associated changes in pharmacokinetics: a systematic review. PLoS Med. 2016;13(11):e1002160. https://doi.org/10.1371/journal.pmed.1002160
  143. American College of Obstetricians and Gynecologists. Guidelines for diagnostic imaging during pregnancy and lactation. Committee Opinion No. 723. Obstet Gynecol. 2017;130(4):e210-e216. https://doi.org/10.1097/AOG.0000000000002355
  144. DiMasi JA, Grabowski HG, Hansen RW. Innovation in the pharmaceutical industry: New estimates of R&D costs. J Health Econ. 2016;47:20-33. https://doi.org/10.1016/j.jhealeco.2016.01.012
  145. Le Tourneau C, Lee JJ, Siu LL. Dose escalation methods in phase I cancer clinical trials. J Natl Cancer Inst. 2009;101(10):708-720. https://doi.org/10.1093/jnci/djp079
  146. Hackshaw A, Farrant H, Bulley S, Seckl MJ, Ledermann JA. Phase II and phase III clinical trial design in ovarian cancer. Gynecol Oncol. 2008;108(2):443-448. https://doi.org/10.1016/j.ygyno.2007.11.025
  147. Friedman LM, Furberg CD, DeMets DL, Reboussin DM, Granger CB. Fundamentals of Clinical Trials, 5th Edition. Springer. https://doi.org/10.1007/978-3-319-18539-2
  148. Strom BL, Kimmel SE, Hennessy S. Pharmacoepidemiology, 5th Edition. Wiley-Blackwell. https://doi.org/10.1002/9781118344828
  149. U.S. Food and Drug Administration. The Drug Development Process. FDA.gov. 2018.
  150. U.S. Food and Drug Administration. Guidance for Industry: Expedited Programs for Serious Conditions – Drugs and Biologics. 2014.
  151. U.S. Food and Drug Administration. Abbreviated New Drug Application (ANDA): Generics. FDA.gov. 2020.
  152. Radley DC, Finkelstein SN, Stafford RS. Off-label prescribing among office-based physicians. Arch Intern Med. 2006;166(9):1021-1026. https://doi.org/10.1001/archinte.166.9.1021
  153. Relling MV, Evans WE. Pharmacogenomics in the clinic. Nature. 2015;526(7573):343-350. https://doi.org/10.1038/nature15817
  154. Weinshilboum RM, Wang L. Pharmacogenomics: precision medicine and drug response. Mayo Clin Proc. 2017;92(11):1711-1722. https://doi.org/10.1016/j.mayocp.2017.09.001
  155. Zhou SF, Liu JP, Chowbay B. Polymorphism of human cytochrome P450 enzymes and its clinical impact. Drug Metab Rev. 2009;41(2):89-295. https://doi.org/10.1080/03602530902843483
  156. Gaedigk A, Sangkuhl K, Whirl-Carrillo M, Klein T, Leeder JS. Prediction of CYP2D6 phenotype from genotype across world populations. Genet Med. 2017;19(1):69-76. https://doi.org/10.1038/gim.2016.80
  157. Johnson JA, Caudle KE, Gong L, et al. Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for Pharmacogenetics-Guided Warfarin Dosing: 2017 Update. Clin Pharmacol Ther. 2017;102(3):397-404. https://doi.org/10.1002/cpt.668
  158. Mega JL, Simon T, Collet JP, et al. Reduced-function CYP2C19 genotype and risk of adverse clinical outcomes among patients treated with clopidogrel predominantly for PCI: a meta-analysis. JAMA. 2010;304(16):1821-1830. https://doi.org/10.1001/jama.2010.1543
  159. Rieder MJ, Reiner AP, Gage BF, et al. Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose. N Engl J Med. 2005;352(22):2285-2293. https://doi.org/10.1056/NEJMoa044503
  160. Relling MV, Schwab M, Whirl-Carrillo M, et al. Clinical Pharmacogenetics Implementation Consortium Guideline for Thiopurine Dosing Based on TPMT and NUDT15 Genotypes: 2018 Update. Clin Pharmacol Ther. 2019;105(5):1095-1105. https://doi.org/10.1002/cpt.1304
  161. Beutler E, Gelbart T, Demina A. Racial variability in the UDP-glucuronosyltransferase 1 (UGT1A1) promoter: a balanced polymorphism for regulation of bilirubin metabolism? Proc Natl Acad Sci U S A. 1998;95(14):8170-8174. https://doi.org/10.1073/pnas.95.14.8170
  162. Phillips EJ, Sukasem C, Whirl-Carrillo M, et al. Clinical Pharmacogenetics Implementation Consortium Guideline for HLA Genotype and Use of Carbamazepine and Oxcarbazepine: 2017 Update. Clin Pharmacol Ther. 2018;103(4):574-581. https://doi.org/10.1002/cpt.1004
  163. Caudle KE, Dunnenberger HM, Freimuth RR, et al. Standardizing terms for clinical pharmacogenetic test results: consensus terms from the Clinical Pharmacogenetics Implementation Consortium (CPIC). Genet Med. 2017;19(2):215-223. https://doi.org/10.1038/gim.2016.87
Updated on December 11, 2025