w.
`
`
`
`
`
`$
`
`E
`
`
`InnOSharma Exhibit 1022.0001
`
`

`

`
`
`éeerzegeir
`
`{filler
`
` :i'
`3‘
`
`.-
`i‘ilzei 3: ME
`
`1.
`
`Prafessor and Executive Dean, South Carolina College of Pharmacy, The
`University of South Carolina, Columbia, Medical University of South Carolina,
`Charleston, South Carolina
`
`
`
`Prefessor, Department of Clinical and Administrative Pharmacy at the
`University of Georgia College of Pharmacy, Athens, Georgia
`
`
`
`Professor, Department of Clinical and Administrative Pharmacy at the
`University of Georgia College of Pharmacy, Athens, Geergia
`
`Professor and Dean, School of Pharmacy, University of North Carolina at
`Chapel Hill, Chapel Hill, North Carolina
`
` «Eerie Mil
`
`Associate Professor of Clinical Pharmacy Practice, University of Cincinnati
`College of Pharmacy, Cincinnati, Ohio
`
`American Society of Health-System Pharmacists®
`
`InnoPharma Exhibit 1022.0002
`
`

`

`Any correspondence regarding this publication should be sent to the publisher, American
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`Library of Congress Cataloging-in-Publication Data
`Concepts in clinical pharmacoltinetics .3" Joseph T. DiPiro
`p. ; cm.
`includes bibliographical references and index.
`ISBN 9?8—l—58528-241—8 {alk. paper}
`1. Pharmacoliinetics.
`l. DiPiro, Joseph T. H. American Society of Health—System
`Pharmacists.
`[DNLMz l. Pharmacolrinetics~Programmed Instruction. 2. Pharmaceutical
`Preparations—-administration 8 dosage-Programmed Instruction. QV 18.2 C744 2010]
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`tered in the us. Patent and Trademark Office.
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`InnoPharma Exhibit 1022.0003
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`

`

`LESSON
`
`1 I
`
`ntroduction to Pharmacokinetics
`
`and Pharmacodynamics
`
`E OBJECTIVES
`
`After completing Lesson 1, you should be able to:
`
`1. Define and differentiate between pharmacokinetics
`and clinical pharmacokinetics.
`
`5. Describe situations in which routine clinical phar-
`macokinetic monitoring would be advantageous.
`
`2. Define pharmacodynamics and relate it to pharma-
`cokinetics.
`
`3. Describe the concept of the therapeutic concentra-
`tion range.
`
`4.
`
`Identify factors that cause interpatient variability in
`drug disposition and drug response.
`
`6. List the assumptions made about drug distribution
`patterns in both one- and two-compartment models.
`
`log of
`7. Represent graphically the typical natural
`plasma drug concentration versus time curve for a
`one-compartment model
`after
`an
`intravenous
`dose.
`
`Pharmawkinetics is currently defined as the study of the
`time course of drug absorption, distribution, metabo-
`lism, and excretion. Clinical pharmawkinetics is the
`application of pharmacokinetic principles to the safe
`and effective therapeutic management of drugs in an
`individual patient.
`Primary goals of clinical pharmacokinetics include
`enhancing efficacy and decreasing toxicity of a patient's
`drug therapy. The development of strong correlations
`between drug concentrations and their pharmacologic
`responses has enabled clinicians to apply pharmacoki—
`netic principles to actual patient situations.
`A drug's effect is often related to its concentration at
`the site of action, so it would be useful to monitor this
`concentration. Receptor sites of drugs are generally inac-
`cessible to our observations or are widely distributed in
`the body, and therefore direct measurement of drug con-
`centrations at these sites is not practical. For example, the
`
`receptor sites for digoxin are thought to be within the
`myocardium. Obviously we cannot directly sample drug
`concentration in this tissue. However, we can measure
`drug concentration in the blood or plasma, urine, saliva,
`and other easily sampled fluids (Figure 1-1). Kinetic
`h0m0geneity
`describes
`the predictable
`relationship
`between plasma drug concentration and concentration at
`the receptor site where a given drug produces its thera-
`peutic effect (Figure 1-2). Changes in the plasma drug
`concentration reflect changes in drug concentrations at
`the receptor site, as well as in other tissues. As the con-
`centration of drug in plasma increases, the concentration
`of drug in most tissues will increase proportionally.
`Similarly,
`if the plasma concentration of a drug is
`decreasing,
`the concentration in tissues will
`also
`decrease. Figure 1-3 is a simplified plot of the drug con-
`centration versus time profile after an intravenous drug
`dose and illustrates this concept.
`
`InnoPharma Exhibit 1022.0004
`
`

`

`2
`
`Concepts in Clinical Pharmacokinetics
`
`DTUQ in
`Blood
`
`I
`I
`
`Drug in
`Tissue
`
`Sample Removed for
`Drug Concentration
`Determination
`
`
`
`Kidney
`Plasma
`Receptor
`
`Time—>
`
`:o
`
`.g
`g’:
`*5no:
`
`0U
`
`FIGURE 1-3.
`
`Drug concentration versus time.
`
`BASIC PHARMACODYNAMIC CONCEPTS
`
`Pharmacodynamics refers to the relationship between
`drug concentration at the site of action and the resulting
`effect, including the time course and intensity of thera-
`peutic and adverse effects. The effect of a drug present
`at the site of action is determined by that drugs binding
`with a receptor. Receptors may be present on neurons in
`the central nervous system (i.e., opiate receptors) to
`depress pain sensation, on cardiac muscle to affect the
`intensity of contraction, or even within bacteria to dis-
`rupt maintenance of the bacterial cell wall.
`For most drugs, the concentration at the site of the
`receptor determines the intensity of a drug's effect (Fig-
`ure 1-4). However, other factors affect drug response as
`well. Density of receptors on the cell surface, the mech-
`anism by which a signal is transmitted into the cell by
`second messengers (substances within the cell), or regu-
`latory factors that control gene translation and protein
`production may influence drug effect. This multilevel
`
`FIGURE 1-1.
`
`Blood is the fluid most often sampled for drug concentration
`determination.
`
`The property of kinetic homogeneity is important
`for the assumptions made in clinical pharmacokinet-
`ics. It is the foundation on which all therapeutic and
`toxic plasma drug concentrations are established. That
`is, when studying concentrations of a drug in plasma,
`we assume that these plasma concentrations directly
`relate to concentrations in tissues where the disease
`
`process is to be modified by the drug (e.g., the central
`nervous system in Parkinson's disease or bone in
`osteomyelitis). This assumption, however, may not be
`true for all drugs.
`
`[I CLINICAL CORRELATE
`
`Drugs concentrate in some tissues because of physi-
`cal or chemical properties. Examples include digoxin,
`which concentrates in the myocardium, and lipid-
`soluble drugs, such as benzodiazepines, which con—
`centrate in fat.
`
`:
`mo
`
`DJ::
`mm
`EuW:
`'200.0
`
`Concentration of Drug in
`Tissues
`
`
`
`l
`Cell Signal
`(2nd Messenger)
`
`Altered
`Receptor
`Expression
`\ Gene Regulation
`i
`Regulation of Protein Production
`
`\l Cellular
`Event
`
`FIGURE 1-2.
`
`Relationship of plasma to tissue drug concentrations.
`
`FIGURE 1-4.
`
`Relationship of drug concentration to drug effect at the recep-
`tor site.
`
`lnnoPharma Exhibit 1022.0005
`
`

`

`Lesson 1: Introduction to Pharmacokinetics and Pharmacodynamics
`
`3
`
`Maximum Effect (Emax
`
`
`20
`
`Plasma Drug Concentration (mg/L)
`
`(log scale)
`
`10
`
`100
`
`Plasma Drug Concentration (mg/L)
`
`FIGURE 1-5.
`
`Relationship of drug concentration at the receptor site to
`effect (as a percentage of maximal effect).
`
`regulation results in variation of sensitivity to drug
`effect from one individual to another and also deter-
`
`mines enhancement of or tolerance to drug effects.
`In the simplest examples of drug effect, there is a rela-
`tionship between the concentration of drug at the receptor
`site and the pharmacologic effect. If enough concentra-
`tions are tested, a maximum effect (Ema can be deter-
`mined (Figure 1-5). When the logarithm of concentration
`is plotted versus effect (Figure 1-5), one can see that there
`is a concentration below which no effect is observed and a
`
`concentration above which no greater effect is achieved.
`One way of comparing drug potency is by the concen-
`tration at which 50% of the maximum effect is achieved.
`
`This is referred to as the 50% eflecn’ve concentration or ECSO.
`When two drugs are tested in the same individual, the
`drug with a lower EC50 would be considered more potent.
`This means that a lesser amount of a more potent drug is
`needed to achieve the same effect as a less potent drug.
`The EC50 does not, however, indicate other important
`determinants of drug response, such as the duration of
`effect. Duration of effect is determined by a complex set
`of factors, including the time that a drug is engaged on
`the receptor as well as intracellular signaling and gene
`regulation.
`
`Later Doses
`AFirst Dose
`
`
`
`
`
`
`Plasma Drug Concentration (log scale)
`
`FIGURE 1-6.
`
`Demonstration of tolerance to drug effect with repeated dosing.
`
`For some drugs, the effectiveness can decrease with
`continued use. This is referred to as tolerance. Tolerance
`
`may be caused by pharmacokinetic factors, such as
`increased drug metabolism, that decrease the concen-
`trations achieved with a given dose. There can also be
`pharmacodynamic tolerance, which occurs when the
`same concentration at the receptor site results in a
`reduced effect with repeated exposure. An example of
`drug tolerance is the use of opiates in the management
`of chronic pain.
`It
`is not uncommon to find these
`patients requiring increased doses of the opiate over
`time. Tolerance can be described in terms of the dose—
`
`response curve, as shown in Figure 1-6.
`To assess the effect that a drug regimen is likely to
`have,
`the clinician should consider pharmacokinetic
`and pharmacodynamic factors. Both are important in
`determining a drug's effect.
`
`I] CLINICAL CORRELATE
`
`Tolerance can occur with many commonly used drugs.
`One example is the hemodynamic tolerance that occurs
`with continued use of organic nitrates, such as nitroglyc—
`erin. For this drug, tolerance can be reversed by inter-
`spersing drug-free intervals with chronic drug use.
`
`[I CLINICAL CORRELATE
`
`One way to compare potency of two drugs that are in
`the same pharmacologic class is to compare EC5O. The
`drug with a lower EC5O is considered more potent.
`
`InnoPharma Exhibit 1022.0006
`
`

`

`4
`
`Concepts in Clinical Pharmacokinetics
`
`Response
`
`I/
`
`Toxicity /’
`
`Drug Concentration (mg/LI
`
`01O
`
`"o‘
`35
`>
`.t
`Ec;
`.0o._
`Q
`
`IO
`
`FIGURE 1-7.
`
`Relationship between drug concentration and drug effects for
`a hypothetical drug. Source: Adapted with permission from
`Evans WE, editor. General principles of applied pharmaco-
`kinetics. In: Applied Pharmacokinetics, 3rd ed. Vancouver, WA:
`Applied Therapeutics; 1992. pp.1—3.
`
`THERAPEUTIC DRUG MONITORING
`
`Therapeutic drug monitoring is defined as the use of
`assay procedures for determination of drug concentra-
`tions in plasma, and the interpretation and application
`of the resulting concentration data to develop safe and
`effective drug regimens. If performed properly, this pro-
`cess allows for the achievement of therapeutic concen-
`trations of a drug more rapidly and safely than can be
`attained with empiric dose changes. Together with
`observations of the drug's clinical effects, it should pro-
`vide the safest approach to optimal drug therapy.
`The usefulness of plasma drug concentration data is
`based on the concept that pharmacologic response is
`closely related to drug concentration at the site of action.
`For certain drugs, studies in patients have provided infor-
`mation on the plasma concentration range that is safe
`and effective in treating specific diseases—the therapeu-
`tic range (Figure 1-7). Within this therapeutic range, the
`desired effects of the drug are observed. Below it, there is
`greater probability that the therapeutic benefits are not
`realized; above it, toxic effects may occur.
`No absolute boundaries divide subtherapeutic, thera-
`peutic, and toxic drug concentrations. A gray area usu-
`ally exists for most drugs in which these concentrations
`overlap due to variability in individual patient response.
`Numerous pharmacokinetic characteristics of a drug
`may result in variability in the plasma concentration
`achieved with a given dose when administered to vari-
`ous patients (Figure 1-8). This interpatient variability is
`primarily attributed to one or more of the following:
`
`FIGURE 1-8.
`
`Example of variability in plasma drug concentration among
`subjects given the same drug dose.
`
`0 Differences in an individual's ability to metabolize
`and eliminate the drug (e. g., genetics)
`0 Disease states (renal or hepatic insufficiency) or
`physiologic states (e.g., extremes of age, obesity) that
`alter drug absorption, distribution, or elimination
`0 Drug interactions
`
`Therapeutic monitoring using drug concentration data
`is valuable when:
`
`1. A good correlation exists between the pharmaco-
`logic response and plasma concentration. Over at
`least a limited concentration range, the intensity of
`pharmacologic effects should increase with plasma
`concentration. This relationship allows us to pre-
`dict pharmacologic effects with changing plasma
`drug concentrations (Figure 1-9).
`2. Wide intersubject variation in plasma drug concen-
`trations results from a given dose.
`
`'.T
`
`7.
`2
`
`Plasma Drug ('nrii wili'w‘iian
`
`0 Variations in drug absorption
`0 Variations in drug distribution
`
`When pharmacologic effects relate to plasma drug concentra-
`tions, the latter can be used to predict the former.
`
`FIGURE 1-9.
`
`InnoPharma Exhibit 1022.000?
`
`OJ
`
`Concentration
`
`D1
`:5h
`
`Da
`
`s Ew 2mHma
`
`)
`.r:
`.9
`
`I
`
`C110
`
`.L—LMMU10
`
`C 0
`
`1
`
`

`

`Lesson 1: Introduction to Pharmacokinetics and Pharmacoclynamics
`
`5
`
`3. The drug has a narrow therapeutic index (i.e., the
`therapeutic concentration is close to the toxic
`concentration).
`4. The drugs desired pharmacologic effects cannot be
`assessed readily by other simple means (e.g., blood
`pressure measurement for antihypertensives).
`
`The value of therapeutic drug monitoring is limited
`in situations in which:
`
`1. There is no well-defined therapeutic plasma con-
`centration range.
`2. The formation of pharmacologically active metabo-
`lites of a drug complicates the application of plasma
`drug concentration data to clinical effect unless
`metabolite concentrations are also considered.
`
`3. Toxic effects may occur at unexpectedly low drug
`concentrations as well as at high concentrations.
`4. There are no significant consequences associated
`with too high or too low levels.
`
`Theophylline is an excellent example of a drug in
`which significant interpatient variability in pharmacoki—
`netic properties exists. This is important from a clinical
`
`..
`
`Co Eg
`
`?._N
`“3“a:we
`area:m
`o1:
`=
`
`0 O
`
`a O
`
`N O
`
`EI!
`E0a
`>"in
`IL
`
`Z.
`
`_ZI
`
`“IL
`
`U>OKA Eo“
`
`JNI<280Z
`
`THEOPHYLLINE CONCENTRATION (mg/liter)
`
`10
`
`20
`
`30
`
`FIGURE 1-10.
`
`Relationship between plasma theophylline concentration and
`change in forced expiratory volume (FEV) in asthmatic patients.
`Source: Reproduced with permission from Mitenko PA, Ogilvie
`Rl. Rational intravenous doses of theophylline. N Engl J Med
`1973;289:600—3. Copyright 1973, Massachusetts Medical
`Society.
`
`
`
`standpoint as subtle changes in serum concentrations
`may result in marked changes in drug response. Figure
`1-10 shows the relationship between theophylline con-
`centration (x—axis, on a logarithmic scale) and its
`pharmacologic effect, (changes in pulmonary function
`[y-axisD. This figure illustrates that as the concentration
`of theophylline increases, so does the intensity of the
`response for some patients. Wide interpatient variability
`is also shown.
`
`Figure 1-11 outlines the process clinicians may
`choose to follow in making drug dosing decisions by
`using therapeutic drug monitoring. Figure 1-12 shows
`the relationship of pharmacokinetic and pharmacody-
`namic factors.
`
`Examples of therapeutic ranges for commonly used
`drugs are shown in Table 1-1. As can be seen in this
`table, most drug concentrations are expressed as a unit
`of mass per volume.
`
`[l CLINICAL CORRELATE
`
`A drug’s effect may also be determined by the
`amount of time that the drug, is present at the site of
`action. An example is with beta-lactam antimicrobials.
`The rate of bacterial killing by beta-lactams (the bac-
`terial cell would be considered the site of action) is
`usually determined by the length of time that the
`drug concentration remains ab0ve the minimal con-
`centration that inhibits bacterial growth.
`
`A diagnosis is made
`
`i
`A drug is selected
`l
`Dosage schedule is
`designed to reach a
`target plasma
`concentration
`
`i
`Drug is administered
`
`/ \
`
`Patient assessments
`are pertormed
`
`Drug concentrations
`are determined
`
`\/
`
`A pharmacokinetic
`model is applied and
`clinical judgment is
`used
`
`FIGURE 1-11.
`
`Process for reaching dosage decisions with therapeutic drug
`monitoring.
`
`InnoPharma Exhibit 1022.0008
`
`

`

`6
`
`Concepts in Clinical Pharmacokinetics
`
`FIGURE 1-12.
`
`Relationship of pharmacokinetics and
`pharmacodynamics and factors that
`affect each.
`
`Pharmacokinatics
`
`Pharmacodynamlcs
`
`
`
`- (.umpliant U
`- liming: .mcl rnmlimiinn (Irmrs
`-
`.*\|J~‘.IJI|i:iuz’i
`-
`iissuin am] hurli- iluirl
`mass and walLimU
`- Drug; inivmi llilll‘,‘
`-
`||ii'|'|ii1.ilinn
`» Drug milmimlism
`
`A Drug rm cpinr siiilus
`- (il‘m‘llt.
`Int hm
`» Iliint mm.” [inns
`lilli'l'i'i‘lit'l’
`
`PHARMACOKINETIC MODELS
`
`The handling of a drug by the body can be very complex,
`as several processes (such as absorption, distribution,
`metabolism, and elimination) work to alter drug concen-
`trations in tissues and fluids. Simplifications of body pro-
`cesses are necessary to predict a drug's behavior in the
`body. One way to make these simplifications is to apply
`mathematical principles to the various processes.
`To apply mathematical principles, a model of the
`body must be selected. A basic type of model used in
`pharmacokinetics is the compartmental model. Com-
`partmental models are categorized by the number of
`
`TABLE 1-1.
`
`Therapeutic Ranges for Commonly Used Drugs
`
`Drug
`
`Digoxin
`
`Lidocaine
`
`Lithium
`
`Phenobarbital
`
`Phenytoin
`
`Quinidine
`
`Cyclosporin
`
`Valproic acid
`
`Range
`
`0.5—2.0 ng/mL
`
`1.5—5.0 mg/L
`
`0.6—1.4 mEq/L
`
`15—40 mg/L
`
`10—20 mg/L
`
`2—5 mg/L
`
`150—400 ng/mL
`
`50—100 mg/L
`
`Carbamazepine
`
`4—12 mcg/mL
`
`Ethosuxamide
`
`40—100 mg/L
`
`Primidone
`
`5—12 mg/L
`
`Source: Adapted with permission from Bauer LA. Clinical phar-
`macokinetics and pharmacodynamics. In: DiPiro JT, Talbert RL,
`Yee GC, et al., editors. Pharmacotherapy: a Pathophysiologic
`Approach, 7th ed. New York: McGraw-Hill; 2008. p. 10.
`
`compartments needed to describe the drug's behavior in
`the body. There are one-compartment,
`two-compart-
`ment, and multicompartment models. The compart-
`ments do not represent a specific tissue or fluid but may
`represent a group of similar tissues or fluids. These
`models can be used to predict the time course of drug
`concentrations in the body (Figure 1-13).
`Compartmental models are termed deterministic
`because the observed drug concentrations determine the
`type of compartmental model required to describe the
`pharmacokinetics of the drug. This concept will become
`evident when we examine one- and two-compartment
`models.
`
`To construct a compartmental model as a representa-
`tion of the body, simplifications of body structures are
`made. Organs and tissues in which drug distribution is
`similar are grouped into one compartment. For example,
`distribution into adipose tissue differs from distribution
`into renal tissue for most drugs. Therefore, these tissues
`may be in different compartments. The highly perfiised
`organs (e.g., heart, liver, and kidneys) often have similar
`drug distribution patterns, so these areas may be consid-
`ered as one compartment. The compartment
`that
`includes blood (plasma), heart, lungs, liver, and kidneys is
`usually referred to as the central compartment or the
`highly blood—perfused compartment (Figure 1-14). The
`other compartment that includes fat tissue, muscle tissue,
`
`Drug
`Dose + Compartment
`
`
`
`l
`
`Elimination
`
`FIGURE 1-13.
`
`Simple compartmental model.
`
`InnoPharma Exhibit 1022.0009
`
`

`

`Lesson 1: Introduction to Pharmacokinetics and Pharmacoclynamics
`
`7
`
`Central
`Compartment
`
`Heart
`
`Liver
`
`Lungs
`
`Kidney
`
`Blood
`
`
`
`Examples of
`Peripheral
`Compartments
`
`Fat Tissue
`
`Muscle
`Tissue
`
`Cerebrospinal
`Fluid
`
`FIGURE 1-14.
`
`Typical organ groups for central and peripheral compartments.
`
`and cerebrospinal fluid is the peripheral compartment,
`which is less well perfused than the central compartment.
`Another simplification of body processes concerns
`the expression of changes in the amount of drug in the
`body over time. These changes with time are known as
`rates. The elimination rate describes the change in the
`amount of drug in the body due to drug elimination over
`time. Most pharmacokinetic models assume that elimi-
`nation does not change over time.
`The value of any model is determined by how well it
`predicts drug concentrations in fluids and tissues. Gener-
`ally, it is best to use the simplest model that accurately
`predicts changes in drug concentrations over time. If a
`one-compartment model is sufficient to predict plasma
`drug concentrations (and those concentrations are of most
`interest to us), then a more complex (two-compartment or
`more) model is not needed. However, more complex mod-
`els are often required to predict tissue drug concentrations.
`
`[l CLINICAL CORRELATE
`
`Drugs that do not extensively distribute into extravascu-
`lar tissues, such as aminoglycosides, are generally well
`described by one-compartment models. Extent of dis-
`tribution is partly determined by the chemistry of the
`agents. Aminoglycosides are polar molecules, so their
`distribution is
`limited primarily to extracellular water.
`Drugs extensively distributed in tissue (such as lipophilic
`drugs like the benzodiazepines) or that have extensive
`intracellular uptake may be better described by the
`more complex models.
`
`COM PARTMENTAL MODELS
`
`K
`
`rate constant
`
`Where: X0: Dose of drug
`X1 = Amount of drug
`in body
`K = Elimination
`
`FIGURE 1-15.
`
`One-compartment model.
`
`ment is represented by an enclosed square or rectangle,
`and rates of drug transfer are represented by straight
`arrows (Figure 1-15). The arrow pointing into the box
`simply indicates that drug is put into that compartment.
`And the arrow pointing out of the box indicates that
`drug is leaving the compartment.
`This model is the simplest because there is only one
`compartment. All body tissues and fluids are considered
`a part of this compartment. Furthermore, it is assumed
`that after a dose of drug is administered, it distributes
`instantaneously to all body areas. Common abbrevia-
`tions are shown in Figure 1-15.
`Some drugs do not distribute instantaneously to all
`parts of the body, however, even after intravenous
`bolus administration. Intravenous bolus dosing means
`administering a dose of drug over a very short time
`period. A common distribution pattern is for the drug
`to distribute rapidly in the bloodstream and to the
`highly perfused organs, such as the liver and kidneys.
`Then, at a slower rate, the drug distributes to other
`body tissues. This pattern of drug distribution may be
`represented by a two-compartment model. Drug moves
`back and forth between these compartments to main-
`tain equilibrium (Figure 1-16).
`Figure 1-17 simplifies the difference between one-
`and two-compartment models. Again, the one-compart-
`ment model assumes that the drug is distributed to tissues
`very rapidly after intravenous administration.
`
`Intravenous
`Administration
`
`Elimination
`
`
`
`Peripheral
`
`is the most frequently
`The one-compartment model
`used model
`in clinical practice.
`In structuring the
`model, a visual representation is helpful. The compart-
`
`FIGURE 1-16.
`
`Compartmental model representing transfer of drug to and
`from central and peripheral compartments.
`
`InnoPharma Exhibit 1022.0010
`
`

`

`8
`
`Concepts in Clinical Pharmacokinetics
`
`FIGURE 1-17.
`
`Drug distribution in one- and two-compartment
`models.
`
`One-compartment model
`belore administration
`
`One-compartment model
`immediately alter
`administration
`
`equilibrium
`
`Two-compartment model
`belore administration
`
`Two-compartment model
`immediately after
`administration
`
`Two-compartment model
`after distributive
`
`The two-compartment model can be represented as
`in Figure 1-18, where:
`
`X0 = dose of drug
`X1 = amount of drug in central compartment
`X2 = amount of drug in peripheral compartment
`K = elimination rate constant of drug from central
`compartment to outside the body
`K12 = elimination rate constant of drug from central
`compartment to peripheral compartment
`K21 = elimination rate constant of drug from periph-
`eral compartment to central compartment
`
`[l CLINICAL CORRELATE
`
`is an
`Digoxin, particularly when given intravenously,
`example of a drug that is well described by two-
`compartment pharmacokinetics. After an intravenous
`dose is administered, plasma concentrations rise and
`then rapidly decline as drug distributes out of plasma
`and into muscle tissue. After equilibration between
`
`drug in tissue and plasma, plasma concentrations
`decline less rapidly (Figure 1-19). The plasma would
`be the central compartment, and muscle tissue would
`be the peripheral compartment.
`
`Volume of Distribution
`
`Until now, we have spoken of the amount of drug (X) in
`a compartment. If we also consider the volume of the
`
`
`
`F|GURE 1-18,
`Two-compartment model.
`
`InnoPharma Exhibit 1022.0011
`
`

`

`Lesson 1: Introduction to Pharmacokinetics and Pharmacoclynamics
`
`9
`
`TABLE 1-2.
`
`Approximate Volumes of Distribution
`of Commonly Used Drugs
`
`Drug
`
`Volume of Distribution (L/kg)
`
`Amlodipine
`
`Ganciclovir
`
`Ketorolac
`
`Lansoprazole
`
`Montelukast
`
`Sildenafil
`
`Valsartan
`
`16.0 i 4
`
`1.1 i 0.2
`
`0.21 i 0.04
`
`0.35 i 0.05
`
`0.15 i 0.02
`
`1.2 i 0.3
`
`0.23 i 0.09
`
`Source: Brunton LL, Lazo JS, Parker KL (editors). The Pharma—
`cologic Basis of Therapeutics, 11th edition. New York: McG raw-
`Hill; 2006. pp. 1798, 1829, 1839, 1840, 1851, 1872, 1883.
`
`the body is primarily composed of water. To calculate
`the volume of the tank, we can place a known quantity
`of substance into it and then measure its concentration
`
`in the fluid (Figure 1-20). If the amount of substance (X)
`and the resulting concentration (C) is known, then the
`volume of distribution (V) can be calculated using the
`simplified equations:
`
`X=VC
`
`or C:K
`V
`
`X
`
`X = amount of drug in body
`V = volume of distribution
`
`C = concentration in the plasma
`As with other pharmacokinetic parameters, volume of
`distribution can vary considerably from one person to
`another because of differences in physiology or disease
`states. Something to note: The dose of a drug (X0) and
`
`
`
`FIGURE 1-20.
`The volume of a tank can be determined from the amount of
`
`substance added and the resulting concentration.
`
`InnoPharma Exhibit 1022.0012
`
`_L O
`
`01
`
`mEi
`
`n
`L“D.
`.E><
`o
`.E’
`
`
`
`DConcentration(ng/mL)
`
`18
`
`12
`Time (hr)
`
`24
`
`FIGURE 1-19.
`
`Plasma concentrations of digoxin after an intravenous dose.
`
`compartment, we can describe the concept of drug con-
`centration. Drug concentration in the compartment is
`defined as the amount of drug in a given volume, such
`as mg/L:
`
`A
`
`1'1
`
`
`.
`amount of drug in body X
`concentration —
`.
`.
`_
`volume in which
`V
`drug is distributed
`
`Volume of distribution (V) is an important indicator of
`the extent of drug distribution into body fluids and tis-
`sues. V relates the amount of drug in the body (X) to the
`measured concentration in the plasma (C). Thus, V is
`the volume required to account for all of the drug in the
`body if the concentrations in all tissues are the same as
`the plasma concentration:
`
`volume of distribution 2
`
`amount of drug
`concentration
`
`A large volume of distribution usually indicates that the
`drug distributes extensively into body tissues and fluids.
`Conversely, a small volume of distribution often indi-
`cates limited drug distribution.
`Volume of distribution indicates the extent of distri-
`
`bution but not the tissues or fluids into which the drug
`distributes. TWo drugs can have the same volume of dis-
`tribution, but one may distribute primarily into muscle
`tissues, whereas the other may concentrate in adipose
`tissues. Approximate volumes of distribution for some
`commonly used drugs are shown in Table 1-2.
`When V is many times the volume of the body, the
`drug concentrations in some tissues should be much
`greater than those in plasma. The smallest volume in
`which a drug may distribute is the plasma volume.
`To illustrate the concept of volume of distribution, let
`us first imagine the body as a tank filled with fluid, as
`
`

`

`10
`
`Concepts in Clinical Pharmacokinetics
`
`
`
`FIGURE 1-21.
`
`K
`
`rate constant
`
`Where: X0: Dose of drug
`X1 = Amount of drug
`in body
`K = Elimination
`
`Drug elimination complicates the determination of the "vol-
`ume" of the body from drug concentrations.
`
`FIGURE 1-22.
`
`One-compartment model.
`
`the amount of drug in the body (X) are essentially the
`same thing because all of the dose goes into the body.
`In this example, important assumptions have been
`made: that instantaneous distribution occurs and that it
`
`occurs equally throughout the tank. In the closed tank,
`there is no elimination. This example is analogous to a
`one-compartment model of the body after intravenous
`bolus administration. However, there is one complicat-
`ing factor—during the entire time that the drug is in the
`body, elimination is taking place. So, if we consider the
`body as a tank with an open outlet valve, the concentra-
`tion used to calculate the volume of the tank would be
`
`constantly changing (Figure 1-21).
`We can use the relationship given in Equation 1-1 for
`volume, amount of drug administered, and resulting
`concentration to estimate a drug's volume of distribu-
`tion in a patient. If we give a known dose of a drug and
`determine the concentration of that drug achieved in
`the plasma, we can calculate a volume of distribution.
`However,
`the concentration used for this estimation
`must take into account changes resulting from drug
`elimination, as discussed in Lessons 3 and 9.
`For example:
`If 100 mg of drug X is administered intravenously and
`the plasma concentration is determined to be 5 mg/ L
`just after the dose is given, then:
`
`volume of
`distribution:
`dose
`2 X0 = 100 mg 2 20 |_
`(V)
`resulting
`C
`5 mg/L
`concentration
`
`I] CLINICAL CORRELATE
`
`The volume of distribution is easily approximated for
`many drugs. For example, if the first 80—mg dose of
`gentamicin is administered intravenously and results
`in a peak plasma concentration of 8 mg/L, volume of
`distribution would be calculated as follows:
`
` volume of
`distribution:
`dose
`2 X0 2 80 m9 = 10 |_
`(V)
`resulting
`C
`8 mg/L
`concentration
`
`[l CLINICAL CORRELATE
`
`Drugs that have extensive distribution outside of
`plasma appear to have a large volume of distribu-
`tion. Examples include digoxin, diltiazem, imipramine,
`labetalol, metoprolol, meperidine, and nortriptyline.
`
`PLASMA DRUG CONCENTRATION
`
`VERSUS TIME CURVES
`
`With the one-compartment model (Figure 1-22), if we
`continuously measure the concentration of a drug in the
`plasma aft