Pharmacology/Receptor Physiology Flashcards
Receptor
protein or glycoprotein which interacts with signaling messenger substance
Ligand
Signaling messenger substance
Ex hormone or drug
‘Initial effect’
Action of drug
‘Succeeding effects’
Drug effects
Law of Mass Action
[L] + [R] <–> [LR]
where formation of L+R is via Ka, separation of L/R into individual components is Kd
[L]=concentration unbound ligand
[R]=concentration unbound R
[LR] = concentration bound R
Ka
rate of constant assoc of L with R
Ka=1/Kd=[LR]/([L]*[R])
Kd
Rate of constant of dissociation of L with R
Affinity
Relationship btw particular R, its L
If amt of ligand administered is just enough to occupy 50% of R then, Ka = 1/[L]
Can a ligand have a strong affinity for the R without producing effect?
Yes
Activity
Ability of ligand to induce an action’
Higher Ka
At equilibrium, number of unbound molecules is low so have high affinity of L for R
Lower Ka
At equilibrium, number of unbound molecules high so have low affinity of L for R
Selectivity of a ligand
determines capacity to produce a particular effect
Highly selective = produce only 1 effect through activity (at only one class/subclass of R
Ex: dopamine vs Dobutamine –> Dobutamine more selective bc only effects at B R, no alpha
Specificity of ligand
capacity to associate with only one specific type of R
o Effects of ligands of highly specific ligand = can be numerous but DT only one type of R-L interaction
Ex: atropine - associates with one specific type of R even though R present in different in tissues, effects diverse
Ex: inhalants - interact with multiple R to produce effects
Limitations to Law of Mass Action
- All L, R equally available to each other
- Binding of drug + R does not alter either drug or R –> not case when drug substrate for R is metabolic enzyme
- Binding of drug to R is reversible…frequently not
- R+drug either bound to each other or not bound ie no ambiguous, partial states
Effect of drug
proportional to concentration of ligand molecules available to bind
Function of dose, method of administration
Lag Time
delay from dosing to onset of pharmacological effects
Can be DT relative difficulty of ligand reaching R (pharmacokinetics) or from post-transduction delay (pharmacodynamics)
Example of a R with lag time
glucocorticoid R = nuclear: when not bound to ligand such as (cortisol, another GC) receptors are located in cytosol
Once activated: complex brought to nucleus –> induces transcription of genes coding from anti-inflammatory proteins, inhibits transcription of genes usually upregulated by inflammatory mediators
Onset of activity = post-transduction (long lag time)
Agonist
ligand that binds to R, usually activates it same way that endogenous molecules would
Full Agonist
Fully activates receptor
Eg morphine
Partial agonist
does not fully activate –> produces less intense maximum effect
ex: buprenorphine
Neutral Antagonist
ligand will bind to receptor, but unable to activate
Assoc usually competitive –> Can be overcome by administrating large enough amount of agonist
Can also be non-competitive
Ex: flumazenil: competitive neutral antagonist at benzo site on GABAA R
Reverse Agonist
ligands activate R but will induce opposite effects to agonist ligands
If R has baseline effect that is not nil, admin of reverse agonist will decrease baseline effect –> ex if agonist effect provides analgesia, then reverse agonist will increase pain sensation
Ex: Ro 19-4603 at benzo binding site on GABAA R
Naloxone
Opioid antagonist but at low doses, enhances analgesia effects
Proposed MOA: increasing effect of endogenous ligands, up regulation of postsynaptic R, inhibiting of counteraction by Gs proteins, uncoupling of filament A, attenuating increase in expression of GFAP
Receptor State Theory
- R by default in non-activated form, needs agonist ligand to be activated
- Non-activated form represents most of R – without presence of agonist ligand, some R can exits in their activated form
- Role of ligand not to activate R but stabilize activated form
Major implications:
o Existence of a baseline agonist effect for R
o Differentiated btw antagonist drugs, inverse agonist drugs
Primary Structure of a R
Linear sequence of amino acids
Secondly Structure
Regular local sub-structure (α-helix or ß-sheets)
Tertiary Structure
Three-dimensional structure of a single peptide molecule
Quaternary Structure
combination of multiple tertiary structure of different proteins linked together
Function of VG Na ion channels
o Conduct sodium cation into cell action potential generated
o As membrane potential increases conformational central pore changes –> increased sodium permeability, influx of sodium ions
Conformation change made possible by presence of particular transmembrane-spanning segments (α-helices) called voltage sensors
Ternary Complex Model
- Relevant for GPCRs
- Sensitivity for [LR] system and pot of agonists = subject to availability of external agonists
Competitive antagonists
- Will shift dose response curve R: will need more agonist to have same maximal effect
- Can be overcome by administrating large enough amount of agonist
- Ex: flumazenil, butorphanol at MOR, naltrexone/naloxone under basal conditions
Reverse Agonists - examples
ligands activate R but will induce opposite effects to agonist ligands
AKA inverse agonist
Ex: Ro 19-463, diphenhydramine at H1R, all H2R, naloxone/naltrexone when MOR bound to GPCR
Ionotropic R
“Fast response”
L, VG
Activation causes flow of ions across plasma membrane
Ion channels = Na, Ca, K, GABAA, nicotinic, NMDA
Metabotropic R
“Slow response”
Activated via ligand
Activation –> series of intracellular events via second messenger cascade
GPCR: adrenergic R, opioid, GABAB, mAChR, dopaminergic, histaminergic
Na Ion Channel Structure
1 large alpha subunit with 4 homologous domains (DI, DII, DIII, DIV)
-Each domain: 6 helical segments
-S4 segment = voltage-sensing segment
When membrane potential increases, these S4 (positively charged) segments move toward extracellular side of membrane –> change conformation of channel
Two accessory beta subunits
What are two other important features of the Na R structure?
o DIII, S6 = inactivation particle of H gate
o DIII, S5-S6 and DIV, S5-S6: segments implicated in H gate
Where do LA bind?
o DIV, S6: binding site of LA
Three States of the Na R
- Resting
- Open
- Closed/Inactive
MOA NaV
At rest, RMP -70mV – m gate closed, voltage sensor S4 in each domain
S4 senses when MP increases to -55mV – rapid opening of activation (m) gate
Opening of activation (m) gate allows Na ions to flood into cell, raises MP to +30mV
At -55mV, inactivation gate (H gate) starts to close but closes MUCH more slowly (0.5-2msec)
Once H gate closed, not capable of reopening for 2-5msec – allows membrane to repolarize, return to resting state
Modulated R Hypothesis
Preferential binding to inactivated, activated states – low affinity for resting state
Can only access DIV, S6 from intracellular side
Lipid soluble LA gains intracellular access via crossing lipid bilayer
* More lipid soluble, faster onset
Poorly lipid soluble LA must enter channel when open during activated state
Guarded R Hypothesis
R for LA inside channel, channel must be open for R binding site to be accessible
LA binds to R with constant affinity
Use-dependent (phasic) block
frequency-dependent blockade, repeated depolarization
* More binding sites made available, increased binding of LA, increased depth of blockade
Tonic Block
Blockade constant
NaV 1.1
peripheral neurons, CNS, cardiomyocytes
NaV 1.2
CNS, embryonic PNS
NaV 1.3
peripheral neurons, CNS, cardiomyocytes
NaV 1.4
skeletal m
NaV 1.5
cardiomyocytes***, CNS, GI
NaV 1.6
CNS, DRG, peripheral neurons, cardiomyocytes
NaV 1.7
CNS, DRG, peripheral neurons, cardiomyocytes, Schwann cells, neuroendocrine
NaV 1.8
DRG
NaV 1.9
DRG
GABA A R
- Fast response anion channels – allow passage of chloride anions into cell, CNS in mammals
Activation of GABA A R?
- Activation: hyperpolarization of neuron inhibits subsequent depolarization of neuron –> reducing CNS activity
- γ-Aminobutyric acid = main agonist
Anesthetic Drugs that work at GABA A
o Most anesthetic drugs that work on GABAA do not directly activate R
o Induce allosteric change ie change conformation/quaternary structure of R = allosteric modulation
Positive Allosteric Modulators at GABA A
barbiturates, benzos, propofol, etomidate, alfaxalone, inhalants, ethanol – allow greater hyperpolarization
Negative Allosteric Modulators at GABA A
flumazenil, decreases efficiency of R
What is true about most anesthetics at the GABA A R?
o Most anesthetic drugs that work on GABAA do not directly activate R at clinically useful doses –> allosteric modulators
Most able to directly activate R if used at doses much greater than what used clinically EXCEPT benzos – BENZOS CAN NEVER DIRECTLY ACTIVATE GABAA
GABA Binding Site
EC R at a/b subunit interface
Increases IC Cl –> hyperpolarization
Benzos
alpha subunit interface with gamma subunit
Decrease rate of dissociation of GABA, increases duration of channel opening
Barbiturates
Beta subunit interface with alpha or gamma subunit
Decrease rate of dissociation of GABA, increases duration of channel opening
Neurosteroids
beta subunit interface
Facilitates movement of Cl into pore
Etomidate
alpha/beta subunit interface
Increased frequency of channel opening, increased affinity for GABA
Also enhances effect of other drugs
Propofol
beta subunit interface
Decreases rate of dissociation of GABA, increases duration of channel opening
Inhalants
alpha/beta subunit interface
Decreases rate of dissociation of GABA, increases duration of channel opening
Picrotoxin
2nd TM helix of ion channel
Non-competitive antagonist, blocks Cl conduction
Structure of GABA A R
α , ß , γ subunits (2a, 2b, γ)
Each subunit: four TM-spanning (α-helix) segments, create chloride channel
TM2 lines ion channel
AMPA R?
- α-aminohydroxymethylisoxazolepropionic acid
Amino
Hydroxy
Methyl
Iso
Xazole
Proprionic acid
AMPA R Structure
4 subunits
Each subunit having four TM segments, creates cation channel
AMPA R Function
–LG ionotropic R: allows Na in, K out
–Assoc with agonist ligand, conformation changes, channel options - amt of glutamine released in synapse dictates amt of cation transfer
–Degree of depolar of postsynaptic neuron induced by AMPA-R action
AMPA Activation and Assoc with NMDA
Activation of AMPA R normally STIMULATORY, upregulated in chronic pain states – why NMDA antagonists beneficial for windup/chronic pain
Multiple or stronger depolarization of postsynaptic membrane also release Mg plug from NMDA so that channel opens further depolarization
* Weak AMPA R activation will not activate NMDA
* Strong AMPA R activation will activate NMDA
NMDA R
o LG, VG ionotropic R: cation channel allows Na+ < Ca2+ into cell, K+ exits cell
Mostly influx of Ca that allows cell to become more positive
o Mg2+ keeps channel closed until strong enough depolarization of postsynaptic membrane occurs
Tetramere structure with 2 homologous subunits
NMDA R agonists
o Glutamate, aspartate= main endogenous agonist
Glycine = co-agonist
NR1 Subunit
- Required for R function
- Increased activity with tissue injury, hyperalgesia
- Co-localized with a2 centrally, peripherally
- Increases COX-1 activity
- Glycine, D-serine can bind
NR2 Subunit
- 4 variants/subtypes
- Determines sensitivity of R, required for R function
- Increased activity with tissue injury
- Glutamate, aspartate binding site
Modulators of NMDA
Mg, Na, Ca, Cu, Zn, K – “My Nana Can Coach Zebra Karate”
MOA NMDA R
Pre-synaptic neuron releases glutamate or aspartate (excitatory amino acids) – binds to NMDA, AMPA at NR2 subunit
Partial postsynaptic depolarization from AMPA R, expulsion of Mg from NMDA once stimulus from AMPA sufficient – allows full channel to be opened
Once open, Ca/Na flow in, K flows out of NMDA (Na, K for AMPA)
* Increases intracellular Ca – acts as second messenger
* Activation of Ca-dependent kinase, calcium/calmodulin-dependent protein kinase II (CaMkII)
* Increase in Na conductance
* Activates formation of NO –> increases positive retrograde signal, releases glutamate from presynaptic neuron
* Hyperalgesia, central sensitization, chronic pain, long-term potentiation
NMDA R Antagonists
amantadine, gabapentin, ketamine/phencyclidine derivatives, ethanol, xenon, N2O, some opioids (methadone, tramadol)
Ketamine, Tiletamine
non-competitive antagonists
Binds to phencyclidine site inside ion channel –> must be open for binding
MOA: decreases frequency, opening time of Ca channel – prevents Ca, Na influx; prevents firing of second order (afferent) neuron
* Also depresses activity of thalamacocortical activity, limbic system, nuclei in RAAS
GPCR
- To transduce extracellular signals, some TM receptors use intermediaries
o Intermediaries= Guanine nucleotide-binding proteins (G-proteins) - Second messengers = series of intracellular biochemical events
o Initiated by receptor-ligand interaction clinical effect
Structure of GPCR
- GTP (guanosine triphosphate) : supplies energy for G-protein receptors
- Structure
o 7 TM spanning proteins with N and C terminal
o Coupled to heterodimeric proteins: alpha, beta, gamma
On alpha subunit, coupling domain btw 5-6
o Binding of ligand causes hydrolysis of GTP to GDP, provides energy for something to happen inside cell
Gs
Increase in adenylyl cyclase
Increased cAMP production
Activation of phosphokinase A
Gq
Phospholipase C activated –> IP3, DAG
Activation of PKC
Increased in Ca in cytoplasm
Gi
Blocks adenylyl cyclase activity
Pharmacodynamics
effects of drug on whole body
Evaluation of potency, efficacy, concentration-response relationships, effective dose, lethal dose, therapeutic index
General principal: more drug = more effects
o Occurrences of U shaped, inverted U shaped dose response curves
Hormesis
dose-response relationships characterized by stimulatory effects at low dose and inhibitory effects at higher dose
o Inverted U-shaped dose-response curve
o Ex: Naloxone
Emax
Maximum efficacy, maximal pharmacological effect of drug or ligand pharmacological effect (E) of drug directly proportional to percentage of activated R
Receptor State Theory
existence of a baseline agonist effect (E0)
Hill’s Equation
Hill’s Equation: E= (Emax -E0)[L] / (Kd + [L])
Potency
concentration of drug needed to obtain a pharmacological effect equal to 50% of Emax , ie EC50
o Lower EC50 less drug needed to achieve required effect, higher potency of drug
o Ex: buprenorphine more potent than morphine
ED50
dose of drug necessary to induce desired effect in 50% of animals
LD50
dose of drug necessary to induce death in 50%
TD50
toxic dose; dose of drug necessary to induce toxic effects in 50% of patients
Replaces lethal dose in human trials
ED90, ED95
ED90 = effective dose in 90% of population
ED95 = effective dose in 95% of population
Therapeutic Index
= ratio LD50 :ED50 or TD50 :ED50
Higher therapeutic index, safer drug considered
Doesn’t take slope of concentration-response curve into effect
* Ex: two drugs A, B with same TD and given at ED90¬ – induce significantly different prevalence of SE
* TD not a useful measure of drug’s clinical safety
Application of Therapeutic Index
A: ED90 significantly different than TD90 – most of population will benefit from A without experiencing significant SE.
B: ED90 not very different than TD90 – large part of population encounter toxic SEs
Pharmacokinetcs
body initiates its actions on drug (absorption, distribution, metabolism, and elimination (ADME)
Zero Order PK
process occurs at constant rate
Change of drug concentration in body fluid (plasma, urine) occurs at constant rate irrespective of concentration of drug present in body fluid
STRAIGHT LINE: y=mx+b
What is true about the general metabolism of drugs and rate at which reactions can occur?
o Most occur as saturable processes (Michaelis-Menten kinetics): speed at which process occurs has upper limit that can be reached
Pharmacodynamics
Drug initiates its action on body (D is for drug)
o Interaction of free drug with receptor –> effect response
Effect response = directly proportional to ratio of R drug concentration to total R concentration
Single Response Systems
Where maximal response is measured, effect response measured approaches an asymptote
Effect response = Max achievable response*concentration/(EC50 + [drug])
Tachyphylaxis
o Sometimes relationship btw [drug], effect response reflects changes in sensitivity of signaling pathway to presence of drug
Ex: R tachyphylaxis, other unknown processes
Better representation by equation using hill coefficient, modifies steepness of effect response curve
Free Hormone Hypothesis
hormone (or drug) present in protein-bound, unbound (or free) forms in equilibrium
Activity of drug or hormone at its site of action proportional to concentration of free drug or free hormone in plasma
* Irrespective of total drug or hormone concentration
* Free drugs can diffuse readily to sites of action
Allows linkage of plasma concentration to drug’s effect response
Plasma PK: degree, extent, duration of drug effect
Half-Life Elimination
- Time interval needed for plasma concentration to be reduced by 50%
Half Life Elimination with Zero Order Kinetics
half-life= function of plasma [ ] of drug at beginning of time interval
–Parameter not constant
Half Life Elimination with First Order Kinetics
elimination half-lives fixed at constant rate per unit time
Rate of Metabolism Affected by:
species, age, gender, BW, dz states (esp renal, hepatic dz), drug interactions
Drug Elimination and Steady State
~4-5 half-lives must pass before change in dose achieves new steady state plasma concentration (at about 97% of total)
Therefore, 4-5 half-lives must pass after cessation of administration before effectively all of drug is eliminated
Loading dose
- Loading dose= C(desired)Vc
o Apparent volume of central compartment (Vc) usually used for calculating loading doses for rapidly acting or toxic drugs, ex: induction agents
Vdss is used for CRI
Mass of Drug in Body
Mass of drug in body proportional to concentration measured in sample space (often plasma) at any time.
Expressed as: XB=C*Vd
–XB= mass of drug in body
–C=concentration
–Vd= Proportionally constant, apparent volume of distribution
* Apparent bc does not represent any particular physiologic or anatomic space
Vc
Volume of circulation, aka volume of central compartment
Vdss
vol of distribution at steady state, sum of all volumes (central and peripheral)
Factors that Affect volume of distribution
o State of hydration
o Age and gender
o Body weight
o Body composition
Fat, muscle, water ratios
o Protein content of serum especially for protein bound drugs
o Plasma expanders such as lipids after meal
o Drug interactions
Total Body Clearance
o Volume of blood from which drug completely removed per unit of time
Volume per unit time, often normalized by body weight (ex: mL/min/kg)
o Measure of efficiency of drug elimination, often directly compared or contrasted with CO in species under examination
Sum of clearance achieved by all mechanisms:
hepatic+renal+other = total
Extraction Ratio
fraction of drug removed from blood on each pass of blood through liver
ER = (Ca-Cv)/Ca where Hepatic clearance is then equal to flow through the liver (Q)*ER
Hepatic Clearance
Rate of blood flow through liver * (drug concentration in arterial blood – drug concentration in venous blood)/drug concentration in artieral blood
Cl(H) = [Q(Ca-Cv)]/Ca
Liver and Clearance
Most body systems, processes = saturable: liver in each individual has maximum capacity for removing drug from blood when no blood flow constrictions
Capacity for drug elimination by combination of biotransformation, excretion by bile = function of liver mass, amount/activity of enzymes of drug metabolism that present in individuals hepatocytes
Intrinsic Clearance
Maximum capacity for drug removal from blood = intrinsic ability of liver to remove drug, innate capacity of liver to clear drug
When Intrinsic Clearance «< HBF…
hepatic clearance = intrinsic clearance (ClH = ClI)
Limiting factor (rate limiting step) of clearance NOT BF dependent, dependent on intrinsic clearance
Ex:
*Variations in plasma protein binding of drug can significantly alter rate of excretion
*Induction of hepatic enzymes: large effect on elimination rate
When Intrinsic Clearance»_space;> HBF…
hepatic clearance = rate of HBF (ClH¬ = QH)
In this case, alterations in HBF profoundly influence rate of hepatic clearance
Dependent on: CO, normal structure/function of hepatic BV
Renal Clearance
Relationship between rate of change of amount of drug in urine, plasma [drug]
Clearance of drug from plasma by kidneys
achieved by summation of renal filtration, active renal tubular secretion of drug into the urinary ultrafiltrate, diminished by any tubular resorption of drug
ClR= (RF/C) + (RS/C) + (RR/C)
* RF= rate of renal filtration
* RS= rate of renal secretion
* RR= rate of renal resorption
C = concentration
What is renal filtration a function of?
function of GFR, plasma concentration of unbound drug
If fraction of unbound drug is one…
renal clearance = GFR
If renal clearance > GFR*unbound fraction…
Renal Secretion must be occurring
If renal clearance < GFR*unbound fraction…
Renal Resorption must be occurring
Absorption
Drugs formulated for standard delivery methods absorbed by concentration-dependent processes that are linear (first-order processes)
When drugs administered by routes other than IV
rate of absorption across membranes (barriers to entry) proportional to difference in concentration across membrane, area of membrane, permeability of membrane to drug
o Manipulate surface area: admin in aliquots at multiple sites
Are CRIs and transdermal patches zero or first order kinetics?
administration of drug constant per unit time (zero order)
Other Challenges with Drug Absorption
Concentration of drug in formulation determines steepness of diffusion gradient for drug absorption
Concentration of drug diluted prior to injection or post injection DT H2O movement (osmotic gradient)
o Lymph/blood flow, CO, factors controlling local BF alter concentration gradient
o Proximity of administration to impermeable boundaries (fascial planes, fat) alter rate of drug absorption
Controllable by appropriate injection site choice
o Unexpected inefficiency, toxicity with high-potency drugs bc of changes in rate, extent of drug absorption
Bioavailability
–Fraction of drug that finds way into systemic circulation
–NOT equal to fraction of dose absorbed as some is removed via metabolism
–Also affected by biotransformation
Three components that make up bioavailability?
- Peak plasma concentration
- Time to reach plasma concentration
- Area under the curve
Bioavailability of given route…
calculated by comparing the total drug exposure of the dose with that achieved when the same dose is given IV
Principle of Superimposition
response to any combination of inputs must equal sum of responses when input separately
If it obeys this, considered linear pharmacokinetic model
Input = dose, output = sample’s drug concentration
Drugs that display first order kinetics
Predictable plasma concentrations after changes in drug where 2x dose = 2x plasma concentration
Stochastic System
each molecule of drug introduced to body, moves through system independently of all molecules of same drug introduced to system
Example: in horses, primary metabolite of cute (oxyphenobutazone) interferes with parent moiety’s metabolism - non-stochastic system
Importance about Drug Assays
Capable of accurately measuring concentrations at least 10x lower than minimum effective concentrations
Experiments in PK
Design determined by elimination rate constant/elimination HL
Not possible to predict HL of drug accurately unless several samples collected over 2-3 HL
o If pilot data on species unavailable, allometric scaling from other species
Common Ax drugs and PKs
Anesthetic drugs = lipophilic, increases need for biotransformation (saturable process)
Also affect CO, regional tissue blood flow
Common that ax drugs have non-linear PK
* Ability to extrapolate results to novel clinical situations requires demonstration whether drug behaves with linear PK
* Eg perform experiment with multiple doses
Formulation admin by route other than IV: attention to effect of formula needed access to PK of active moiety after IV inj
Naive Data Pooled Set
Least desirable
All data from all animals pulled together for data analysis
Approach loses opportunity to develop understanding of differences btw animals within population or variance within populations
When use naive pooled data set?
necessary when each individual only able to be sampled 1-2x
* Sample vol large vs circulating blood vol
* Act of sampling likely to alter PK at subsequent time points
* Species difficult to evaluate, capture, restrain
Standard Two Stage Approach
Most common, similar individuals from target population with each individual sampled at same time points, on multiple occasions after dosing
Following washout period (>5 half lives): dosed again, sampled to evaluate either dose proportionality or effect of chosen manipulation on drug’s PK
Linear mixed models, factors for dose, sequence, animal, sequence + animal interactions, etc
PK-PD Study
Embellishment of two stage approach where data collected to measure drug concentration +/- drug effects
OBJECTIVE MEASURE
Surrogate: biological markers (intermediate enzyme activities) or second messenger concentration
MOA PK-PD Studies
Data from each animal analyzed independently, combined to generate estimates for population variables
evaluate correlation between dose and effect, predict ideal doses better, to gain better understanding of drug’s effect on pathophysiological processes
Disadvantage of PK-PD Studies
Need large number of sample time points per animal to estimate larger number of variables accurately
POP PK Studies
Evaluate PK of drug in clinical cases
Small # samples (usually 2-5) taken from each case at times convenient for case
Alternatively small # cases sampled frequently to describe PK adequately
Goal of POP PK Studies
Need suitable structural model for PK of drug (previous study)
Allows identification of factors within clinical population that might markedly alter PK, alter efficacy/toxicity of drug
Single Compartment Model
After IV bolus, rapid distribution to one compartment
Two Compartment Model
IV bolus: rapid distribution then drug moves out of central compartment, into other compartment (body compartment)
Three Compartment Model
After IV bolus, plasma concentration peaks –> exponential decline, 3 distinct phases
* Initial rapid drop
* Rate of decrease then slows
* Steady, predictable decrease
Explained by movement of drug between a central (V1), 2 peripheral compartments (V2 & V3)
V1
central compartment, equilibrates with effect site (brain), from which drug removed from body (e.g. liver metabolism, renal excretion)
V2, V3
V2, V3:“reservoirs” where drug moves from V1, no connection with effect site
* V2 (mostly muscle) better perfused than V3 (fat, bone), smaller capacity to absorb drugs vs V3
Why Use Compartment Models
Purpose: evaluate data so as to derive estimates of PK variables, estimates may then be used to make predictions of outcome
Plot time and concentration on semi logarithmic axes, check whether data can be described by a single straight line
if so, one compartment model
If not, check has a two compartment model
Mathematical Models for PK Model Fitting
- Monte Carlo
- Simplex
- Gauss-Newton, Marquadt
Monte Carlo
Directly compare minimizing criterion using random iterations to vary parameter estimates
* Robust to poor initial parameter estimates
* Slow, computer intensive
* Care should be taken not to restrict number of iterations greatly
Simplex
Directly compare minimizing criterion using simple stepwise approach
* Robust to poor initial parameter estimates
* Slow, computer intensive
* Start with large step sizes, gradually reduce step size through several runs of minimization process to avoid finding false solutions
* Usually starting point
Gauss-Newton and Marquardt
Gradient methods, use either first or second order derivatives of minimizing criterions
* Require good initial estimates in order to proceed
* High reliability of finding best solution
Non-Compartment Models
o Applicable to both stochastic, non stochastic PK – allows calculation of volumes of distributions, clearance, mean time parameters
o Mean time parameters: average total time spent by molecules in kinetic space after introduction to that space
Homogenous Kinetic Space
analogous to single compartment
Heterogenous Kinetic Space
grouping of multiple independent compartments of complex compartment model
Mathematics for Non-Compartmental Modeling
–Simpler
–Area under concentration vs time curve from time of introduction of dose (t=0) to infinity (AUC)
–Area under first moment of concentration vs time curve from time of dosing until infinity (AUMC)
–Linear or log linear trapezoid models
What is the most common error assoc with non compartmental models?
failing to define PK curve for adequate time period
Large portion of total area under portion of curve that after last quantified time point ie portion of curve that is extrapolated
If proportion of total area that was extrapolated is greater than 20%, that experimental design was inadequate for approach to data analysis
Physiologically based PK models (PBPK):
allow for individual organ, tissue blood flow as proportion of cardiac output
Allow determination of extraction ratio for each organ of interest, drug clearance achieved by that organ, estimation of organ/tissue drug concentration
Allow understanding of effect of drug recirculation on arterial, venous drug concentrations
Delayed Absorption or Distribution
lag btw dosing and changes in concentrations or between appearance of drug in sample space and distribution to site of action
NSAIDS
Constant Rate Therapy
maintenance of specific plasma concentration, consequent effect desired
–Usually IV, also patches, slow release injectable agents
Requires constant rate of absorption
Intermittent Bolus Injection
plasma drug concentration reaches a peak, decreases as re-distribution, clearance occurs
o Loading dose, effect maintained by repeat injections
o Oscillations: inconsistent levels in targeted effect
o Result in administration of large total drug dose, slower/longer recovery from effect
CRI
Eliminates peaks, troughs
o Better quality of effect, decrease in total drug dose delivered
CRI - Bags
Gravity Dependent
Speed of infusion depends on:
–Diameter/length of connecting tube
–size of drops
–size of cannula
–viscosity of agent
–height of fluid
–venous pressure of patient
–As bag empties, infusion rate decreases - needs readjusting
Syringe Drivers for CRIs
If higher than heart: siphoning may occur DT weight of liquid –> larger drug volume administered than programmed
o Resolved by protection against syringe plunger moving faster than motor drive
If lower than vascular port: less agent infused than programmed DT back pressure from venous bed, weight of liquid
Other Risks with Syringe Drivers
- Infusion sets should incorporate one way valve system
- If syringe driver positioned vertically, outlet placed downwards - avoid infusing bubbles formed by gas coming out of solution
Rate Controlled Infusions (Non-PK-Dependent CRIs)
Use of loading dose then adjustment of infusion rate based on patient needs
Smoother ax, less drug used overall, requires frequent fine tuning adjustments
Problem with Standard CRIs
Beginning = too low of a plasma concentration
Over time mass accumulates; prolonged –> undesired effects
Pharmacokinetic-dependent infusion systems
manually controlled using RCI or stepped infusion, or electronically controlled with computer adjusting speed of infusion: Target Controlled Infusion (TCI)
Limitations with TCI
More reliant technique on preexisting PK data, more achieved plasma drug concentration depends on quality, relevance of PK model used/similarities of patient and experimental subjects
Deviations from conditions under which PK data obtained may result in unexpected plasma concentrations
Zero Order Kinetics
Elimination rate INDEPENDENT of drug concentration
Observed when elimination mechanisms saturated ex elimination by particular enzyme of which there are only small quantities
Linear on linear scale, curved outward on log scale
TCI MOA
Drug infused must equal amount of drug eliminated = steady-state plasma drug concentration (CSS)
First order elimination: mass of drug eliminated per unit time depends on plasma drug concentration at steady state of agent (Css), clearance (Cl)
What does a maintenance infusion rate for TCI depend on?
- Target plasma concentration at steady state
- Drug’s total body clearance
Elimination HL Parameters
~4-5 times elimination half-life for plasma drug concentration to approach its accumulation plateau (same as non-PK dependent CRI)
–Loading Dose
Loading Dose
cause plateau to be reached sooner
Calculating LD: dose required to fill central compartment (VC) or calculating dose to fill total distribution volume at steady state (VSS)
VC: plasma concentration will be low, VSS: Overshoot
Stepped Infusions
Series of CRIs aimed at reaching targeted plasma drug concentrations as rapidly as possible while neither over or undershooting
Fast initial infusion to fill central compartment, followed by maintenance infusion determined by desired target or central compartment drug concentrations, drug’s rate of clearance
Very rigid, difficult to adapt to clinical situations
BET
Bolus - Elimination - Transfer
Precursor to TCI system
B of BET
Bolus
Loading Dose
E of BET
Elimination
Steady state rate of infusion according to drug’s elimination
T of BET
Transfer
Exponentially decreasing rate to match redistribution of drug from central compartment to peripheral sites
How BET Precursor to TCI
computer programed with set of PK parameters for species/drug, algorithm calculates infusion rate necessary to achieve target concentrations
Accuracy dependent on PK variables used to program device
* Calculated of percentage prediction error (PE%) as difference btw measured, predicted values
Percentage Prediction Error (%)
= (measured concentration – predicted concentration)/predicted concentration x 100%
MDPE%
mean prediction error (MDPE%)
Using values of PE% derived at each measurement point, number of induces of performance in individual subject calculated
Measure of bias to indicate whether measured concentrations systemically above or below targeted values
Measures inaccuracy, typical size of difference btw measured and targeted concentrations
Wobble
measures total intra individual variability in performance error
Divergence
systematic time-related changes in measured concentrations away from or towards the targeted concentration
Positive Value
widening of gap between predicted, measured value
Negative Value
Measured and predicted values converging over time
Context Sensitive Half Time
time from end of infusion necessary for patients plasma’s drug concentration to decrease by 50%
CSHL and Short Term Infusions
CSHL depends on redistribution
Clinical Efficacy of Bolus Dose
clinical effect mostly dependent on redistribution of drug from brain to other tissues
CSHL with Long Term Infusions
peripheral compartments saturated, CSHL approaches true elimination half-life of drug
CSHL with Modern Length Infusions
CSHL will depend on drug’s distribution, elimination
Decrement Time
time in which decrease in concentration modeled specifically for compartment of effect site
Allows for clinician to better predict a stop infusion time for end of surgery (percentage), duration of infusion (context), context-sensitive effect site decrement time requires for necessary decrease
Drug Interactions - three types
- Physiochemical
- PK
- PD
Physiochemical
o Two incompatible drugs mixed together in vitro
o Interactions: changes in physical stability of complex formulations, changes in solubility with precipitation, changes in chemical stability of active or excipient ingredients, absorption onto delivery device surfaces, chelation or chemical reactions (reduction or oxidation)
PK Interactions
Interactions during different PK phases of A, D, E or biotransformation
Example of a Beneficial PK Interaction
epinephrine + Lidocaine to prolong its effect / absorption locally)
PK Interactions: Distribution
Drug interactions can change distribution (but not clinically relevant in anesthesia)
PK Interactions: Alterations in Plasma Binding
competition btw drugs for same binding site thought to be important
Displacement of drug from protein binding does not markedly alter unbound fraction in circulation, affects elimination rate more than efficacy
Drug-drug interactions during biotransformation
more frequent
Clinical significant: depends on hepatic intrinsic clearance for each drug
Extent of genetic polymorphism among breeds, individuals of same species
* Ex: MDR1 frame shift mutation
Elimination and PK Drug Interactions
Inhibition of clearance: results in increase in drug concentration
Increased clearance: decreased in drug blood concentration, lack of efficacy +/- therapeutic failure
Inhibition, induction of drug clearance can affect CYPs (phase I metabolism) or transporters (Phase III metabolism)
Effect of Increased CO during TCI/CRI with drugs with high intrinsic hepatic clearance
decreases in plasma drug concentration, consequent changes to efficacy
Vice versa
Alteration in hepatic clearance related to change in CO described with propofol in humans, sheep, pigs
PD Drug Interactions
Result in modification of response of body to one or more concomitantly administered drugs
DT alterations of R sensitivity or affinity to one agent by other
Example: MAC sparing drug
How Assess PD Interactions
- Isobolographic Analysis
- Response Surface Modeling Techniques
Isobolographic Analysis
Evaluate effects of different [ ] of two agents on specific effect (ex loss of consciousness)
Different dosing pair combinations resulting in same effects evaluated
Isobole constructed by drawing line through “iso-effective” combinations
Isobolographic Analysis: line of additivity or additive interactions
straight line through btw two [ ]s for each single agent associated with same effect
–Synergism: concave, up shaped isotope
–Infra-additivity: concave-down isotope
Downside of Isobolographic Analysis
Only 2 dimensional, information only on specific level eg EC50
Response Surface Analysis
More complete set of effect levels (EC01-EC99)
3D graphs, incorporates all available isoboles for different levels of effect
Each single combination of two drugs: point on surface, height = drug effect of interest
ADR/ADEs
ADR (adverse drug reactions), adverse drug events (ADE): describe events that include undesired effects and inefficacy, relative to expected effects after drug administration
Examples of ADR Categories
dose-related, non-dose related, dose- and time-related, time-related, withdrawal, unexpected inefficacy
Tachyphylaxis of Tolerance
- Drugs that induce physiological adaptation, R downregulation/tachyphylaxis, enzyme induction or inhibition can result in time-related undesired effects
o Direct effects or be caused by drug interactions
o Developing tolerance: onset of inefficacy – clenbuterol, opiate analgesics
In what group of drug are ADEs most commonly reported?
NSAIDS
Drug Metabolism
Two phases: phase I, II
Xenobiotic Drug Metabolism
metabolized by either or both phases depending on physiochemical properties of drug, species of animal
Phase I Biotransformation
Goal: convert fat-soluble (lipophilic) compounds into:
o Water-soluble (hydrophilic) compounds ready for immediate renal clearance
o Add chemically reactive sites to relatively chemically inert molecule for further biotransformation
Secondary Biotransformation
further Phase I interactions or conjugation reactions
Examples of Phase I Reaction
Oxidation - CYP, others
Reduction
Hydrolysis
Hydration
Isomerization
Ring-Crystalization
Phase II
Conjugation reactions attach exogenous compound covalently to substrate which increases molecular weight, water solubility
Phase III
needs further transport across biological membranes, recently labeled as Phase III
Phase I Biotransformation
Majority performed by cytochrome p450 isoenzymes (CYPs), localized in liver
on endoplasmic reticulum of metabolically active cells
o Responsible for oxidation, reduction, hydrolysis, hydration reactions
Prepare xenobiotics for Phase II conjugation)
o CYPs: hemoproteins (spectral absorbance 450 nm when reduced, complexed with CO)
Naming of CYP Proteins
Families represented by Arabic number
Subfamilies: capital letter
Final Arabic number= individual enzymes
CYP2B11
: propofol hydroxylation, breed differences in propofol metabolism
Also contributes to alfax, barbiturate metabolism
CYP3A
main contributor to medetomidine metabolism
Other Important CYP in Dogs
- Phenobarbital increases activity of CYP2B11, 2C21, 3A26
- Rifampin induces CYP 3A26
- Omeprazole induces CYP 1A2
Enzyme Induction
–Slow process: days to weeks
– Effect on drug concentration can alter treatment outcomes
–Clinical relevance mostly confined to drugs with low intrinsic hepatic clearance
–Process usually reversible
CYP Inhibition
- Competitive
- Non-competitive
- Uncompetitive
- Mechanism-Based
Examples of Drugs with Inhibitory CYP Activity
Propofol - rats, hamsters
Medetomidine - dogs, rats, fish
Dexmed - dogs, rats
Atipamezole - dogs
CYP Inhibition - Important Considerations
Inhibition of biotransformation usually reversible
Occasionally irreversible, permanent enzyme activity loss until new enzymes synthesized
CYP inhibition usually immediate response (unlike induction)
Clinical Consequences of Inhibited CYP
higher plasma drug concentrations +/- prolonged elimination HL
Increased risk of accumulation, toxic effects
Phase II MOA
Mechanisms: glucuronidation, sulfation, methylation, acetylation, amino acid conjugation, glutathione conjugation, fatty acid conjugation
Glucuronidation: most important form
* Occurs with alcohols, phenols, hydroxylamines, carboxylic acids, etc
Which is the most important form of Phase II reactions
Glucuronidation
Glutathione
protective compound
Removal of potentially toxic electrophilic compounds
Epoxides, haloalkanes, nitroalkanes, alkenes, aromatic halo/nitro compounds
Sulfation
major metabolic pathway for phenols
Enzymes that Facilitate Conjugation Reactions
sulfotransferases (SULT), UDP-glucuronosyltransferases (UGT), glutathione S transferase (GST)
Phase III Biotransformation
–Transport of metabolites via transporters in intestine, liver, kidney, brain
–Transmembrane Transporters
Examples of Transmembrane Transporters
P-glycoprotein (P-gp)
organic anion-transporting polypeptide 2(OATP2)
multidrug resistance-associated protein (MRP)
ABC Transporters
ATP-binding casette transporters
Multidrug resistance Assoc protein, P-glycoprotein
ABC Transports
- Utilize energy from ATP to transport substrate across the cell membrane
ABC transporters Locations - liver
canicular membrane –> biliary excretion of both parent drugs, metabolites; transporters involved in said excretion
* Also sinusoidal membrane, drug uptake from blood to hepatocytes
ABC transporters Locations - kidney
organic anion, cation transport systems found on brush border, basolateral membranes of tubular epithelial cells = responsible excretion of drugs into urine
Isomers
Drugs often carbon based entities, multiples structural molecular forms:
Constitutional Isomers
= same number, type of atoms, connectivity btw atoms differs (ex: propane vs cyclopropane)
Pose little practical clinical problem
Stereoisomers
occur DT inflexibility of carbon-carbon double bonds (cis-trans isomers) or carbon molecule may have four different covalently bonded moieties, creates one or more chirally active centers (enantiomers, diastereomers)
R-S Naming System
Orientation of molecule in space, reading direction of descending atomic mass
o Clockwise R: R for rectus, straight
o Anticlockwise S, ex S-ketamine = active isomer: S for sinister, left
D-L Naming System
polarized light rotates to right when passed through solution of an enantiomer dextrorotatory (+) isomer, image = levorotatory (-) isomer
Cis-Trans Isomers
differences in affinity for drug R or metabolizing enzymes
Products rarely have more than minor contamination of less active isomer
Chirally Active Stereoisomers
pose a major consideration for clinical pharmacology
o Two types of chiral stereoisomers: enantiomers and diastereomers
What are the two types of chiral stereoisomers?
- Enantiomers
- Diastereomers
Racemic Mixtures
Products with both enantiomers, diastereomers
Diastereomers
No planar symmetry
Enantiomers
chirally active stereoisomers with planar symmetry, one form = mirror image of other
* Molecule with two active chiral centers = possibility of four isomers
o Two of possible pairings = symmetry, are stereoisomers but the other four pairings do not have planar symmetry
