Transcript UConn 2005

Predicting Human Drug
Metabolism and Pharmacokinetics
in Drug Discovery
Carl D. Davis, Ph.D.
April 17th 2007
Drug Metabolism and Pharmacokinetics
Pharmaceutical Candidate Optimization
Bristol-Myers Squibb Company
[email protected]
Agenda
• Introduction: the significance of drug metabolism in
drug discovery
• Overview of drug-metabolizing enzymes and associated
concerns
• Tools for predicting human drug metabolism and
pharmacokinetics
• Scaling preclinical data to predict human
pharmacokinetics
• Summary
2
Drug Metabolism
• The metabolism and toxicity of phenacetin and acetaminophen are well studied and
very illustrative examples of processes that can affect drugs in general
3
Drug Metabolism
• The exposure of xenobiotics (e.g. drugs) and endogeneous
substrates is regulated in animals and humans by clearance, either
by direct elimination (biliary and/or renal) or by enzyme-mediated
metabolism
– Generally this is a detoxication process that prevents
accumulation of bioactive compounds in the body
• can also produce reactive metabolites and toxicity
• The contribution of these processes to total clearance of a drug is
evaluated in drug discovery and development to identify the safe
efficacious dose of a compound and safe exposure of its
metabolite(s)
– In discovery, drug metabolism is typically an impediment when
looking for an optimal dose
• More highly cleared compounds require bigger and more
frequent doses to achieve a therapeutic effect
– Problems: formulation, inter-individual variability, drug-drug
interactions and safety margins
4
The Significance of Drug Metabolism
• The oral exposure profile of a drug depends on its Absorption,
Distribution, Metabolism, and Excretion (ADME)
– The rate of metabolism is a significant factor governing the oral
bioavailability of a drug
5
Metabolic Clearance and Systemic Exposure
• Target exposure lie in the therapeutic window with safety vs risk defined by
the unmet medical need, the severity of disease and the quality of options
available
6
Drug Metabolism in a Drug Discovery Setting
• Large number of structurally diverse compounds
– Methods optimized for throughput and economy
• More sophisticated methods used for lead compounds
– Most sophisticated methods used in Development (GLP)
• Limited data available on compound properties
– Matrix teams encounter matrix problems:
• Solubility, Absorption, Active-Efflux, Metabolism, Toxicity,
Efficacy
– Define issues for development
• New PK/PD models
– Limited/no validation data available
• Species differences in pharmacology
• Species differences in drug metabolism and PK
– Consider active metabolite(s)
• Limited/No human ADMET data available
– Discovery studies predictive rather than mechanistic
• Revise as human data become available
7
Overview of Drug-Metabolizing
Enzymes and Associated Concerns
8
Cytochromes P450
• Cytochromes P450 (CYPs) are a hemethiolate superfamily of enzymes
that are widely distributed across species (bacteria → human)
• In mammals CYPs expressed in many tissues; most highly expressed in
the liver
• Regulate the metabolism of structurally diverse xenobiotics and some
endobiotics (e.g. steroids)
– Most important class of drug-metabolizing enzymes
• CYP nomenclature is based on shared homology of amino acid
sequence:
Family (>40%)
Subfamily (>55%)
CYP2C19
Isoform
Family (>40%)
Subfamily (>55%)
CYP2C9*2
Isoform
Allele
Genotype/
Phenotype
9
Relative Amounts of Individual
Human Hepatic CYPs
Shimada et al., JPET: 1994
Lasker et al., Arch. Bioch. Biophys:1998
10
Human Cytochromes P450 and their Relative
Contribution to Hepatic Drug Metabolism
Bertz & Granneman, ClinPK: 1997
≈ 60% of drugs are metabolized primarily by CYPs:
• CYP3A4 is involved in the metabolism of most of them
• large active site volume can accommodate multiple substrates
• CYP2D6 is involved in the metabolism of many CNS drugs
11
Polymorphic Distribution
Simple bimodal distribution
Frequency
Fast CL
Phenotype
Antimode
Slow CL
Phenotype
1 2 3 4 5 6 7 8 9 10 11
Phenotype (e.g. Cmax µg/mL)
• A trait with differential expression in >1% of the population
12
12
Frequency of CYP Polymorphic Phenotypes
(divers sources)
• CYP2D6 has a complex genotype and trimodal phenotype
• Slow, Fast and UltraFast Metabolizers
13
13
CYP2D6 Genotype and Nortriptyline PK
Dalen P, et al. Clin Pharmacol Ther (1998)
• The clearance of an equivalent dose of nortriptyline in humans is markedly
dependent on the relative expression and functional activity of CYP2D6
14
CYP Polymorphisms and Adverse Drug Reactions
Enzyme
Variant Allel
(Frequency in
Caucasian)
Examples of ADRs associated with
Variant Allele
CYP1A2
CYP1A2*1F (68%)
Antipsychotics: tardive dyskinesia
CYP2C9
CYP2C9*2 (8-13%);
CYP2C9*3 (7-9%)
Warfarin: haemorrhage
Phenytoin: phenytoin toxicity
Tolbutamide: hypoglycaemia
CYP2C19
CYP2C19*2 (13%);
CYP2C19*3 (0%)
Mephenytoin: toxicity
Diazepam: prolonged sedation
CYP2D6
CYP2D6*4 (12-21%);
CYP2D6*5 (4-6%);
CYP2D6*10 (1-2%);
CYP2D6*17 (0%)
Propafenone: arrhythmias
Metoprolol: bradycardia
Nortriptyline: confusion
Opioids: dependence
Phenformin: lactic acidosis
Perhexiline: hepatotoxicity
CYP3A4
CYP3A4*1B (5.5%)
Epidophyllotoxins: treatmentrelated leukaemias
Pirmohamed and Park Toxicology (2003): Adapted from Ingelman-Sundberg et al. (1999), Ingelman-Sundberg (2001)
and Primohamed and Park (2001)
15
Non-CYP Drug Metabolizing Enzymes
• Cytochromes P450 are not the only drug-metabolizing enzymes:
– Flavin Monooxygenases (FMOs; membrane-bound & NADPH-dependent)
– Esterases: AChe BChe, CE1, CE2 et al (drugs and prodrugs)
– Amidases (peptides including “biologicals”)
– Uridine Glucuronosyl-S-Transferases (UGTs)
– Glutathione-S-Transferases (GSTs)
– Aldehyde Oxidase (AO)
– Xanthine Oxidase (XO)
– Monoamine Oxidase (MAO)
– Alcohol & Aldehyde Dehydrogenase (non-specific)
– N-Acetyl Transferases (NATs)
– Sulfotransferases (STs)
– Many others: e.g. Epoxide hydrolases; DT Diaphorase; O-Methylation; SMethylation; Amino Acid Conjugation: glycine, taurine; histamine
methyltransferase (HMT); thiopurine methyltransferase (TPMT); catechol
O-methyltransferase (COMT)...
16
NAT2: Isoniazid Exposure and Bimodal Phenotype
H
N
O
Frequency of Slow Acetylator Phenotype
(Evans 1989):
Canadian Eskimos:
Asian:
European/Caucasian:
Egyptian:
Moroccan:
5%
10-20%
40-70%
80%
90%
NH2
N
Isoniazid
(Isonicotinyl Hydrazine)
TOXICITY: Isoniazid-related peripheral
neuropathy greater in slow acetylators
(still used to treat non-resistant TB)
17
Drug Metabolizing Enzymes and Bioactivation
• Typically NATs mediate a detoxification pathway with side
effects more prevalent in Slow Acetylators
• N-Acetylation also involved in toxicity, with NATs mediating
bioactivation e.g. of procarcinogens
Metabolism and Bioactivation of Arylamines
(spontaneous)
Target
nucleophiles
e.g DNA and
proteins….
Potential for
toxicity
(structural
alert)
• Knowing the enzyme(s) that metabolize your drug helps you to understand
mechanisms involving species and/or organ-specific toxicity and their
relevance to human safety
18
Genetic Polymorphisms of Non-CYP Drug Metabolizing
Enzymes that Increase the Risk of Adverse Drug
Reactions
Enzyme/Target/Gene
Drug
Adverse Drug Reaction
Butyrylcholinesterase
Succinylcholine
Prolonged apnoea
N-acetyltransferase 2
(NAT2)
Sulphonamides
Hydralazine
Isoniazid
Hypersensitivity
Lupus erythematosus
Neuoropathy
Dihydropyrimidine
dehydrogenase
Fluorouracil
Azathioprine
Mercaptopurine
Myelotoxicity
Myelotoxicity
Myelotoxicity
UGT1A1
Irinotecan
Diarrhoea, myelotoxicity
(Güzey & Spigset: Drug Safety, 2002)
19
Human Arylamine N-Acetyl Transferases
Figure from Patin (AJHG, 2006)
• When a drug is metabolized primarily by one pathway ethnic differences in
its metabolism should be considered in the dose prescribed
Tools for predicting human drug
metabolism and pharmacokinetics
21
Tools for Studying Drug Metabolism
In Vitro:
• Fresh or cryopreserved hepatocytes: gold standard
– Human cells available for biomedical research
• Liver subfractions: cheap and simple to prepare
– S9, Microsomes, Cytosol, Mitochondria
• Liver slices: cheap, not as simple to prepare; multiplexed
assays
– Fresh human liver tissue has very limited availability
• Recombinant enzymes: very specific
– Transfected cells; Microsomes/Supersomes
• Inhibition studies
– Typically with human liver microsomes with drug ± CYP-selective
inhibitor. (e.g. ketoconazole for CYP3A; quinidine for CYP2D6)
22
Tools for Studying Drug Metabolism
In Vivo:
• Transgenic animals
– Knockout mice/rats
– Humanized mice/rats
• In vivo inhibition studies: complex model
– 1-Aminobenzotriazole (non-selective mechanistic CYP inhibitor)
– Cimetidine (rat CYP2C11 inhibitor)
23
Scaling preclinical data to predict
human pharmacokinetics
24
Predicting Human Clearance and PK
Generate In Vitro Data:
• Incubate drug with liver microsomes or hepatocytes, measure intrinsic
clearance and apply scaling factors to predict in vivo clearance
– co-incubate with a series of CYP-selective inhibitors to get a relative
contribution
• Incubate drug with recombinant enzymes, measure turnover, correct
for relative abundance and kcat
– apply scaling factors to predict in vivo clearance
Generate In Vivo Data:
• Use allometric-scaling of CL and Vss in animal PK studies to predict
equivalent parameters in human
Predict PK:
• Use the in vitro/in vivo CL and Vss values and relevant absorption data
to predict a human PK exposure profile and simulate scenarios for
bioavailability, CL and DDI
25
Reaction-Phenotyping Methods:
Calculating Intrinsic Clearance
• Intrinsic clearance (CLint) is the enzyme-mediated clearance that would occur
without physiological limitations (e.g. hepatic blood flow)
Metabolite-Formation Approach:
Rate of Metabolism, ν = Vmax * CE
Km + CE
CLint = Vmax/Km
Rate (nmol/min/mg
protein)
Michaelis-Menten Kinetics (Simple form)
Vmax
15
Rate-linear metabolite
formation kinetics
0
0
10
Km
Substrate Concentration (uM)
CLint =
(ml/min/mg)
t1/2 = ln2/k
ln2
t1/2 * [HLM]
Time
1
0
-1 0
ln[S] (uM)
When CE << Km
C = C0 * e-kt
Substrate
Concentration (uM)
Substrate-Depletion Approach:
60
-2
-3
-4
-5
y = -0.0693x
(slope = -k)
-6
First-Order kinetics
0
0
60
Time
26
Reaction-Phenotyping Methods: Scaling Intrinsic
Clearance in Liver Microsomes or Hepatocytes to In Vivo
Hepatic Clearance
Using CLint from MM or substrate-depletion kinetics:
CLintin vitro
Scaling factors
(e.g. microsomal;
hepatocellularity)
CLint’in vivo
Models of
hepatic clearance
(apply blood-flow limits)
CLh as %QH
In Vivo Clearance
(Exemplified by Houston, 1994)
• By modifying CLint, the effect of polymorphisms and/or DDIs on total exposure
can be predicted
27
In Vivo Hepatic Clearance and the Venous Equilibrium
or “Well-Stirred” Model
The Well-Stirred model is the one most commonly used for scaling hepatic
clearance (CLH):
CLH
=
QH * fub*CLint’in vivo
QH + fub*CLint’in vivo
(NB: with in vivo data, this
variation assumes concentration
in blood and plasma to be the
same: CB/CP = 1)
High Clearance drugs:
(i.e. blood-flow limited)
CLH ≈ QH
Low Clearance drugs:
CLH ≈ fub*CLint’in vivo
There are many other factors to consider in predicting human
PK
28
Scaling rCYPs to HLM
Total metabolic clearance is the sum of individual reactions:

n
Vtotal =
i=1
Vmaxi * S
Kmi + S
The Total Normalized Rate (TNR) approach uses the rate of metabolism
measured in each rCYP, and factors based on the relative abundance of the
CYP in HLM to get an HLM equivalent:
n
V(s)HLM =

Ai * Vi(s)rCYPi
i=1
Theoretically:
V(s)HLM =
% Contribution CYPiHLM =
CLintHLM (if kcatrCYPi = kcatHLMCYPi)
Ai * Vi(s)rCYPi* 100
V(s)HLM
Ai denotes the relative abundance of the enzyme (e.g. pmol CYP/mg liver microsomal protein)
29
Predicted Human Reaction-Phenotype
• Measure metabolism in human recombinant CYPs: Drug A shows the same rate of
metabolism in each; Drug B shows greater metabolism in CYP2D6 (polymorphic).
• The predicted phenotype depends on the relative expression of the native
human CYPs
30
Allometric-Scaling
Y = aWb
(Y= CL or Vss)
• In vitro and in vivo data can be fitted to predict the human clearance
• Using the exponents and Species Invariant-Time methods, the human PK
exposure profile can be predicted and used for simulations
31
The Significance of Drug Metabolism
• Calculate the relative contribution of a CYP-mediated pathway to the
overall clearance and thus predict the effect of a co-administered CYP
inhibitor on oral exposure:
AUCpo (Inhibitor)
AUCpo (Substrate)
1
=
fm*fmP450
CLint(Substrate)/CLint(Inhibitor)
+ [1-(fm*fmP450)]
• Single CYP primary clearance mechanisms are unattractive in that
they are susceptible to altered oral exposure following coadministration of a potent CYP inhibitor
32
Reaction-Phenotyping
• Predict the in vivo metabolic clearance and the contribution of
individual Drug Metabolizing Enzymes to the total in vivo
clearance
– A drug with a metabolic clearance (e.g. >40% of the total
clearance) and metabolized by a polymorphic enzyme and/or
a primary enzyme (e.g. >30-50% of the total metabolic
clearance) has an increased relative risk of drug-drug
interactions and/or individual variation
– Reaction-phenotyping can refine the human dose projection
33
Putting Some of it Together
IMPACT OF RESULTS
If unsafe, the drug won’t be
developed
If target efficacious levels
can’t be reached, the drug
won’t be developed
• The predicted human PK and drug metabolism can point towards
potential drug-drug interactions and/or polymorphisms that may affect the
new drug (a multitude of factors can confound the predictions)
• First in Human (FIH) starting doses and controlled human CYP inhibition
studies provide adjustments for better prospective modeling of lead/backup drugs
34
Summary
•
Enzyme-mediated clearance affects most drugs, with the CYP superfamily of
enzymes usually involved and CYP3A4 the worst offender
•
Metabolic clearance is a significant factor in oral bioavailability and thus the
dose prescribed
•
Many CYPs are polymorphically expressed: profound differences can be seen
between humans in their exposure to the drug and/or metabolite(s)
•
Major clearance pathways (>40% of total) mediated by a single enzyme can be
a concern if that enzyme is polymorphically expressed or inhibited or induced
(co-medicant/herbal supplement/diet/environment)
– Drug metabolizing enzymes generate active/reactive metabolites that may
be involved in efficacy and/or toxicity associated with the drug
•
An array of tools are available (in vitro and in vivo) that allow early screening
and prediction of human PK and drug metabolism
– These tools have reduced attrition, with better PK properties associated
with new drugs: improved safety, faster development and lower R&D costs
35
Thanks for your attention