definition of pgt & pgx · pharmacogenetics and pharmacogenomics • pharmacogenetics – the...
TRANSCRIPT
Hong-Hao Zhou, MD
SECOND ANNUAL SYMPOSIUM ON PHARMACOVIGILANCE-Pharmacovigilance Strategy to maximize drug safety
11:15-12:00, March 4, 2010 Hong Kong
Clinical Trials in Pharmacogenetics and
Pharmacogenomics
• PHARMACOGENETICS – the study of the role of inheritance in inter-individual variation in drug response
• PHARMACOGENOMICS – the use of DNA sequence information to measure and predict the reactions of individuals to drugs
• Often, these terms are used interchangeably
Definition of PGt & PGx
Genomic medicine
Ref: Roses, A. Pharmacogenetic and the practice of medicine. Nature, 405, 857-865
Genetic Testing
Disease geneticsDisease prognostics/diagnostics
PharmacogeneticsMedicine response profiles
Rare mendelian diseases:
Causal genes
Common complex diseases,
Susceptibility genes
New disease insights and future medicines Optimal medicine response
Genes for drug
metabolism and/or action
SNP profiles for drug
metabolism
Potential for unsolicited information and ethical, legal and social implication
Utility
What is tested
Benefits
Risks
GWAS PGx
Genomics
Paradox of Modern Drug Development
Clinical trials provide evidence of efficacy and safety at usual doses in populations
Physicians treat individual patients who can vary widely in their response to drug therapy
• Define function of genetic variants of biomarkers related to drug safety and efficacy;
• Define genetic (SNP) profile related to drug safety and efficacy;
• Drug development;
• Personalized medicine.
Use of clinical trial in pharmacogenetics
Two Ways of Clinical Trials in PGt
• Identify suitable loci using in vitro studies
• Generate possible treatment hypotheses
• Select suitable patients– Enrichment studies
• Prove the treatment works for these patients
• Identify potential drugs
• Find those that work in general
• Find the drugs on patients areconsiderable
• Search for genetic subgroups
From Gene From Drug
Functional test of variant
Sampling
+
-
Geneticanalysis
Screen of target volunteers
+/-
Treatment
• Patient numbers for genetic test maybe unbalanced in two arms.
• Sampling maybe limited in some patients.• Results are not confirmative Confirmative trial will be
necessary
Retrospective Design
Placebo
Drug
+
-
Entry
Sampling
Treatment
Randomized, double blind, placebo-controlled trial
+
-Ge
ne
tic
an
aly
sis
To test clinical utility
▬ PGx test is really necessary?▬ Cost-benefit relationship
Results are confirmative
Prospective design 1
Ra
nd
om
ize
d
Genetic analysis
Genotype directed treatmentSampling
Conventional treatment
+
-
+
-
• Increase analytical power of trial• Results are confirmative• May lose a chance of treatment for gene (-) patients
Prospective design 2
Sampling
Placebo
Drug
Treatment
No entry
Ra
nd
om
ize
d
Randomized, double blind, placebo-controlled trial
Enrichment Approach
+
-
Geneticanalysis
Prospective design
Sampling
Placebo
Drug
Placebo
Drug
Treatment
Ra
nd
om
ize
d+
-
Geneticanalysis
Clinical trials identify SNP profile for efficacy or toxicity of drug treatments
Not responds to standard drug treatment
Patient
Individual SNP profile are sorted
SNP profile A SNP profile B
SNP profile D
SNP profile ESNP profile C
Responds to standard drug treatment
Patient with SNP profile A&B given standard drug treatment
IGF2BP2, KCNJ11, and TCF7L2variations influence repaglinide response
and risk of type 2 diabetes
IGF2BP2 binds to insulin-like growth factor 2 (IGF-2), which is an important growth and insulin signaling molecule.
KCNJ11 (potassium inwardly rectifying channel, subfamily J, member 11 gene) encoding Kir6.2 is a candidate gene in relation to T2DM.
TCF7L2 is involved in the growth, differentiation, proliferation, and insulin secretion of pancreatic β-cells. It is involved in the pathogenesis of T2DM.
IGF2BP2 variations influence repaglinide response and risk of type 2 diabetes
b: P<0.05, c: P<0.01compared to AA
Fasting plasma glucose Postprandial serum insulin
Huang Q, Acta Pharmacologica Sinica (2010) 31: 709–717
Total cholesterol Low density lipoprotein-cholesterol
Baseline levels inIGF2BP2 rs1470579genotypes
N=350 T2DM
IGF2BP2 variations influence repaglinide response and risk of type 2 diabetes
b: P<0.05, c: P<0.01compared to AA
Baseline levels inIGF2BP2 rs4402960genotypes
Huang Q, Acta Pharmacologica Sinica (2010) 31: 709–717
Fasting plasma glucose Postprandial serum insulin
Total cholesterolPostprandial serum insulin
IGF2BP2 variations influence repaglinide response and risk of type 2 diabetes
Changes of FPG (A), PPG (B) (post-Pre repaglinide 3mg/d, 8w) in IGF2BP2 rs1470579genotypes
Change of PINS (C) IGF2BP2 rs4402960genotype after treatment of repaglinide
. b: P<0.05; c: P<0.01
N=42
Huang Q, Acta Pharmacologica Sinica (2010) 31: 709–717
: Fasting plasma glucose : Postprandial plasma glucose
: Postprandial serum insulin
Yu M, CPT 2010;87:330-5.
Changes of FPG, PPG, HbA1c after Repaglinide (3mg/d, 8w) in KCNJ11 Lys23Glugenotypes
(N= 40 T2DM)
KCNJ11 Lys23Glu polymorphism affect repaglinide therapeutic effect in T2DM
0
1
2
3
4
5
6
*
a
0
1
2
6
8
10
12 *
△FP
G (m
mol
/l)
△H
bA1c
(%)
△PP
G (m
mol
/l)
b
00.5
11.5
22.5
33.5
44.5
5CGGGA/AA
*
* p<0.05
Fasting plasma glucose Postprandial plasma glucose
Glycated hemoglobin
-16-14-12-10
-8-6-4-20
△FI
NS
(mU
/l)
a
*
0
0.5
1
1.5
2
2.5
△LD
L-c
(mm
ol/l)
C -3
-2
-1
0
1
23
4
5
△TG
(mm
ol/l)
b*
CC/CTTT
*
TCF7L2 rs290487(C/T) polymorphism affect repaglinide therapeutic effect in T2DM
Yu M, CPT. 2010;87:330-5.
Changes of FPG, PPG, HbA1c after Repaglinide treatment (3mg/d, 8wks) in TCF7L2 rs290487(C/T)
genotypes (N= 40 T2DM)* p<0.05
Triglyceride
Fasting serum insulin
Lowdensity lipoprotein-cholesterol
Hypertensive Pateints (n=422)
Randomization
One dose fiting all conventionaltherapy (n=218)
Different dose based on Genotype personalized therapy (n=204)
GP1: 2.5mg; GP2: 25mg; GP3: GP3: 50mg bid for 3 months
25mg bid, for 3 monthes
CYP2D6 and B-recepotor genotyping CYP2D6 and B-recepotor genotyping
CYP2D6 genotypingβ1 receptor genotyping
Low 2D 6 activity, High β1 sensitivityMedian 2D6 activity and β1 sensitivityHigh 2D6 activity, Low β1 sensitivity
Stratified to 3 groups
Hypertension patients stratified by CYP2D6 and β1 -adrenergic receptor genotypes
Hypertension patients stratified by CYP2D6 and β1-adrenergic receptor genotypes.
Low 2D 6 activity, High β1 sensitivityCYP2D6*1*10+Arg389ArgCYP2D6*10*10+Arg389Arg and Gly389Arg
Median 2D6 activity and β1 sensitivityCYP2D6*1*1+Arg389Arg/Gly389ArgCYP2D6*1*10+Gly389ArgCYP2D6*10*10+Gly389Gly
High 2D6 activity, Low β1 sensitivityCYP2D6*1*1/CYP2D6*1*10+Gly389Gly
Low dosen=14
Mid. Dosen=90
High dosen=104
Blood pressure response to metoprolol monotherapy in hypertension patients
0
2
4
6
8
10
12
14
16
18
20
⊿SBP ⊿DBP
Blo
od p
ress
ure
decr
ease
(mm
Hg)
AB
*
*⊿DBP P=0.009 compared with group A.
Efficacy of genotype directed metoprolol monotherapy was significantly higher than conventional therapy
Genotype base therapy vs conventional therapy
* ⊿SBP: P=0.014 compared with group A2;
§ ⊿DBP P=0.014 compared with A2;
† ⊿DBP P=0.034 compared with A2.
0
2
4
6
8
10
12
14
16
18
20
⊿SBP ⊿DBP
Blo
od p
ress
ure
decr
ease
(mm
Hg) A1
A2
A3*
§
†
Reduction in Blood pressure after conventional metoprolol monotherapy in hypertensive patients stratified according β1-adrenergic receptor and CYP2D6 genotype.
Different Genotype and same dosage
Blood pressure response to metoprolol monotherapy in hypertension patients
Reduction in BP after metoprolol monotherapy in hypertension patients stratified according β1-adrenergic receptor and CYP2D6 genotype.
0
2
4
6
8
10
12
14
16
18
⊿SBP ⊿DBP
Blo
od p
ress
ure
decr
ease
(mm
Hg)
A1B1
*
Same Genotype with conventional/genotype base therapy
Reduction in DBP was significantly greater in genotype directed therapy group (12.5mg bid) than the conventional therapy group (25mg bid)
* ⊿DBP P=0.048 vs A1.
Blood pressure response to metoprolol monotherapy in hypertension patients
Blood pressure response to metoprolol monotherapy in hypertension patients stratified according β1-adrenergic receptor and CYP2D6 genotype.
0
5
10
15
20
⊿SBP ⊿DBP
Blood pressure decrease (mm Hg)
A2
B2
Same Genotype with same dose in conventional/genotype base therapy groups
No difference in reduction of BP between A2 and B2 (both are same genotype) after the same dose by conventional and genotype directed therapy
Blood pressure response to metoprolol monotherapy in hypertension patients
Reduction in BP after metoprolol therapy in hypertensive patients stratified according β1R and CYP2D6 genotype. compared with A3.
0
5
10
15
20
⊿SBP ⊿DBP
Bloo
d pr
essu
re d
ecre
ase
(mm
Hg)
A3
B3
*
§
Same Genotype with same dose in conventional/genotype base therapy groups
*⊿SBP P=0.015 vs A3;
§⊿DBP P=0.006
Efficacy of metoprolol in same genotype was significantly higher in genotype based dose adjusted therapy than no dose adjusted therapy
Blood pressure response to metoprolol monotherapy in hypertension patients
Ongoing PGxclinical trial to seek SNPs profile for efficacy and safety of
indapamide, benazepril & losartan
DMET Chip SNP and CNV Correlated analysis
Indapamide n=800400 in each Group
Losartan n= 800 cases400 in each Group
Benazepril n=800400 in each Group
Without ADR
Good Efficacy
Poor Efficacy
Finding of new biomarker for efficacy,dose,toxicy
PyrosequencingRepeating Validation
With ADR
Research Group 400×3=1200
Validation Group 400×3=1200
Grouping Way ⅠGrouping Way Ⅱ (If exists)
Prospective clinical PK study for new biomarker
Essential Hypertensive Patients(2400 cases)
Random Group
863 Program
Design of Ongoing Warfarin Study
5000 patients using warfarin from the 2nd Xangya Hospital
“Derivation” cohort “Validation” cohort
About 1000 patients to test the algorithms
About 4000 patients to create dosing algorithms
Vitamin K
Intake and smoking
INR achieved with a stable warfarin dose
Target INRConcomitant medications
Stable therapeutic dosePrimary indication
Demographic characteristics
Genotype
Retrospective analysis
Endpoint: evaluate the % of validation patients predicted within 20% of the clinically-
correct warfarin dose
Algorithm for initial warfarin dose
Study Design of Tacrolimus
2000 patients using tacrolimus from the 3nd Xiangya Hospital and central south hospital
“Derivation” cohort “Validation” cohort
About 400 patients to test the algorithms
About 1600 patients to create dosing algorithms
Retrospective analysis
Endpoint: evaluate the % of validation patients predicted within 20% of the clinically-
correct tacrolimus dose
Algorithm for initial tacrolimus doseConcomitant
medicationsConcomitant
diseases
Laboratory variables
Target tacrolimus concentration
Stable therapeutic dose
Trough blood concentration
Demographic characteristics
Genotype
Relative use of PGt & PGx
during the process of drug development
TargetID Validate
ScreenDev.
CmpdLib.
Screen
Submitfor
ReviewLead
Optim.Preclin.Studies
Clin.Trials
I II III
PharmacogenomicsPharmacogenomics
PharmacogeneticsPharmacogenetics
Genetic assay is available and reliable/validated
Results are prospectively confirmed
Benefit/Risk can be evaluated even in gene (-)
Enrichment effect is reasonable and acceptable
What is needed for good PGt/PGx
PGx clinical trials in drug development
Ref: Roses, A. Pharmacogenetic and the practice of medicine. Nature, 405, 857-865
Abbreviated SNP linkage disequilibrium profile for efficacy and
common AE
Abbreviated SNP linkage disequilibrium profile for
serious rare AE
Comprehensive medicine response
profile predict efficacy and AE
“Non-responsive” profiles define unmet need Research
Phase II clinical trials
Smaller, faster and more efficient phase III
studies
Market approval with medicine response profile;
pharmacogenetic surveillance
Enhancement with comprehensive medicine
response profile; traditional surveillance
Used to select patients for phase III clinical trials
Application of PGt and PGx in Clinical Trials
Data from CMR International Institute for Regulatory Science 2003
0123456789
Understandingmechanism of action
(13)
Identifying newtargets (9)
Investigating targetpolymorphisms (13)
Stratifying patientsfor ADRs (7)
Stratifying patientsfor PK/PD effects
(12)
Stratifying patientsfor response (9)
Phase I Phase II Phase III Phase IVPhase I Phase II Phase III Phase IV
Mechanism
(13)
Identify Target
(9)
Target Polymorphism
(13)
ADR in Stratify Patients(7)
PK/PD in Stratify Patients(12)
Efficacy in Stratify Patients(7)
Current Applications of Pharmacogenomics
• Interpretation of clinical trial results, data quality, study design, and biomarkers.
• Targeting drugs at genetically-defined populations.
• Three areas of greatest activity– Clinical genotyping
– Pre-clinical gene expression
– Clinical gene expression
Traditional Clinical TrialsTraditional Clinical Trials
Roses, Nature Reviews Genetics, 2004.Roses, Nature Reviews Genetics, 2004.
NonNon--respondersresponders RespondersResponders HyperHyper--respondersresponders
Pharmacogenetic PrePharmacogenetic Pre--ScreeningScreeningIn Clinical TrialsIn Clinical Trials
Roses, Nature Reviews Genetics, 2004.Roses, Nature Reviews Genetics, 2004.
NonNon--respondersresponders RespondersResponders HyperHyper--respondersresponders
-- Smaller, Faster & Less ExpensiveSmaller, Faster & Less Expensive
PGt/PGx in Phase I study
• Phase I studies
– Explain outliers or patient-to-patient variability in PK
– Exclude or include specific patients
– Normalize genotype frequencies
– Bridge to other populations
t 1/2
, hr
1010
2020
3030
4040
5050
Desipramine PK Parameters
CYP2D6 *6/*9CYP2D6 *6/*9
Genotyping can increase trial safety and explain outlying data
CYP2D6 poor metabolizers (2 null alleles) excluded.
One outlier with slow metabolism
Outlier has *6 null allele and *9 allele with reduced enzymatic activity.
Expected occurrence of null/*9 genotype is 0.4%
Adapted from Katz et al., Abbott Labs.Adapted from Katz et al., Abbott Labs.
Extensive metabolizers
Poor metabolizers
35 33
80
140 0
1 2 3Clinical trial center
Nu
mb
er
of
sub
jec
ts
70
140
0
Phase I study on a CYP2D6 substrate
In the trial, any center’s conclusion on tolerance rate, or PK parameters may not be accurately reflect the true of studied population.
PGt/PGx in Phase II/III study
• Phase II/III studies
– Identify genetically-defined groups with more pronounced or rapidly progressing disease
– Exclude/include at-risk individuals
– Stratify studies based on genotypes
• Clinical response
• Risk of adverse events
– Where appropriate, develop drugs for specific groups
– Identify genetic markers associated with clinical outcomes
Extensive metabolizers
Poor metabolizers
95
6380
20
5 7
1 2 3Clinical trial site
Nu
mb
er
of
sub
jec
ts
140-
120-
100-
80-
60-
40-
20-
0-
Phase II study on a CYP2C19 substrate
1 2 3Clinical trial site
Plas
ma
conc
entr
atio
n
50
100
0
5% 10% 20%
Phase II study on a CYP2C19 substrate
ADR rate
5000 events
Genotype, Risk and Events
0.1
1
10
100
1000
10000
100000
1E-10 1E-09 1E-08 1E-07 0.0000010.00001 0.0001 0.001 0.01 0.1 1
Genotype frequency
Indi
vidu
al ri
sk
I I I I I I I I I I I
—
—
—
—
—
—
5000 Events
High frequency of CYP2D6 variants in Caucasians
Highly polymorphic: deletions, critical SNPs, duplications
In Europe
Ingelman-Sundberg TRENDS Pharm Sciences 25, 193-200 (2004)
Relevant for 15 % of the drugs used
CYP2D6DuplicatedMutiplied
CYP2D6 HomozygousDeletionFrameshiftStop codons
CYP2D6 HeterozygousDeletionFrameshiftStop codons
CYP2D6 Two normal alleles
High frequency of CYP2C19 variants in Chinese
Highly polymorphic: critical SNPs/*2, *3
CYP2C19 Homozygous*1 /*1
CYP2C19Homozygous*2, *3, *5
CYP2C19Heterozygous*1/*2, *3j, *5
In China
Log10% 4hydroxymephenytoin excreted
-2.0 -1.0 0 1.0 2.0
180-260 million subjects have no CYP2D6 enzymes (PM)
Too slow drug metabolism
Too high drug levels at ordinary dosage
High risk for ADRs
No response from certain prodrugs
PM
IM
EM
Num
ber o
f sub
ject
s
20
10
0
Zhou HH et al, CPT 1989
Issues Raised by Ethics Committees
• Patient confidentiality/data privacy
• Specify genes
• Scope of sample use for future research
• Length of storage period
• Disclosure of individual results to patients
• Limited sample withdrawal period
• Samples cannot be used for commercial purpose
• Sample ownership
• Investigator role in access/use of samples/data
• Fairness in the use of genetic information– Who should have access to personal genetic
information, and how will it be used?
• Privacy and confidentiality of geneticinformation.– Who owns and controls genetic information?
• Psychological impact and stigmatization due to an individual's genetic differences. – How does personal genetic information affect an
individual and society's perceptions of that individual?
Ethical, Legal and Social Implications
• Reproductive issues– Do healthcare personnel properly counsel
parents about the risks and limitations of genetic technology? How reliable and useful is fetal genetic testing?
• Clinical issues– How will genetic tests be evaluated and
regulated for accuracy, reliability, and utility?Currently, there is little regulation at the federallevel.
Ethical, Legal and Social Implications
• Uncertainties associated with• gene tests for susceptibilities• complex conditions (e.g., heart disease) linked
to multiple genes and gene-environment interactions.
– Should testing be performed when no treatmentis available?
– Should parents have the right to have their minor children tested for adult-onset diseases?
– Are genetic tests reliable and interpretable by the medical community?
Ethical, Legal and Social Implications
• Conceptual and philosophical implications– Do people's genes make them behave in a
particular way? Can people always control their behavior? What is considered acceptablediversity
• Safety and environmental issues concerning genetically altered foods and microbes
• Commercialization of products including property rights (patents, copyrights, and trade secrets)– Who owns genes and other pieces of DNA?
Ethical, Legal and Social Implications
Therapeutic specificity
Direct information receiver
Indirect information receiver
Now
Future
Diagnosis
Diagnosis+ Gene profile
Ethical, Legal and Social Implications
Pharmacy
National health care systems
Insurance companies
Family
Friends
Health care personnel
Other surroundings
Ele
ctr
on
icp
ati
en
tjo
urn
al
Direct information receivers refers to systems that automatically receive information about the patients’ drug usage by the use of for example the electronic patients journal.
Indirect information receivers refers to individuals that intentionally or unintentionally receive information about the patients’ drug usage.
Diagnosis-Therapy-Information flow associated with prescription of a drug
Patient
Patient
Inaccurate choice
Select the exact
PGt & PGxClinical Trial
Center
Phamacogenomic Database
for Chinese People
Technical Systemfor
High-Throughput Assays
Pharmacogenomics Evaluation System
For New Drug
Development
Pharmacogenomics Evaluation System
For Major Disease
Treatment
Technical System for High-ThroughputGene PolymorphismFunctional Testing
Software System forPharmacogenomics
Study
Integrated Technical System for supporting PGt/PGx Clinical Trial in CSU
• Too much enrichment may limit target patients/Indication• Enriched population may not represent a real
population in a practical medicine• Enriched approach may limit the indication for
approval and increase off label use• How much enrichment effect is useful and reasonable?
Prospective design
Out of indication
Target patient
Real target practical medicine
General target in clinical trial
Limited target
Small LargeEnrichment effect
Traditional Clinical TrialsTraditional Clinical TrialsPhase I: Safety and Dosage
Phase II A: Small Safety and Efficacy Study
Phase II B: Large Safety, Efficacy and Dose Ranging Study
Phase III: Comparative Safety and Efficacy; Randomized and Controlled
Non-Responders Responders Hyper-responders
Tested Drug Placebo
Pharmacogenetic PrePharmacogenetic Pre--ScreeningScreeningIn Clinical TrialsIn Clinical Trials
Roses, Nature Reviews Genetics, 2004.Roses, Nature Reviews Genetics, 2004.
Pharmacogenetic Screen
Phase I Phase IIA Phase IIB Phase III Phase III
Non-Responders Responders Hyper-responders
Translation of PGx to Clinical Trials in Drug Development
• DNA samples are being collected in almost all clinical trials by major pharmaceutical companies
• DMET (drug metabolism) chips are used routinely to determine polymorphisms in CYP and related enzymes
• Regulatory agency reviewers always look for PGx factors influencing PK, PD and, through subset analysis, clinical outcomes
Proposal• SFDA should establish policies on categories of PG studies• “Submission requirement” should be included in policy
• Submission not required for some types• Submission required for other types• Some with no regulatory impact
• “Regulatory impact” should be included in policy• Results from some study categories should not have any
regulatory impact• Other study results should be utilized as part of
safety/efficacy evaluation• Possible threshold determination: Does genomic
information represent valid biomarker with known predictive characteristics?
• Develop threshold and policies using public and transparent process with advisory committee oversight
The objectives of this Proposal
Free exchange of data?
Ability of SFDA scientists to begin developing framework for new findings?
Advance the use of the new science?
Examples: With Regulatory Impact (cont.)
• Safety rationale based on animal genomic data--i.e., explaining why a toxic finding is unique to that species
• In general- results intended to influence the course of the clinical development process will be considered part of the S&E evaluation
• Trial enrollment by genotype: enrichment of respondersavoiding bad outcomes
• Selection of dose based on metabolizer genotype
PG results without regulatory impact
• Evaluation of new transporter gene diversity vs response in clinical subjects
• Genomic SNP data collection in clinical trial subjects
• Gene expression microarray screen in trial subjects
• Gene expression microarray screen in animal toxicology study
Unresolved Issues in Application of Pharmacogenomics
What are reasonable expectations of the role of genetics in drug responses?
If a relationship is identified between a genotype and a response, will that lead to specific labeling requirements, even if the drug is safe and effective for the general population?
Will collection of DNA in a clinical trial be a green light for the FDA to request pharmacogenetic studies?
• Will the division of the patient population into multiple genetic subgroups lead to a request for larger studies to enable statistical power for each group?
• What will be the regulatory requirements for tests indicated on the drug label (IVD vs homebrew) and for tests used in genotyping for registrational studies?
• Under what conditions will it be possible to label a drug based on testing of only a pharmacogenetically defined patient group?
Unresolved Issues in Application of Pharmacogenomics
PK Basis for Differences in Drug Response
• Extrinsic factors– environment (smoking, diet, alcohol)– drug interactions (Rx, OTC and herbal)
• Intrinsic factors– demographic (gender, age, race)– disease (renal, hepatic)– pharmacogenetics (PGt)
• polymorphisms in genes encoding metabolic enzymes