Role of genomics in pharmacovigilance prof. MUDr. Ond ej Slana , - PowerPoint PPT Presentation

Role of genomics in pharmacovigilance prof. MUDr. Ond ř ej Slana ř , Ph.D. Daepartment of Pharmacology, 1st Faculty of Medicine, Charles University in Prague General Teaching Hospital, Prague 1

2 The Wall Street Journal, Friday, April 16, 1999

Genetics in cancer therapy • Healthy (host) cells: > 12,000,000 SNPs > 100,000 VNTRs > 1500 CNV • Cancer cells: > 12,000,000 SNPs > 100,000 VNTRs > 1500 CNV + tumor-specific aquired Mutations

Genetic biomarkers • Disease Risk – To identify SNPs that put individual to higher risk of disease development • Early detection – diagnosis • Predictive – Treatment/dose selection 4

How much do we know about genetic biomarkers? Real life example - Rare disease X • 2,300 theoretical non-synonymous point mutations that lead to unique single amino acid substitutions • 800 identified so far – Recent annual rate 40/year • 600 tested for predictive value for treatment Y – 250 has a predictive value for treatment Y 5

PGx pre-/post-approval guidance EMA FDA Pre-approval Post- Pre-approval Post- approval approval When to + -/+ + - sample DNA When to + -/+ + - conduct PGx genotyping + -/+ + - methodology EU PGx in pharmacovigilance guideline in preparation/draft version 6

The European Medicine Agency’s decision-making tree 7 Maliepaard et al 2013

PGx in the PhV • systematic consideration of pharmacogenetics in the risk management plan (RMP) – Extent of PG effects and implications on BM use in target population – whether use in patients with unknown or different genotype could be a safety concern or requires additional data to be generated – If important genomic polymorphism identified but not fully studied , this should be reflected in safety specification and PhV plan 8

post-authorisation collection of genomic data • Pharmacogenomic surveillance system: genomic biological samples should be collected prior to prescription • Every patient receiving a medication and experiencing serious ADRs or lack of effectiveness should be encouraged that genomic samples be collected especially in the initial post-authorisation phase • Collaborative actions , such as a consortium (biobanking)-based approach involving MAHs, academia and regulatory authorities 9

Risk Evaluation • genomic BM testing for idiosyncratic reactions – precisely define the clinical variables – frequencies of genetic variants in relevant population – PPV and the NPV calculated • genomic BM related to PK or PD – drug concentrations, in addition to lack of efficacy or particular toxicity • phenotype cannot always be predicted from a genotyping • the presence or absence of therapeutic alternatives should be considered 10

Level of evidence • Ideally, data from well conducted RCT(s) • Retrospective data analysis – Biological sample or BM status availability from all or majority of the subjects from RCT – Prospectively planned – Replication of results – Biological plausibility – Difference between BM+ vs BM- is large – Isolated retrospective observations are expected to provide confirmatory evidence whenever clinically and ethically appropriate 11

Risk minimisation measures • Label information – based on SPC guideline • Additional RM – restricted access to the medicinal products based on specific test – a patient registry – additional educational materials to the prescribers or patients regarding important PGx information 12

Effectiveness of RM measures • Knowledge on the recommendations on BM use • Are the recommendations followed • Availability /use of the test

A genetic test Shall demonstrate • analytic validity • clinical validity • clinical utility • ethical, legal and social implications Centers for Disease Control and Prevention 14

Utility of PGx test Drug PhV HTA patients registration Treatment +/- +++ +++ +++ +++ Maximum + +++ ++ +++ efficacy/safety Relative efficacy - + ++ +++ 15

Abacavir • registred 1999, prospective confirmation study Mallal et al. 2008, clear clinical validity/utility • HLAB*5701 (all races) 6-8% in Caucasians , 1% in Asian populations and less than 1% in African populations • Hypersensitivity, serious • 48% to 61% of patients with the allele vs 0% to 4% of patients without the allele • PPV 55%, NPV 100% 16

SPC section 4.1 – Indications Abacavir (Ziagen) Before initiating treatment with abacavir, screening for carriage of the HLA-B*5701 allele should be performed in any HIV-infected patient, irrespective of racial origin. Abacavir should not be used in patients known to carry the HLA-B*5701 allele, unless no other therapeutic option is available in these patients, based on the treatment history and resistance testing. 17

Thiopurin S-methyltransferase (TPMT) % population TPMT 12 O 2 N N N 10 N S N CH 3 N NH TPMT 5 Azathioprine TPMT TPMT frequency 0.3 % PM 0 11 % IM 0 5 10 15 89 % EM TPMT activity [u/ml RBC] Woodson, J Pharmacol Exp Ther 1982; 222 :174 18

AZA azathioprine 6-MP 6-merkaptopurine TPMT hypoxantin-guanin-fosforibosyltranferase 6-methyl MP thio-IMP thio-inosinmonophosphate inosin-5‘-monofosphate dehydrogenase guanosin-monophosphate- TPMT syntetase Thioquanine methyl-thio- IMP metabolites 19

AZA azathioprine 6-MP 6-merkaptopurine TPMT hypoxantin-guanin-fosforibosyltranferase 6-methyl MP thio-IMP thio-inosinmonophosphate inosin-5‘-monofosphate dehydrogenase guanosin-monophosphate- TPMT syntetase Thioquanine methyl-thio- IMP metabolites 20

TPMT • Strong evidence that PM are at extremely high risk for development of myelosupression (80-100%) • the size of the effect of TPMT variant alleles on the risk of myelosuppression ? 21

SPC Imuran PGx information section 4.4. Deficiency TPMT – high risk for myelotoxicity … . … ..genetic test does not identify all patients at risk 22

Does PGx translate in the clinics ? Gen No of labs Conducted (phenotype+genotype) tests (phenotype+genotype) CYP2C9 6 3 warfarin CYP2C19 4 2 phenytoin NAT2 4 150 Pseudocholinest. 16 2000 Suxamethonium/mivacurium TPMT 6 2500 AZA/6-MP 23 (2003, Australia + New Zeeland) Sharon et al, Pharmacogenetics, 15, 2005, 365-369

Does PGx translate into the clinics? 328 prescribing physicians of AZA, 65% screen for TPMT 1982 1995 2015 TPMT phenotype by 67% (n = 189) respondents (dermatologists 94%, gastroenterologists 60%, rheumatologists 47%) 91% of testing was carried out prior to prescribing AZA Genotype testing is not typically available to NHS clinicians but 5% (n = 15) clinicians (2% dermatologists, 2% gastroenterologists, 1% rheumatologists) reported using it. Fargher EA, J Clin Pharm Ther. 2007 Apr;32(2):187-95. 11 rheumatologists of AZA, 55% screen for TPMT, province of Saskatchewan Taylor-Gjevre et al. 2013 24

Warfarin • approval in 1954 • VKORC1 gene 2004 • Multiple candidate gene studies: – VKORC1 and CYP2C9 genotypes influence the inter- patient variability in warfarin dose requirements, together explaining 10–45% of the overal variance • confirmed by several GWAS 25

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Warfarin • COUMAGEN-II Anderson et al. 2012 – PG dosing led to significantly fewer out-of-range INRs at 1 and 3 months • The Clarification of Optimal Anticoagulation through Genetics (COAG ) Kimmel et al. 2013 – No diference in percentage of time within therapeutic INR range (45% in both arms), in African American lower (TTR 35% versus 43.5%) • European Pharmacogenetics of Anticoagulant • Therapy (EU-PACT) Pirmohamed et al. 2013 – PG dosing led to significantly higher percentage of time within therapeutic INR range (67% vs. 60%, p 0.001)

28 Xu et al. 2014

29 Xu et al. 2014

Warfarin • GIFT study results to come – powered to detect a difference in thrombotic and major bleeding events with genotype-guided dosing • ENGAGE AF-TIMI 48 trial 14,348 patients 4833 taking warfarin (Mega et al. 2015) – sensitive and highly sensitive responders spent greater proportions of time over-anticoagulated in the first 90 days of treatment – and had increased risks of bleeding with warfarin (sensitive responders hazard ratio 1.31, 95% CI 1.05-1.64, p=0 · 0179; highly sensitive responders 2.66, 1.69-4.19, p<0 · 0001). – greater early safety benefit from edoxaban compared with warfarin 30

Warfarin • Controversy if PGx improves treatment if treatment managed correctly and patients monitored …… is this the situation in reality? • screening for all patients - still controversy • PGx may help to identify reason for suboptimal treatment outcomes 31

Warfarin SPC PGx info 32

SPC PGx info Ehmann et al. 2014

Ehmann et al. 2014

Conclusions I Individualization via PGx • Fully personalised medicine (autologous cellular therapy) • Multiple-stratified personalised medicine (TPMT, breast ca) • Bimodal-stratified personalisation (HER2+/HER2-) 35

Conclusions II • Challenges in obtaining the information post- approval • Hesitance of prescribers to use the tests, especiall for products long on the market • Over-optimistic expectations by lab workers • Valid PGx biomarkers appeared in recent years, data for others on the way 36

Thank you for your attention 37