Lon Cardon

Quantitative Sciences

GlaxoSmithKline

Capitalizing on the human genomeApplications and interface with academia for medicine discovery and use

Complex disease gene discovery

Perception &Promise

1990s Early 2000s 2006+

Tech

nolo

gy:

Hum

an G

enom

e Pr

ojec

t

RFL

P, m

icro

sate

llite,

SN

Ps

Stud

ies:

Can

dida

te g

enes

‘Gen

ome-

wid

e’ li

nkag

e

1000s ‘discoveries’ –unreplicated

GWAS

GWAS: large(-ish) samples + specific traits + subset of genome

Disease Gene Discovery: 2007

Human genetics points of impact

New targets ADME

Efficacy/Pers Med

Safety

Drug repositioning

Drug Discovery & Development

MarketTarget ID Validate target Candidate First time

humanProof of concept

Phase II to III

• Efficacy. Few examples of responder v non-responder (cf oncology)

Why?• Theory: multigenic with small effects• Practice: well-designed studies not yet conducted …a future opportunity for collaboration

Less than expected success

• New Targets. Clear point of interface, but limited success Genetic data often one small piece of puzzle

Safety Efficacy Unmet need Plausible mechanism … Genetically validated …

Continued optimism

1996: Microsatellites & linkage

2007: SNPs & genome-wide association

2010: Rare variants & sequencing

Present areas of translational genetics success

Oncology (becoming mainstream)

Mechanism of action (ad hoc but highly informative)

Rare Diseases (sequencing technology enabling wave of progress)

Adverse Events (numerous and increasing, but implementation lags behind discovery)

SampleMale CADMale MI

Cases28901134

Controls31283128

OR0.770.72

0.5 0.6 0.7 0.8 0.9 1 1.1 1.2

Adverse Events Genetics

Antiretroviral drug abacavir commonly used in treatment of HIV-1

Abacavir hypersensitivity reaction (ABC HSR) observed– Multiorgan clinical syndrome– Rechallenge is permanently contraindicated and can be fatal– Affects ~8% of clinical trial patients

Abacavir hypersensitivity

1 Control Arm Data Only

OR (immunulogically confirmed, white): 0.03 (0.00 – 0.19)Mallal et al, NEJM 2008

Pos Neg

Immunologically Confirmed HSR1

HLA-B*5701

23 0

25 794

Pos PV48%

Neg PV100%

Sens 100%

Spec 97%

HSR

No HSR

Consequences of a predictive genetic marker: Abacavir

Goldman & Faruki 2008. Genetics in Medicine 10: 874-78. Graph courtesy LabCorp

• Treatment guideline changes

DHHS (USA) BHIVA (British HIV Association, UK) UK guidelinesEACS (European AIDS Clinical Society) pan-

European guidelines

• Regulatory Recommendations

GSK Core Safety Information, Aug 2007‘EU Summary of Product Characteristics update,

Jan 2008US Prescribing Information update, July 2008

• HSR reduction based on screening

W. Australia, UK, France, US

• Increase in HLA*B5701 tests

Genetic Influences on ADR RiskLarge effects, predictive utility

DrugAdverse Drug Reaction Genetic Risk Factor

Reaction Prevalence

Risk Allele Freq.1 Effect2

Clopidogrel Cardiovascular events 0.13 CYP2C19*2/3/4/5 0.03 3

Gefitinib Diarrhea 0.28 ABCG2 Q141K 0.07 5

Isoniazid Hepatotoxicity 0.15 CYP2E1*1 & NAT2 0.133 7

Co-amoxiclav Hepatotoxicity <0.001 HLA-DRB1*1501 0.20 10

Irinotecan Neutropenia 0.20 UGT1A1*28 0.32 28

Ticlopidine Hepatotoxicity (cholestatic)

<0.001 HLA-A*3303 0.14 36

Tranilast Hyperbilirubinemia 0.12 UGT1A1*28 0.30 48

Flucloxacillin Hepatotoxicity <0.001 HLA-B*5701 0.04 81

Allopurinol Severe cutaneous reaction

<0.001 HLA-B*5801 0.15 678

Abacavir Hypersensitivity reaction 0.08 HLA-B*5701 0.04 >1000

Carbamazepine

Stevens-Johnson <0.001 HLA-B*1502 0.04 >1000Following from Nelson et al, 2009. Pharmacogenomics J

But AE predictions not always ‘perfect’

• Large effects do not always mean ‘perfect’ prediction (cf abacavir)

• Imbalanced prediction (NPV/PPV) people at risk excluded with some certainty some people not at risk denied otherwise effective treatment

Variables affecting utility:• Indication• Risk/benefit• Access

Genetics expectation was to differentiate on individual-level efficacy, but reality today is potential to differentiate on individual-level risk

Summary (1): Applications today

Genetics has under-delivered on translation promise

Genetic findings of practical utility now exist

They are not widely used

Why not?

Physician education

Market and culture

Engagement of regulators

….

Widespread availability of tests

If the genotyping data were readily and simply available at the time of prescribing, should it be used? Stated this way, the answer would almost certainly be “yes”. Roden and Shuldiner, Circulation, June 2010

Summary (2): Towards populationsCollaboration to capitalize

Genetic factors have translational utility today

To broadly exploit the genome, greatest challenges are not– Technology– Computation / how to analyze data– Know-how

Greatest need involves clinically well-characterized collections

Genetics discovery with populationsGenetics translation with samplesGenetics applications applied to individuals

Genetics, Biobanks & Electronic Medical Records

All pieces in place– Large numbers of individuals– Rich, broad clinical information – High throughput, complete

genome, low-cost technology

Convergence opens up the genome– Sub-group identification– Natural settings to see consequences of up/down protein levels– Treatment comparisons: both safety and efficacy– New indications for existing treatments– ..more

Meslin, EM & Goodman, KW (2010) Science Progress

Individual Population Individual

Single gene disorders

Complex disorders

Biobanks toElectronic Medical Records

Start here

Acknowledgements

GSKVincent MooserMatt NelsonJohn WhittakerColin SpraggsStephanie ChissoeFrank HokePhilippe Sanseau

WellcomeTrustNIH/NHGRI