Personalized Medicine - Genomics

Maria Judit Molnar

2014

The Personal Genome Project is a long term, large cohort study

Aims to sequence and publicize the complete genomes and medical records of 100,000 volunteers, in order to enable research into personal genomics and personalized medicine.

It was initiated by Harvard University in 2005.

The Personal Genome Project is a long term, large cohort study

Aims to sequence and publicize the complete genomes and medical records of 100,000 volunteers, in order to enable research into personal genomics and personalized medicine.

It was initiated by Harvard University in 2005.

Personal Genome Project

• The individuals agree to make their genome and their health records public.

• „volunteers… willing to share their genome sequence and many types of personal information with the research community and the general public,

• Aim: to understand genetic and environmental contributions to human traits.”

The project publish the • genotype (the full DNA sequence), • phenotype: medical records, various

measurements, MRI images, etc. • all data are within the public domain• made available over the Internet so that

researchers can test various hypotheses about the relationships among genotype, environment and phenotype.

Risks

Dealing with bad news

Genotype and phenotype

Some variants predicting severe effects in the PGP-10

Some variants predicting severe effects in the PGP-10

Participant Variant Putative effect

PGP5 (hu9385BA) PKD1-R4276W Autosomal dominant polycystic kidney disease

PGP6 (hu04FD18) MYL2-A13T Hypertrophic cardiomyopathy

PGP9 (hu034DB1) SCN5A-G615E Long QT syndrome

PGP10 (hu604D39) PKD2-S804N Autosomal dominant polycystic kidney disease

PGP10 (hu604D39) RHO-G51A Autosomal dominant retinitis pigmentosa

PGP CanadaPGP Canada

PGP UKPGP UKPGP HarwardPGP Harward

Risk-Benefit Ratio

The roots

„ It’s far more important to know what person the disease has than what disease the person has.”

Hippocrates (BC. 400)

The paradigm of the classic treatments

SymptomDiagnosis TreatmentDosage

Non specificNon selectivUniformized

Phenotype

Trial and error

Does not evaluate the different therapeutic response - the blockbuster concept

The medicine in the XX. century

• „One fits to all”

• The target is the disease

• Evidence based medicine– statistical approach using the rule of large numbers,

resulting in statistically meaningful conclusions

Paracelsus

(1493-1541)

“The dose makes the poison.”

But differently for genetically different individuals

The revolution of the molecular biology:

Right DiseaseRight DiseaseRight PatientRight Patient

Right DrugRight DrugRight TimeRight Time

Ineffective therapies – waste money

Hypertension Drugs 10-30%

ACE Inhibitors $390 million – $1.2 billion

Heart Failure Drugs 15-25%

Beta Blockers $345 million – $575 million

Anti Depressants 20-50%

SSRIs $2.3 billion – $5.8 billion

Cholesterol Drugs 30-70%

Statins $3.8 billion – $8.8 billion

Asthma Drugs 40-70%

Beta-2-agonists $560 million – $1.0 billion

The results in 2013

• The most drugs are not or partially effective in the 60% of the treated patients

• Side effects are responsible for– 100,000 death– 2 million hospitalisations– 100 billion USD cost for healthcare in USA– 50%- of the cases is related genetics

Personalized Medicine: The Answer?

Definition

The use of information and data from a patient’s genotype andphenotype (level of gene expression and/or clinicalinformation) to:

– stratify disease

– select a medication

– provide a therapy

– initiate a preventative measure that is particularly suited to that patient at the time of administration

Personalized Medicine is an emerging practice of medicine that uses an individual's genetic profile to guide decisions made in regard to the prevention, diagnosis, and treatment of disease

Focus on the clinical needs!

“Bench to Bedside” “Bedside to Bench to Bedside”

However genomic determinate the potential biological and physiological reactions of the individual, we can not miss the analysis of the environmental effects.

The bigest weakness of the clinic nowadays is the lack of the exact diagnosis and the inapropriate determination of the stadium of the disease.

The classical therapy:Uniformisation

Observation Treatment Uncertain respond

Observation Testing (Biomarker) Treatment Predictedrespond

Targeted therapy:Differenciate, diagnostics and drug co-development

Independently from the heterogeneity of the population try to get in large cohorts positiv results/risk ratio with the treatment (clinical utility)

Targeted therapies help by identificatioon of the patients with the best respond and less side effects

Biomarkers are such diagnostic tools, wich may predict the therapeutic respond to a certain drug

Healthcare pressure:Risk / benefit ratio

Economical pressure:Cost / benefit ratio

New Technologies:Expanding possibilities

Needs of highly differentiated healthcare, which effects the health of the person and society

Only the really innovative medicine is justifiedInnovative ~ Personalized, Differentiated

The key drivers of the paradigm change in the healthcare - 2013

The Power of Information - Moore’s law

Computer processing power is doubling every 18 monthsAmount of data is doubling every 18 months

Power of technology

Technological improvement

• Genomic revolution of the end of the 20.th century– Completing the Human Genom Project (2000)

• „Only” 25 thousand genes – vs 100 thousand– Computed genotyping, DNA microarray– „$1000 Genom”

• „Nobody expected”:– 25thousand genes – 9 million SNP– The function of 30% of the genes is uncleared– The role of deletions, duplications, CNVs– Microsatellite polymorphisms– Epigenetic

Forrás: Jose de Leon, Pharm Res 59 (2009) 81-89 alapján

PM impacts diagnostic categories

A new era in genomics medicine?

• Human genome project

• Direct-to-consumer genomics

• Intellectual property disputes– Catalona– Myriad Genetics– Henrietta Lacks

• Personal Genome Project

Drug discovery paradigm shift: a problem or an opportunity?

• Ever increasing demand for safer medicine• Stark realization that drug discovery is expensive and slow

– shrinking budgets, consolidation, outsourcing• Current drug inventory is large, diverse and possibly has a

lot more to offer than was initially thought• Increasing availability of genomic data and tools to

use/understand it

Genomic data in the patient care

Monogenic vs Complex Disorders

Monogenic Disorders: Success story

Complex disorders: limited success rate

Age related macula degeneration

Apolipoprotein E Genotype and Alzheimer Disease

• Metaanalysis of 40 study• 5.930 patient and 8.607 control

A mutation in APP protects against Alzheimer’s disease and age-related cognitive decline and Alzheimer Disease

Thorlakur Jonsson et al.

Nature 2012; 488, 96–99 (02 August 2012) doi:10.1038/nature11283

A coding mutation (A673T) in the APP gene protects against Alzheimer’s disease

This substitution results in an approximately 40% reduction in the formation of amyloidogenic peptides in vitro.

The change of disease concept

Traditional: reductionist, one single factor

Causal factor Disease

Basic risk

Environmental factors

Preclinicalprogression

Disease onset

Diseaseprogression

Irreversiblechanges

New conception: multifactorial

Egészségre Egészségre gyakoroltgyakorolt

hatáshatásSNPSNP combinations combinations

Other SNPsEnvironment

Köztesfenotípus

Effect on the Effect on the healthhealthIntermedier

phenotype

Complex, polygenic, multifactorial disease

Egészségre Egészségre gyakoroltgyakorolt

hatáshatásMutMutationation

Other SNPsEnvironment

intermediateintermediatephenotypephenotype

Effect on the Effect on the healthhealth

Intermedierphenotype

Monogenic disease

New Disease Concept

The old paradigm: Treatment of the disease

0

10

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30

40

50

60

1. n.év 2. n.év

Diagnosis

Select drug

Switch drug

Switch drug again

Time

Reactive medical care

Dis

ease

sev

erity

To effective health management

0

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1. n.év 2. n.év

ScreeningPredisposition

Diagnosis/Prognosis

Right Drug

Time

Efficient medical care

Dis

ease

sev

erity

Monitoring

Social expectations

• Cheaper, more effective drug development

Forrás: Business Insights: Expanding Applications of Personalized Medicine, 2009

Social expectations

United StatesDepartmentof Genetic Identity

Louis Cipher12230 Pacific Ave.Los Angeles, CA 90024

HolographicSequence Data

ISSUE DATE0 2 - 0 5 -2 0 0 1

IDENTIFICATION NUMBERJ Q-85 3-64 3-8 49 3-23 07

This card required for allmedical services: tamperingvoids National Health Coverage

Scruples

• Healthpolitical questions• Regulatory issues• Financing aspects• Insurance consequence

– USA: Genetic Information Nondiscrimination Act (2008)

• Ethical questions– How to sell the test laymens?

FDA prohibited to sell the testFDA prohibited to sell the test

What will likely happen??

Personalized medicine will involve pharmacogenomic treatment approaches that transcend the „one-size-fits-all”

approach

Personalized medicine will focus on keeping people well and treating disease at its earliest stages!

Laboratory medicine will lead the way!

„Disease signatures” comprised of hundreds or thousands of data point will be the biomarkers of the future

Drug companies will develope their markets around interventional treatments for „disease signatures”!!

The POTENTIAL for Personalized MedicineA „Wellness” Vision

• A new comprehensive and integrated approach to wellness – prevention of chronic disease, early detection of disease risk and individualized treatment plans

• Predictive toxicology for new drug candidates – ability to predict which individuals will benefit and those who might be most at risk for experiencing serious side-effects

Healthy Pre-disease Diseased RecoveringRoutine ComprehensiveHealth Status Monitoring

New diagnostics Disease prediction Preventative therapies

Earlier disease detection

New interventional therapies

New diagnostics

Accurate disease diagnosis

Personalized treatment

Informed treatment decisions

Real-time Disease Reoccurrence Monitoring

•People adopting healthier lifestyles

•Timely testing of environmental exposures

•Improved economics of disease screening

•Reduced occupational exposures

•Timely medical interventions

•Reduced hospitalizations

•More timely therapy

•Reduced unnecessary referrals

•More efficient treatment plans

•Improved outcomes

The POTENTIAL for Personalized Medicine

Increased Healthcare Quality and Reduced Costs (?)

Predict and prevent chronic diseasesKeep people out of the hospitalEliminate adverse drug eventsImprove drug developmentCreate new markets

The POTENTIAL for Personalized MedicineTransform Healthcare Markets

Today

HC markets on numbers of sick people might be treated with a new drug

MetricMorbidity and mortality

rates

OutcomePeople suffer and die from

chronic and preventable diseases with multiple hospitalizations

Tomorrow

HC markets based on numbers of people with preventable diseases

MetricNumber of people positive for valid

predictive biomarkers

Outcome• New era of interventional

therapeutics• People will live healthier, pain-

free lives and die of old age or trauma with minimal hospitalizations

Multiplex biomarkers to predict and guide treatment of early chronic Dz

We Can’t do This Now!!

Current Personalized MedicineApproaches Limited To:

PharmacogenomicsElectronic Health Records

Great Start – But does not yet address the all technologies

required for prediction and prevention

State of the Art in HC Measurement Technologies

Despite Major Progress over the Last 25 Years, Healthcare

Measurement Technological Capabilities is Limited to: Digitalizing medical records

Measuring a few serum biomarkers

Identifying simple genetic defects/differences

Imaging gross anatomical features and detect major changes

Imaging some disease-associated molecular mechanism

Comparing mRNA expression patterns between healthy and diseased cells

Statistical analysis of research for evidence-based medicine

The Personalized Medicine Gap

The lack of adequate measurement technology limits the vision for personalized medicine

We simply do not have the tools to measure the biochemical details of the human body with the

resolution needed to fully-realize the amazing potential of personalized medicine

Need to Know the Root Cause of Chronic Disease

But…

Human Cells are Extremly Complex

Diseases are the result of perturbations in complex biomolecular networks

PreventionBRCA1/2 - Breast and ovarian tu.

prophyilactic tamoxifen and surgery

EffectivityOncology

Herceptin – breast cancerCetuximab – colon tumor

Rare disease: cystic fibrosis Ivacaftor G551D mutation in CFTR geneSafety

VKOR/CYP2C9 – warfarin dosing

PM in the clinical practice

Multiplex Tests are Already Starting to Have an Impact

OncoType DXAnalyzes by qPCR, mRNA expression of a panel of 21 genes within a tumor to

determine a Recurrence Score

MammaPrintMicroarray-based prognostic breast cancer mRNA expression profiling test of 70 genes

AlloMapqPCR-based expression profile of 11 genes to assist physicians in managing heart transplant patients for potential organ rejection

Tissue of OriginMicroarray technology considers 15 common malignant tumor types, including bladder, breast,and colorectal tumors based on mRNA expression on 1,550 genes

A kihivások

New Technologies for Determination of „Disease Signatures”

Changes in biomolecular networks indicative of the onset or progression of disease

Normal Human System

100 trillion cells 6 billion basepairs

30,000 genes 10 million different proteins 100,000’s of molecular events 50 organs and organ systems

ABNORMALITIES

Multiplex Measurements

Computer Integration

Cell- or Tissue-specific Disease Probablity Score

•Increased Drug Pipeline

•Improved Diagnostics

•New Predictive Biomarkers

•Decrease Adverse Events

•Improve Clinical Outcome

•Fewer Errors & Misdiagnoses

•Predict Disease Onset

•Prevent Disease

•Reduce Health Care Costs

Discovery Decisions

Clinical Decisions

Changes due to P4 Medicine

• More innovative, patient-centered, proactive medicine that will be predictive, preventive, personalized and participatory rather than reactive

• The role of physician is changing

• Patients increasingly need „coaches” to help them dealing with complexity of „data clouds”, monitor their health and wellness

• Broadening the definition of patient (not only limited to thick persons)

• Social media and e-health will influence the healthcare

Fears from the P4

• Payer: increasing expenses?

• Physician: decreasing margin?

• Patient: certain drugs are inaccessible?

• Authorities: how to deal the complex situation?

• Diagnostic lab: more test with bed financing?

• Industry: – Narrowing market?– New financing strategy? ??

Too soon for conclusions

New ideas about self, privacy, medicine, and freedom

Ethics

Conclusion

We tend to overestimate the effect of technology in the short run and underestimate the effect in the long run

Amara’s Law

Figuring out how to use that information to improve your medical care is personalized medicine's next great challenge