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Personalized Medicine

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Hayley Browdy

on 2 March 2013

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Transcript of Personalized Medicine

History and Current State Personalized Medicine
By: Hayley Browdy, Jenny Horn and Danna Pinto What is personalized medicine? Very basically, it is medical care that is tailored to an individual based on a variety of factors that include...
• age
• genetics
• gender
• concurrent disease
• concurrent drug therapy
• environmental agents such as smoking and ethanol
• pharmacokinetics In the way we will be discussing...
Personalized medicine involves integrating genomic technologies and advances with the understanding and interpretation of clinical and family histories in order to tailor therapeutics to individual patients

A key component of personalized medicine is making the science of pharmacogenetics apply clinically so that genetic make-up can be the foremost indication of the effectiveness and safety of a particular drug or treatment. History The concept of genetic differences affecting a person's response to their biochemical environment has been well respected and researched for over one hundred years

This concept has become what we know now as pharmacogenetics which has become the way to explore personalized medicine
-For instance in 2007, clinical trials employing pharmacogenomic strategies yielded 97 completed trials and another 144 in process at the time which is a significant amount with a focus on the basis of what is now termed personalized medicine GWAS: Genome Wide Association Study GWAS studies are aimed at detecting variants at genomic loci that are associated with complex traits in the population and associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders.

As of an article published January 13th 2013, GWAS has lead to the following accepted ideas...
1.) Many loci contribute to complex-trait variation
2.) At a number of identified risk loci, there are multiple alleles associated with disease at a wide range of frequencies.
3.) There is evidence for pleiotropy, i.e., that the same variants are associated with multiple traits
4.) A number of variants associated with disease or complex traits in one ethnic population are also associated the same disease or traits in other populations

This is important because it helps to validate the idea that personal medicine has been and can continue to happen and will eventually lead to a complete look at our genetics to determine the best treatment for any given person. Problems with GWAS 1.) Most of the associations with a disease condition are inconclusive and their functional significance is elusive
2.) Results are not always readily replicated
even when they can be replicated the associations can be weak
3.) It targets common diseases
ex: cardiovascular diseases are the leading cause of death- so even a weak association can have a significant population impact Pharmacogenetics: Selecting Optimal Therapy Pharmacogenetics: Avoiding ADRs The Future of Personalized Medicine Questions? Scenario Described in 2000 1.) Shortly after person is born genotype record at Physicians office
2.) Information transmitted to secure database
3.) A decision support system is set up
-physician may prescribe personal immunization and screening schedule and -recommend specific preventive measures
-genotyping information complemented by screening program based on bio-molecular profile
--screening may lead to recommendation about lifestyle or nutrition
--detection of early stages of disease
--leads to refined diagnosis and choice of personalized therapy Where can it take us? Genomic and computational technologies increasing impact on the pharmaceutical companies
(LEFT ARROW) The same technologies will be adapted and used to directly serve patients which can lead to more personalized and information driven medical care
(RIGHT ARROW) System Applications Integrated Model to Genomic Medicine In the American Health care industry several trends, where genomics factors in heavily, are pointing towards development of model for personalized medicine...
1.) US consumers asked to shoulder more of their share of health care cost
-By exposing health care to greater consumer pressure market forces will expand choices and maybe options for individualized care
2.) Consumers more informed about their own health and the broad range of the choices that are available to them
3.) Pharmaceutical industry is under siege from reports of ADRs, patent expiration, generic competition, complaints about pricing, declining number of new drug approval
4.) Advances in biotechnology
-Provides opportunities to take a biological approach to treating individuals Policies Promoting Personalized Medicine -In March 2005, FDA released "Final Guidance on Pharmacogenomics Data Submissions"
-Genomic technology is becoming cheaper
Cost and Benefit analysis must also be done
Society must grapple with the price of health care in the genomic age
*How the resources will be allocated in a just and equitable way

The government has demonstrated its commitment to personalized medicine
1.) FDA launched the Critical Path Initiative which helped incorporate genetic advances into development of medical products and drugs
2.) Obama as senator in 2006 introduced a bill that would accelerate genomic research, diagnostics and treatments
-Last May similar bill was proposed
3.) FDA also created a new position last year to coordinate genomic activities within the agency
4.) In March the National institutes of health announced that they would establish a voluntary testing registry by 2011 to provide comprehensive information about the more than 16000 clinical laboratory genetic tests available
5.) About 10% of new drug labels contain information one genes and drug response Healthcare Costs Personalized medicine may not lower the costs of health care
-May reduce the use of ineffective medications and cost of adverse side effects
-But may not lower drug development costs
-Different drugs targeting different population segments; must produce more drugs that fit individual genotypes Need a methodical and systematic approach that is rooted in evidence-based science
1.) Using meticulous data and sample collection
2.) Testing of approaches
3.) Computational methods for judging and interpreting information
-Must be meaningful to scientists, clinicians and patients
4.) Clinician involvement is critical
-Ability to interpret tests
-Must perform ongoing outcomes research to adjust existing models based on results How do we integrate Genomics into healtcare? Integration Process Direct to Consumer Genetic Testing -There are dozens of genetic tests that are available in the US that people can purchase on their own
-The results and interpretation of these tests can be misleading or inconsistent
*Only few companies have genetic counselors on staff to help interpret results
-The FDA is trying to regulate these tests
-They sent letters to genetic testing companies to inform them that they needed approval to market their devices Ethical Complications Justice and the Jagged Edge How do we decide who gets certain treatments and medication?
-In reality there is a jagged edge
~Some people benefit a lot, some do not at all and some will somewhat benefit
~This is a fundamental problem for medicine advancement
Who should make the decision?
-Clinicians ? or Patients?
-Should we rely on panels of specialists
-Should we rely on administrations of health plans and health facilities to trim the ragged edges and establish limits
Rough justices versus the status quo
-Is the status quo morally preferable?
~Individuals with excellent private health insurance or Medicare have access to extraordinarily expensive drugs at little direct expense to themselves even if these drugs are marginally beneficial to them
~While those without good health insurance or any at all might not have access to drugs that could potentially do them a lot of good Bevaizumab (Avastin)-Targeted biological drug for breast cancer (costs 100,000)
-It only extended life by a few months
-But there were marked differences in survival among people with specific genotypes
~People with VEGF (AA/AA) genotype-had the longest survival from all other subgroups (49.7) months
~Overall median was 26.7

Should the drug be approved for the small percent of patients who are likely to benefit the most? Example 1 Example 2 Panitimumab (vecibix) and Cetuximab (Erbitux)
-Patients with no mutation sin the codon 12 and 1 of the KRAS gene
~Can prolong life by 2 years in patients with out these mutations
~Not all the patients without this mutation show the same response
~Further research must reveal additional genetic factors that affect median survival

Is it moral to deny the drugs at social expense to all patients who would gain less than a year of life?
Should patients be told to pay for these expensive therapies and be led to believe that they will prolong their lives by a lot when it may not be so? Example 3 Erlotinib (Tarceva) and Gefitinib (Iressa)
-Epidermal growth factors receptor (EGFR) inhibition is the key to successful treatment for non-small-cell lung cancer
~They are TKIs- tyrosine kinase inhibitors
~These drugs work best in patients with mutations in EGFR exons 19 and 21
~Some researchers suggest that TKIs be limited to these patients
~Other studies show that patients without these mutations also derive significant survival benefit from TKIs
They have lower response rates that those with the mutations
Should side effects be taken into consideration to determine who should have access to expensive drugs?
-These expensive therapies might have milder side effects than chemotherapy
-Doctors and patients may find it unacceptable to restrict use of targeted therapies based on genomic information Addressing Variability The "optimal" drug that would be safe and effective for all patients does not exist
-Inter-individual variability is inherent in drug therapy
~Serious adverse events
~Variability in target or maintenance dose
Personalized medicine: individualized therapy guided by clinical, genetic, genomic, and environmental information
-Pharmacodynamics: individual response to drugs depending on the mechanisms of the disease
-Pharmacokinetics: individual response to drugs depending on how a patient handles a drug
~Polymorphisms in genes encoding drug-metabolizing enzymes and drug transporters Implications of Personalized Medicine Therapeutic Drug Monitoring Programs (TDM)
-Use serum concentration-time data to optimize pharmacotherapy
-Not performed until after drug is administered

-Studying a single genetic variant with a drug response phenotype
~Treatment responders and non-responders (assessment of drug efficacy)
~Serious adverse effects (drug toxicity)
1.) Selection of patients with the highest probability of therapeutic efficacy
2.) Reduction of adverse drug reactions (ADRs)
3.) Determination of the most appropriate drug dosage to provide efficacy and safety of the treatment

-Surveying the entire genome for associations with drug response phenotypes Goal: Reduce Trial-and-Error Prescribing Example #1: Breast Cancer
-30% of cases are characterized by over-expression of over-expression of a cell surface protein called Human Epidermal Growth Factor Receptor 2 (HER2)
~Standard therapy ineffective
~Herceptin (trastuzumab), an antibody drug, can reduce the recurrence of a tumor by 52% when used in combination with chemotherapy (compared to chemotherapy alone)
~Molecular diagnostic tests for HER2 identify patients who will benefit from Herceptin and other drugs that target HER2
-Oncotype DX and MammaPrint~Complex diagnostic tests that place patients into risk categories
~Determine whether the cancer may be treated successfully with hormone therapy alone, avoiding chemotherapy, or whether a more aggressive treatment is needed

Example #2: Colon Cancer
-40% of patients suffer from tumors that have a mutated form of the KRAS gene
~Standard therapy ineffective; will not respond to Erbitux (cetuximab) and Vectibix (panitumumab)
-Only patients with the normal (wild-type) form of the KRAS gene should be treated with these drugs in conjunction with chemotherapy Example #3: Late-Stage Cancers
-Targeted therapies paired with genetic tests providing hope to late-stage cancer patients and their families
~Melanoma patients that have the BRAF V600E gene mutation and whose cancer cannot be surgically removed can be treated with ZelboraTM (vemurafenib)
~Non-small cell lung cancer patients who express the abnormal anaplasticlymphomakinase (ALK) gene can be treated with Xalkori (crizotinib)
~Both BRAF and ALK mutations can be detected by commercially available tests, cobas 4800 BRAF V600 Mutation Test and Vysis ALK Break Apart FISH Probe Kit

Example #4: Stents and Blood Clots
-Plavix (clopidogrel): blood-clot preventing drug-Varied impact on protecting stent patients from thrombosis
~Depending on patients' genetic variance within CYP2C19, which encodes an enzyme that converts the drug from an inactive to an active state
-25-30% of stent patients have a 3-fold risk of stent thrombosis when using Plavix relative to other patients
-A genetic test can reveal the risk and allow physicians to create an alternative course of treatment, i.e. the drug Effiant (prasugrel) Limiting Use to Genetically-Defined Patient Populations -A drug that failed in clinical trials or that was withdrawn from the market can be revived by limiting its use to genetically-defined patient populations
1.) Iressa (gefitinib)
~The lung cancer drug did not demonstrate a survival advantage in a general population and was withdrawn from the market
~10% of patients who test positive for epidermal growth factor mutations demonstrate benefit
2.) Bucindolol
~The Beta-blocker was being tested for the treatment of heart disease but was dropped
~Beta-blocker Evaluation of Survival Test (BEST): diagnostic test to predict who will benefit from the drug -Most prescribed medications are effective in no more than 60% of the individuals in whom they are used
-About 5.3% of all hospital admissions are associated with ADRs
-Many are the result of variations in genes that code for the family of cytochrome P450 (CYP450) enzymes and other drug-metabolizing enzymes
~cause a drug to be metabolized either faster or slower than normal
1.) "overdose toxicity": result of trouble with inactivation of the drug and elimination
2.) ineffectiveness: elimination of the drug too rapidly before it has had a chance to work
-"poster-child for pharmacogenomics research"
used to prevent blood clots
-needs to be closely monitored because patients whose Warfarin levels are not maintained within its very narrow therapeutic index are at risk for clotting or bleeding
-Common genetic variants in two genes, CYP2C9 and VKORC1, have been associated with dosing variability that can lead to possibly fatal adverse effects
-Therefore, the FDA recommends genotyping for all patients before Warfarin treatment
~genetic testing to target the dosing of Warfarin could prevent 17,000 strokes in the U.S. and could avoid as many as 43,000 visits to the emergency room Example #1: Warfarin
-nucleoside reverse transcriptase inhibitory that is used in combination with other anti-retroviral medications for the treatment of HIV
-6% of patients undergoing treatment have a genetic variant in HLA-B*57:01 that leads to a hypersensitivity reaction
~symptoms: fever, rash, fatigue, cough, gastrointestinal symptoms, and dyspnea (shortness of breath)
-in 2008, the FDA implemented a black box warning recommending that all patients be screened for HLA-B*57:01 before abacavir treatment Example #2: Ziagen (Abacavir)
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