Personalized Care Medicine Based on Your Genetics
Peter H. O’Donnell, M.D.
Department of Medicine
Committee on Clinical Pharmacology and Pharmacogenomics
Center for Personalized Therapeutics
The University of Chicago
“If it were not for the great variability among individuals, medicine might as well be a
science and not an art.”
--Sir William Osler (1892)
Pharmacogenomics
• Study of the effect of genetic variation on drug response or toxicity
Potential Advantages
• Adverse drug reactions are 5th leading cause of death in U.S.
• Efficacy rates for common drugs treating prevalent diseases are ~50%
• Health care system wastes millions of dollars on poor prescription drug choices
Davies et al., Curr Drug Saf. (2007)
Langley et al, Pharm World Sci (2005)
Altman, Clin Pharmacol Ther (2011)
cdc.gov
A Drug Example
• Simvastatin: #2 most prescribed drug in the U.S. – 83 million prescriptions/year
• One of several choices for treating hypercholesterolemia – alternatives include other statins,
non-statins
• Limited in its use by the occurrence of myopathy
Herper M., “America's Most Popular Drugs” Forbes. May 11 2010
Another Drug Example: Is Clopidogrel Effective for Your
Patient?
Clopidogrel Use: Gene Carrier Status Increases Risk
Mega et al., NEJM (2009) *Primary efficacy outcome: death, MI, or stroke
53%
increased
risk in allele
carriers
Proton Pump Inhibitors
Heidelbaugh et al., Therap Adv Gastroent (2012)
$11 billion worldwide expenditures on this class of drugs (#2 overall)
1st Generation Proton Pump Inhibitor and CYP2C19
Furuta et al., Eur J Clin Pharmacol (2009)
McNicholl et al., Aliment Pharmacol Ther (2012)
Should Choice of PPI Be Based on CYP2C19?
A Clinical Decision “Calculus”
Precision Medicine – Are We Ready? • Survey of >10,000 U.S. physicians:
– 98% believe genetic profiles may influence drug therapy
– 13% had ordered a PGx test
– 26% believe they will order one in next 6 months
– 10% feel adequately informed about PGx testing
Stanek et al., CPT (2012)
• “Pharmacogenomics can play an important role in identifying responders and non-responders to medications, avoiding adverse events, and optimizing drug dose”
• >140 different drugs are listed on this site, all having PGx information contained in their drug labels
fda.gov
Haga et al., Pharmacogenomics J (2012)
Patients as Drivers?
Cost vs Benefit
Clinical genotyping costs now are approximately 50¢ per variant per person
Lala et al., J Thromb Haemost (2013)
Cost Effectiveness
Barriers to Realizing Pharmacogenomic Implementation
• PGx test availability
• Delay in obtaining results
• Lack of provider knowledge
• Provider concerns regarding interpretation, translation
• Clinical relevance of current PGx evidence
• Cost
Hypothesis
Providing preemptively-obtained pharmacogenomic results at the time of
prescribing will improve prescribing decisions, and patient outcomes
“Genomic
Prescribing
System” (GPS)
from Ratain CPT 2007
Elements of the Project
1) TECHNICAL – Create customized pharmacogenomic
test panel; accurately measure genotypes
2) TRANSLATION/EDUCATION – Create clinical summaries of the
pharmacogenomic literature for use in interpreting tested genotypes
3) KNOWLEDGE TRANSFER – “GPS”—electronic dissemination and
instantaneous availability of results for access at any clinical moment
4) IMPLEMENTATION SCIENCE – Measure the results of deploying the
pharmacogenomic intervention for best prescribing
Participants Patients
• Adult outpatients receiving care from study physician at academic medical center
• Must be taking at least 1 regularly-used prescription medication, but not more than six
Physicians
• Primary Care (7)
• Oncology (3)
• Cardiology (2)
• Gastroenterology (1)
• Hepatology (1)
• Pulmonology (1)
• Nephrology (1)
• Executive Health (1)
Average Yrs in Practice = 20 (range 3-46)
UChicago Custom PGx Panel
>7,000 pharmacogenomic
publications/800 drugs
Key Features
BROAD SCOPE
(all relevant drugs)
PREEMPTIVE TESTING
(not reactive)
BUNDLED, “LIFETIME” TEST
(reduces marginal cost)
PATIENT and PROVIDER
ENGAGEMENT
cancer.uchicago.edu
Results
• 1214 patients have been approached for participation
– 87% of patients approached have consented
• 1052 patients currently enrolled
• 720 have been genotyped
Top Diseases of Enrolled Patients Disease # of Patients Percentage
Hypertension 518 52%
Hypercholesterolemia 396 40%
GERD 168 17%
Obesity 152 15%
Arthritis 139 14%
Coronary Artery Disease 120 12%
Diabetes Mellitus 115 12%
Obstructive sleep apnea 101 10%
Anemia 99 10%
Hypothyroidism 97 10%
Most Frequently Prescribed Medications Drug # of Patients Percentage
Aspirin* 344 33%
Hydrochlorothiazide* 216 21%
Atorvastatin* 197 19%
Lisinopril 170 16%
Amlodipine* 141 13%
Levothyroxine 121 12%
Metoprolol* 115 11%
Fluticasone Propionate* 113 11%
Omeprazole* 90 9%
Losartan 83 8%
Simvastatin* 82 8%
Metformin 73 7%
Acetaminophen 67 6%
N=1052
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
I feel veryinformed
I feel somewhatinformed
I feel somewhatunder-informed
I feel veryunder-informed
13%
50%
31%
6%
% o
f R
esp
on
den
ts
How Informed Do
You Feel About
PGx?
0%
10%
20%
30%
40%
50%
60%
70%
Never Almost Never Sometimes Frequently AlmostAlways
63%
13% 19%
6%
0% %
of
Res
po
nd
ents
Have PGx
Results Changed
Prescribing
Methods in Prior
6 Months?
Physician Characteristics
Average Yrs in Practice = 20 (range 3-46)
34(1.3%)
100%
33% 6%
n=881 (33%)
70%
n=1413 (54%)
25%
3%
Use and Impact of GPS
% clicked to receive
clinical details:
1786 clinic encounters 73% with GPS log-in 2640 result signals
% Rx changed:
At 89% of visits, PGx
information available
for at least 1 drug
patient was taking
N=6992
1.9%
New Medications Prescribed
66%
of the time info provided, GPS influenced the
decision
34%
(77/227) had an alert available for that changed med
76%
(227/298) logged into GPS when
prescribing a new med
298
New Meds Prescribed
Discontinued Medications
75%
of the time info provided, GPS influenced the
decision
52%
(65/124) had an alert available for
that changed medication
77%
(124/161) logged into GPS when discontinuing a
med
161
Meds Discontinued
9 89% (8/9) 88% (7/8)
Med Changes
Influenced by GPS
Med Changes Where
Physician Saw Alert
Total Meds
Changed Alert Color
79 72%
(57/79) 72%
(41/57)
124 80%
(99/124) 62%
(61/99)
Medication Changes By Alert
Pe
rce
nta
ge
Note: Possible to choose more than one answer
Reasons Provided for Using GPS to Influence Medication Change
Ease of Use GPS was simple to use GPS result summaries
are too complicated or
technical
53% 47%
Agree strongly
Agreesomewhat
Disagreesomewhat
Disagreestrongly
7%
67%
27%
I am likely to enroll other patients so that I can use GPS for them
0
1
2
3
4
5
6
7
8
9
10
Agree strongly Agree somewhat Disagree somewhat Disagree strongly
Nu
mb
er o
f R
esp
on
ses
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
I feel veryinformed
I feel somewhatinformed
I feel somewhatunder-informed
I feel very under-informed
Baseline
All SurveysPost-GPS
Per
cen
tage
of
Res
po
nse
s How Informed Do You Feel About Pharmacogenomics?
Participant Responses “The genetic profile suggested that there would be a higher
benefit, and less of a chance of side-effects…and I have numbers to show his cholesterol and LDL are much better than they had been previously” --Project MD 1
“In this age of medicine, a lot of it is about shared decision-making, and bringing technology to that” --Project MD 2
“The new genetic information is very helpful when considering alternatives among a class of drugs such as mental health drugs, which traditionally have been prescribed on a ‘let’s see if this helps’ basis. It helps eliminate some and focus on others. Thank you for your study!” --Patient
How was your provider at being interested in you as a whole person?
Per
cen
tage
of
Res
po
nse
s
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Excellent Very good Good Fair Poor
ConsultedGPS
Did NotConsult GPS
Control
I wish my care was more “individualized”
Per
cen
tage
of
Res
po
nse
s
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
AgreeStrongly
AgreeSomewhat
Not Sure DisagreeSomewhat
DisagreeStrongly
Influencedby GPS
Notinfluencedby GPS
No Login
Conclusions
• Successfully implemented an individualized health care model of preemptive pharmacogenomic testing
• Patient interest robust; physician adoption high
• PGx alerts had widespread applicability to patients and to drugs being prescribed
• Delivered results were utilized during office visits
• Physicians report that availability of PGx information is relevant to their practice, and worthy of repeated use
Future Directions • Larger number of
patients and physicians
• Outcomes Measurements
– decrease adverse/ non-response events
• Integrate GPS with EMR
• Engagement of other providers (e.g., pharmacy, nursing)
Routine Clinical
Use
PHASE II/III RESEARCH
PHASE I COMPLETION
How Many Might Benefit…
1/3
of us +
3/4
of us
the lifetime utility of comprehensive pharmacogenomic testing may be substantial
?
Project Team
Keith Danahey Mark Ratain Jerry Yeo David Meltzer
Ishai Strauss
Linda Patrick-Miller
Others
Emanuele Agolini
Edward Leung
Russ Altman (Stanford)
Yusuke Nakamura
Sheena Hussain Nisha Wadhwa Paula Friedman Paige Galecki Debby Stoit
Amy Kaufman
Rebecca Wellman
Acknowledgements NIH K23 GM100288-01A1
NIH/NHLBI 5 U01 HL105198-09
Bucksbaum Institute Associate Faculty Scholar Pilot Grant
Chicago Innovation Exchange - Innovation Fund
The University of Chicago Cancer Research Foundation Auxiliary
The William F. O’Connor Foundation
The University of Chicago Center for Personalized Therapeutics
