personalizing medicine in pacejacques turgeon, b.pharm., ph.d. chief scientific officer, trhc ceo,...
TRANSCRIPT
Jacques Turgeon, B.Pharm., Ph.D.Chief Scientific Officer, TRHC
CEO, TRHC Precision Pharmacotherapy R&D InstituteProfessor Emeritus, Université de Montréal
Fellow, Canadian Academy of SciencesFellow, Académie de Médecine, France
Véronique Michaud, B.Pharm., Ph.D.COO, TRHC Precision Pharmacotherapy R&D Institute
Adjunct professor, Université de Montréal
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Personalizing Medicine in PACE
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Putting Science Back in Pharmacy Practice through Research.
Precision Pharmacotherapy Research and Development Institute
• Enhancing Quality• Saving Lives• Reducing Costs
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Medication Risk Mitigation 3
The Problem: Adverse Drug Events
3.5 million
Patients taking two concurrent medications have a 13% risk of an adverse drug event, rising to 38% for four medications, and 82% for seven or more medications prescribed simultaneously.
2 million
1.3 million
1.7 to 4.6
350,000 39%
50%20.4%
Affected Hospital Stays
Emergency Department VisitsPhysician Office Visits
Increased Days Per Affected Hospital Stay
Hospitalizations Of Seniors in U.S. on 5+ meds(Approx. 20 million people)
Of Seniors in U.K. on 5+ meds (Increase of 12% from 20 years ago)
Readmissions
https://www.cdc.gov/nchs/data/hus/hus15.pdf#079
http://www.telegraph.co.uk/news/2017/11/15/half-over-65s-take-least-five-drugs-day
Adverse Drug Events is estimated to be the 4th leading cause of death— ahead of pulmonary disease, diabetes, AIDS, pneumonia, accidents, and automobile deaths.source: https://www.fda.gov/drugs/developmentapprovalprocess/developmentresources/druginteractionslabeling/ucm110632.htm
source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4716390/
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Providing pharmacists with easy to understand and apply visual clinical decision
support systems at the point of care.
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TRHC Precision Pharmacotherapy Research andDevelopment (PPR&D) Institute is committed tothe development of proprietary products and theirvalidation and recognition by the scientific andregulatory communities to optimize medicationregimen, improve patient outcomes, reduceutilization of various healthcare services, lowerhealthcare costs, and manage risk.
Mission Statement
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The PPR&D Institute vision expands with the emergingresearch initiatives that include bioinformatics,biomedical engineering systems, nanoscale science,patient-specific information, data-driven technologiesand solutions, and translational research.
Vision
Preference Population Personalized Precision Predictive
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1. Preference
Experience
Incentives
PBM
Formularies
Patient’s previous response
Allergies
Other drugsCom
orbi
ditie
s
Guidelines
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2. Population
Results from clinical trials:How much of the average result applies to my patient?
Inclusion/exclusion criteria.
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2. Identification of Medication Risk
Targeted population
Based on total drug regimenBased on drug claimsPrimary design based on PACE data
Our algorithm includes: Anticholinergic BurdenSedative Burden
Adverse Event Odds RatioCompetitive Inhibition
Long QT Syndrome
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2. Identification of Medication Risk
Targeted population
Based on total drug regimenBased on drug claims
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3. Personalized
Evidence-based guided therapy and disease-guidelines modulated by individual characteristics.
Multiple diseases, polypharmacy and multidrug interactions.
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CYP3As
Inhibitors Substrates Inducers
Turgeon et al.
3. Medication Risk Mitigation: The Matrix
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3. Medication Risk Mitigation: The Matrix
3A4
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A 74-year-old man with known hypercholesterolemiaand hypertension, has presented in the recentmonths recurrent angina. A PTCA procedure wasperformed and appropriate platelet inhibitor therapyinitiated (clopidogrel) with GI bleeding protection(omeprazole). The participant also has a depressivestatus and chronic pain. He currently receives 10chronic meds plus multi-vitamins.
3. Medication Risk Mitigation: Case Study
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3. Medication Risk Mitigation: Case Study
Prodrug
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3A4
3. Medication Risk Mitigation: Case Study
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Assuming normal and functional CYP2C19 activity (*1/*1), our pharmacists would recommend to either administer omeprazole and clopidogrel at different times of the day or to change omeprazole for pantoprazole ( ).
3A4
3. Medication Risk Mitigation: Case Study
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4. Precision
How our genetic make-up and inherited characteristics influence drug action: efficacy and toxicity.
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A PGx test is ordered for this PACE participant …
3A4
4. Pharmacogenetic testing in PACE
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A PGx test is ordered for this PACE participant …
1) Since this paricipant is a poor metabolizer for CYP2C19 (non-functional enzyme), the use of clopidogrel is not recommended (CPIC Guidelines) as this is a prodrug with impaired transformation into its active metabolite. Another platelet aggregation inhibitor such as ticagrelor (directly active) should be used instead.
3A4
4. Pharmacogenetic testing in PACE
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4. Pharmacogenetic testing in PACE
Cavallari et al. JACC Cardiovasc Interv 2018;11:181-191
*2/*2
*1/*1
*2/*2 on ticagrelor or prasugrel
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A PGx test is order for this PACE participant …
2) Omeprazole has been shown to be more active in PMs, and did not have to be replaced by another PPI.
3A4
4. Pharmacogenetic testing in PACE
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A PGx test is order for this PACE participant …
1) Since this patient is an ultra-rapid metabolizer for CYP2C19 (hyper-functional enzyme), a lower dose of clopidogrel should be used (CPIC Guidelines) as more of the active metabolite is formed, increasing the efficacy of the drug but also the risk of bleeding.
2) The concomitant use of omeprazole may be seen as a good thing as it would decrease the risk of bleeding due to competitive inhibition and decrease formation of the active metabolite. However, omeprazole will be metabolized more rapidly and expected to be less efficacious.
*17/*17
UM
3A4
4. Pharmacogenetic testing in PACE
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4. Pharmacogenetic testing in PACE
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4. Pharmacogenetic testing in PACE
Bain et al., JAPhA 2018;58:281-289
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4. Pharmacogenetic testing in PACE
Bain et al., JAPhA 2018;58:281-289
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4. Pharmacogenetic testing in PACE
Bain et al., JAPhA 2018;58:281-289
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4. Pharmacogenetic testing in Primary Care
J Am Board Fam Med 10.3122/jabfm.2017.06.170145 on 27 November 2017.
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4. Pharmacogenetic testing in Primary Care
Schwartz et al., J Am Board Fam Med 10.3122/jabfm.2017.06.170145 on 27 November 2017.
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4. Pharmacogenetic testing in Primary Care
Schwartz et al., J Am Board Fam Med 10.3122/jabfm.2017.06.170145 on 27 November 2017.
Phenotype distribution: all patients had at least 1 variant allele, and the majority (66.0%) had >5. Notably, among the genes tested, 36.0% of patients were identified as rapid metabolizers for the CYP2C19 isoform; 40.0% were considered intermediate or poor metabolizers for the CYP2D6 isoform.
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CPIC Guidelines
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CPIC Guidelines
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5. PrecisionDisease-state
How environmental factors and multiple disease-states influence drug action: efficacy and toxicity.
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5. Disease-induced phenoconversion
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5. Disease-induced phenoconversion
Gravel et al. ClinPharmacolTher2019
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Gravel et al. ClinPharmacolTher2019
5. Disease-induced phenoconversion
This suggests that formation of clopidogrelactive metabolite would be decreased and
clopidogrel to be less effective in T2D patients.
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5. Disease-induced phenoconversion
Insufficient generation of the active metabolite
through CYP2C19 could lead to poor
responsiveness in patients with T2D.
Angiolillo et al. JACC 2014
PK assessments revealed that patients with T2D had ~40% less exposure to clopidogrel’s active
metabolite
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5. Disease-induced phenoconversion
• Patients with T2D and treated with clopidogrel have higher number of non-responders, and less platelet inhibition than non-T2D.
• In the OPTIMUS study, 60% of the diabetes patients remained poor responders even though a doubling of the maintenance dose of clopidogrel was used and associated with an increase in platelet inhibition.
Geisler et al. Diabetes Care 2007Angiolillo et al. Diabetes 2005Angiolillo et al. JACC 2007
Platelet response to clopidogrel is attenuated in diabetics.
Residual platelet reactivity after a 600mg loading dose of clopidogrel
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5. Disease-induced phenoconversion
Prasugrel & Ticagrelor?• TRITON-TIMI 38 demonstrated that prasugrel was more
efficacious than clopidogrel in patients with diabetes.
• PROMETHEUS showed that the use of prasugrel was associated with a lower risk of death in diabetic patients (at 90 days and 1 year).
• Studies indicated that ticagrelor and prasugrel have similar platelet inhibitory effects in patients with T2D.
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5. Disease-induced phenoconversion
Prasugrel & Ticagrelor?• TRITON-TIMI 38 demonstrated that prasugrel was more
efficacious than clopidogrel in patients with diabetes.
• PROMETHEUS showed that the use of prasugrel was associated with a lower risk of death in diabetic patients (at 90 days and 1 year).
• Studies indicated that ticagrelor and prasugrel have similar platelet inhibitory effects in patients with T2D.
Drug selection should consider underlying disease state.
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5. Disease-induced phenoconversion
Can other diseases induce phenoconversion? Rheumatoid Arthritis
Morgan Clin Pharmacol Ther 2009
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5. Disease-induced phenoconversion
Use of Biomarkers as a Phenotype Measurement in Patients
• Several probe drugs are used to study the impact of genes, ethnicity, environmental factors, drug-drug interactions on CYP450s.
• The usual phenotyping strategy involves the administration of an exogenous probe drug with serial blood samplings or urine collection.
• The identification of an endogenous biomarker could be of interest as less invasive measure. 6β-OH cortisol:cortisol ratio and 4β-OH cholesterol:cholesterol
ratio have been proposed as markers for CYP3A.
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5. Disease-induced phenoconversion
All population
T2D cohort
Endogenous cholesterol-based metrics could be a suitable markers of CYP3A in patients with inflammatory chronic diseases such as T2D.
The appropriate threshold for dose adjustment needs to be established.
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6. Predictive
New knowledge, machine learning and artificial intelligence allow the construct of predictive models of drug
pharmacokinetics and pharmacodynamics.
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6. Predictive PK-PD Modeling
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7. Predictive in-silico testing
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Predictive PK-PD and in-silico
• Not a single patient included in clinical trials looks like PACE participants taking 15-25 drugs/day.
• Usual software based on one-to-one drug analyses cannot predict DDIs in such patients and cannot provide an appropriate, clinically relevant recommendation.
• Computer simulations using PK-PD models allow us to define complex models of drug combinations and predict drug plasma levels and responses.
• In silico nano-technologies such as “Human-on-a-chip” also allow us to expose human tissues to various drug combinations under various conditions.
• All these approaches provide us with answers without exposing patients to potentially toxic conditions.
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8. Conclusion
• Personalized approaches in the design of drug regimens improve outcomes in patients with polypharmacy.
• Advanced Clinical Decision Support Systems are indispensable tools to help define appropriate drug regimens.
• Precision medicine, including pharmacogenetic testing, help refine drug selection.
• Predictive medicine, using AI and Machine Learning strategies will bring us to even more faultless drug selection.
• All these approaches aim at improving outcomes associated with drug use and decreasing Adverse Drug Events, the 4th
leading cause of death.
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8. Conclusion
Personalized
Precision PGx
Precision DiseasePredictive
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How can PharmacistsMitigate Risk Associated
with Drug-Related Adverse Eventsin PACE Participants?
Thank you