Medication Risk Identification and Mitigation 12019 (NASDAQ: TRHC)Proprietary and Confidential -- © 2019 Tabula Rasa HealthCare, Inc.
Competitive Inhibition and PGx:Managing Accumulative, Multi-Drug Interactions
Veronique Michaud, BPharm, PhDCOO, TRHC Precision Pharmacotherapy R&D Institute
Associate Professor, Université de Montréal
Jacques Turgeon, BPharm, PhD,Chief Scientific Officer, TRHC
Professor Emeritus, Université de MontréalFellow, Canadian Academy of Health Sciences
Fellow, Académie nationale de médecine, France2019 (NASDAQ: TRHC)Proprietary and Confidential -- © 2019 Tabula Rasa HealthCare, Inc.
Medication Risk Identification and Mitigation 22019 (NASDAQ: TRHC)Proprietary and Confidential -- © 2019 Tabula Rasa HealthCare, Inc.
We were co-founders of InterMed-Rx which was licensed to Tabula Rasa HealthCare in 2013.
InterMed-Rx was acquired by Tabula Rasa HealthCare in September 2016. We hold shares in TRHC.
InterMed-Rx was incorporated into the TRHC’s MedWise software enhancing the basic Pharmacodynamics (ACB/Sedative) of the TRHC model.
Disclosure
Medication Risk Identification and Mitigation 32019 (NASDAQ: TRHC)Proprietary and Confidential -- © 2019 Tabula Rasa HealthCare, Inc.
• Recount milestones in competitive inhibition research.
• Explain basic principles as it pertains to bioavailability, drug metabolism and competitive inhibition.
• Evaluate therapeutic effects related to enzyme substrates, inhibitors and inducers.
• Calculate dose changes required under conditions of competitive inhibition.
• Describe how genetic variants may affect drug pharmacokinetics and pharmacodynamics for a series of drugs.
Session Objectives
Medication Risk Identification and Mitigation 42019 (NASDAQ: TRHC)Proprietary and Confidential -- © 2019 Tabula Rasa HealthCare, Inc.
• Recount milestones in competitive inhibition research.
• Explain basic principles as it pertains to bioavailability, drug metabolism and competitive inhibition.
• Evaluate therapeutic effects related to enzyme substrates, inhibitors and inducers.
• Calculate dose changes required under conditions of competitive inhibition.
• Describe how genetic variants may affect drug pharmacokinetics and pharmacodynamics for a series of drugs.
• Discuss drug-induced and disease-induced phenoconversion.
• Introduce the concept of repressor and reverse-repressor as it pertains to new biologics.
And also …
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• Over the last 2-3 decades, transformative changes have been seen in the science and clinical practice of DDIs.
The approach to DDIs has changed since the 1990s.
• Big Pharmas do no longer routinely conduct box-checking clinical DDI studies with narrow therapeutic drugs or with drugs expected to be frequently coadministered.
Leaving all potential DDIs to postmarking reports and hoping them to be not serious.
• DDI assessment is now embedded into a multidimensional optimization approach
Molecular determinants of drug clearance (enzymatic systems, transporters)
Foundational mathematical frameworks for in vitro-in vivo extrapolation and PKPD modeling.
Transformative Changes in the Landscape of DDIs
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Transformative Changes in the Landscape of DDIs
• DDI studies are designed not to answer questions related to specific drug pairs that can be concomitantly administered. Instead, they are performed with well characterized probe substrates, inhibitors or inducers of specific enzymes or transporters.
• Innovations in mechanistic assessment of ADME, PGx, PBPK modeling, understanding DME-mediated DDIs and enzyme-transporters interplay have enabled the emphasis from a descriptive to a predictive science of DDIs:
Health agencies (e.g. FDA, EMA, Japan) adopted a mechanism-informed quantitative translational approach to DDI risk assessment
Moved away from traditional/irrational DDI studies towards informed DDI studies based on in vitro studies combined with translational modeling and simulation.
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Clinical Pharmacology & Therapeutics, Volume: 105, Issue: 6, Pages: 1345-1361, First published: 27 March 2019, DOI: (10.1002/cpt.1435)
Evaluation of DDIs
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Transformative Changes in the Landscape of DDIs
FDA Approves XENLETA (Lefamulin) Injection and Tablets for the Treatment of Adults with Community-Acquired Bacterial Pneumonia (CABP)
Drug Interactions
• Strong and Moderate CYP3A Inducers or P-gp Inducers: Avoid concomitant use of XENLETA Injection and XENLETA Tablets with strong and moderate CYP3A4 inducers or P-gp inducers unless the benefit outweighs the risks. Concomitant use of XENLETA Injection or XENLETA Tablets with strong CYP3A4 inducers or P-gp inducers decreases lefamulin AUC and Cmax, which may reduce the efficacy of XENLETA.
• Strong and Moderate CYP3A Inhibitors or P-gp Inhibitors: Avoid concomitant use of XENLETA Tablets with strong CYP3A inhibitors or P-gpinhibitors. Monitor for adverse effects of XENLETA Tablets when administered concomitantly with moderate CYP3A inhibitors or P-gpinhibitors. Concomitant use of XENLETA Tablets with strong CYP3A inhibitors or P-gp inhibitors increases lefamulin AUC, which may increase the risk of adverse reactions with XENLETA Tablets.
• CYP3A4 Substrates: Concomitant use with CYP3A substrates known to prolong the QT interval is contraindicated. Concomitant use of sensitive CYP3A substrates with XENLETA Tablets requires close monitoring for adverse effects of these drugs. Concomitant use of XENLETA Tablets with sensitive CYP3A4 substrates increases the AUC and Cmax of CYP3A4 substrates, which may increase the risk of toxicities associated with cardiac conduction. Concomitant use of XENLETA Injection with CYP3A4 substrates does not affect the exposure of CYP3A4 substrates.
• Drugs that Prolong QT: Avoid concomitant use of XENLETA Injection and XENLETA Tablets with other drugs that effect cardiac conduction (for example, Class IA and III antiarrhythmics, antipsychotics, erythromycin, moxifloxacin, tricyclic antidepressants). XENLETA has the potential to prolong the QT interval of the electrocardiogram (ECG) in some patients. The PD interaction potential to prolong the QT interval between XENLETA and other drugs that effect cardiac conduction is unknown.
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• With an increasing prevalence of multi-morbidities and polypharmacy in elderly people, it is anticipated that DDIs would occur at an higher frequency:
Clinicians need to understand mechanisms underlying DDIs when facing with complex multi-drug regimens to perform a proper risk assessment of drug-related adverse events.
• Transporter-mediated DDIs represent major challenges.
• Complex and large molecules (e.g. biologics):
Underlying mechanisms of DDIs with biologics are not straightforward (linked to their mechanism of action or modulation of the disease pathophysiology).
Can produce complex effects on the immune system leading to cytokine modulation/or release.
• Many harmful DDIs are based on alterations of plasma concentrations of a victim drug due to another drug causing inhibition, competitive inhibition and/or induction of the metabolism or transporter-mediated disposition of the victim drug.
Knowledge Gaps and Barriers
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Basic Concepts in Enzymatic Processes: Definition
SUBSTRATE : molecule that demonstrates affinity for a protein. This protein iscapable of transforming this molecule by a chemical reaction. Inlay terms, a drug is the substrate of an enzyme if that particularenzyme is able to convert it into a metabolite.
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Basic Concepts in Enzymatic Processes: Definition
INHIBITOR : compound that binds to CYPP450 isoforms but that bindingresults in a decreased activity of the enzyme. Inhibitors maybind at the enzymatic site and thus prevent the binding andtransformation of a substrate (competitive inhibition).
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Basic Concepts in Enzymatic Processes: Definition
INHIBITOR : However, inhibitors can also bind to sites other than theenzymatic site, and lead to a change in conformation (structure)of the protein; this is called inhibition at an allosteric site. Thisinhibition is non-competitive since the substrate could haveaccess to its enzymatic site but the protein is not functionalsince distorted.
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Basic Concepts in Enzymatic Processes: Definition
INDUCER : molecule that is capable of increasing the activity of the enzyme.Generally, the inducer increases the synthesis (i.e. the amount) ofenzymes present thereby increasing the total activity.
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Basic Concepts in Enzymatic Processes
CLint = Vmax / Km
Substrate concentration
Velo
city
of m
eta
bolit
efo
rmation
Metabolite(s)
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Basic Concepts in Enzymatic Processes
CLint = Vmax / Km
Medication Risk Identification and Mitigation 162019 (NASDAQ: TRHC)Proprietary and Confidential -- © 2019 Tabula Rasa HealthCare, Inc.
Basic Concepts in Enzymatic Processes
CLint = Vmax / Km
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The CYP450 system:To understand, manage and predict drug interactions
Substrate
Metabolite
Several DDIs are due to Impaired Drug Disposition
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17 publications on the characterization of mexiletine
metabolismCYP1A2
CYP2D6
CYP450 Superfamily: in 1987, 7 Isoforms. J Turgeon PhD Thesis
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CYP2D6 Involvement in the Metabolism of Na+ Channel Blockers
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Clin Pharmacol Ther 2000;67:44-57
How to take advantage of
phenoconversion.
CYP2D6 and CYP1A2: Mexiletine and Propafenone
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For 3A4 inhibitionCave = 100 / (100 – 50)Cave = 2
For CYP2C9 inhibitionCave = 100 / (100 – 5)Cave = 1.053
The CYP450 Superfamily: Metabolic Pathways (1995-20…)
5%
10%50%
35%
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F = 80%
Time
Log P
lasm
a C
oncentr
ation
0.1
0.01
1
10A small increase in the Cmax is to be expected on first dose.
Clinical Decision Support System: The Matrix
Medication Risk Identification and Mitigation 232019 (NASDAQ: TRHC)Proprietary and Confidential -- © 2019 Tabula Rasa HealthCare, Inc.
• The strategy is to avoid having two substrates of the same isoenzyme being present at high concentrations in the liver/intestine at the same time.
• Give the substrate with the lowest affinity first.
• Determine the Tmax of the substrate with the lowest affinity.
• Give the substrate with the highest affinity with a delay equal or greater than the Tmax of the low affinity substrate.
Clinical Decision Support System: Time of Dosing
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Clinical Decision Support System: Time of Dosing
Medication Risk Identification and Mitigation 252019 (NASDAQ: TRHC)Proprietary and Confidential -- © 2019 Tabula Rasa HealthCare, Inc.
AM J Geriatrics PharmacotherVol 9(6), 2011:461-470
Clinical Decision Support System: Clinical Application
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Clinical Decision Support System: Time of Dosing
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Clinical Decision Support Systems
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•The Innovative CDSS opened the door for translational researches in Pharmacogenomics.
•Possibility to analyze:
Drug-Drug Interactions,
Multi-Drug Interactions,
Drug-Gene Interactions,
Drug-Drug-Gene Interactions (Phenoconversion)
•Machine learning
Complex algorithms
Behavioral analyses
The Value of Innovative Clinical Decision Support System
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Drug-induced Phenoconversion
The use of an advanced clinical decision support systems supported by complex algorithms (artificial intelligence) is mandatory to help clinicians make the appropriate decision.
Some strategies could be developed to prevent phenoconversion, when associated with competitive inhibition.
Pharmacogenomics and Disease state are another conditions to consider.
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Intersubject Variability in Drug Response: PGx as a Causal Factor
Figure adapted from R. BR. Leon-Cachon 2015 & Simonosky 2019
drugs disease
food Etc…
Drug effectiveness
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Pharmacogenetics: Translating a Genotype to a Phenotype
Genotype Phenotype Activity
2 increased function alleles Duplication of functional alleles (*N)
Ultra-Rapid Metabolizer (gUM)
Increased
1 normal + 1 increased function allele2 normal (wild-type) function alleles
1 increased + 1 decreased allele
Normal Metabolizer (gNM)Extensive Metabolizer
(gEM)
Normal(reference)
1 normal + 1 decreased function allele1 normal function allele + 1 null allele
Intermediate Metabolizer (gIM)
Decreased
2 decreased function alleles 2 null alleles
Gene deletionPoor Metabolizer (gPM)
Little to none
*This classification varies based to the gene
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CYP450GCCGCCTC
GCCTCCTC CYP450
Wild-type (ref. as normal expression/activity)
Genetic polymorphism(e.g. altered expression/activity)
Wild-type genotype
Poor metabolizer genotype
X
Pharmacogenetics: Translating a Genotype to Concentrations
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Wild-type genotype
Wild-type genotype
Wild-type genotype
Adapted from DelRe et al. 2017
Intragenotype Variation due to Phenoconversion
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Wild-type genotype
Wild-type genotype
Wild-type genotype
Predicting a patient’s phenotype from his/her genotype is highly complex and not always reliable
Adapted from DelRe et al. 2017
Intragenotype Variation due to Phenoconversion
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Addressing Phenoconversion
• Mismatch genotype-phenotype
Intragenotype differences observed in clinical responses/outcomes
• Phenoconversion usually results from nongenetic extrinsic factors:
Comedications
o As genetically inherited variant traits give rise to DMEs of altered activity, administration of certain drugs can inhibit a DME, mimicking the genetic defect and producing a PM phenocopy or induce the DME converting to an EM or UM phenocopy.
Disease states
Significant impact on the analysis and interpretation of genotype-focused clinical outcome in routine clinical practice
• There is no standardized process by which to translate a genotype into a phenotype assignment.
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Intragenotype variation due Drug-Drug Interactions Leading to Phenoconversion
DelRe et al. Cancer Treatment Rev 2017
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Pharmacogenomics by TRHC
Sample work flow
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Disease-induced Phenoconversion
Figure adapted from R. BR. Leon-Cachon 2015 & Simonosky 2019
drugs diseasefood Etc…
Drug effectiveness
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Clinical Evidence of Disease-induced Phenoconversion
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Adapted from Zanger et al. Pharmacol&Ther 2013
Theoretical Correlation between Disease-mediated Alterations in Drug Metabolizing Enzymes and Drug Levels
Disease
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CYP450s and Inflammatory Cytokines
• CYP450s metabolize a plethora of xenobiotics and are involved in many physiological functions.
• Evidences exist relating the modulatory role of inflammatory mediators on CYP450 activities.
• Infection and inflammation are closely related to hepatic and extrahepatic metabolism by CYP450s.
• Recent knowledge brought light to the impact of inflammatory mediators on the expression of CYP450 enzymes in animal models.
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Evidence Suggestive for Inflammatory Cytokines Suppressing CYP450 Activities
Shah and Smith. DMD 2015
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Pavek Front Pharmacol 2016
REPRESSOR : inflammatory conditions or drugs associated with a downregulation of CYP450 expression.This mechanism requires time.
CYP3A4
PXR activator PXR repressor
Rifampin IL-6, LPS, TNFα
Evidence Suggestive for Inflammatory Cytokines Suppressing CYP450 Activities
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Can T2D Induce CYP450 Phenoconversion?Clinical Evidence: Clopidogrel
• Patients with T2D show highly variable responses to different drugs;
In addition to antidiabetic drugs, the prevention of micro- and macro-vascular complications in T2D generally requires multiple treatments.
Some patients are resistant to certain drugs while others are more sensitive to other drugs.
• Patients with T2D and treated with Clopidogrel have higher number of non-responders and less inhibition of platelet function than non-T2D patients.
Residual platelet reactivity after CLO 600mg loading dose
OPTIMUS study: 60% of T2D patients remained
poor respondersGeisler et al. Diabetes Care 2007
Angiolillo et al. Diabetes 2005Angiolillo et al. JACC 2007
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Can T2D Induce CYP450 Phenoconversion?Clinical Evidence: Clopidogrel
Clopidogrel is a prodrug that requires CYP2C19
activity for transformation into its
active metabolite
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Can T2D Induce CYP450 Phenoconversion?Clinical Evidence: Clopidogrel
• PD assessments revealed that patients with diabetes have ~ 40% less exposure to Clopidogrel’s active metabolite than patients without diabetes.
Poor responsiveness to Clopidogrel in diabetic
patients could be due to insufficient generation
of the active metabolite through CYP2C19.
Angiolillo et al. JACC 2014
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Can T2D Induce CYP450 Phenoconversion?Clinical Study (NTC02291666)
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Can T2D Induce CYP450 Phenoconversion?Clinical Study (NTC02291666)
ClinPharmacolTher2019
1.8-fold
1.9-fold
1.6-fold
*adjusted p-value for age and gender
Metabolic ratios of CYP450 probes
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Can T2D Induce CYP450 Phenoconversion?Clinical Study (NTC02291666)
ClinPharmacolTher2019
Inflammatory markers, T2D and CYP450 activities
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• IL-6 plays a central role in the immunopathogenesis of RA.
• Patients with active RA exhibit high levels of IL-6.
• Elevated IL-6 levels as observed in patients with RA have been shown to modulate CYP450 activities:
Studies using animal rat model of RA showed a decrease of gene expression, hepatic and intestinal activities of CYP450s during the development of induced arthritis.
PK and bioavailability of drugs may be altered in rheumatic diseases.
Rheumatoid Arthritis
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• Disease modifying agents (Biologics) have considerably changed the management of RA.
Often combined with conventional drugs.
• Despite the efficacy and safety profile of biologics (e.g. monoclonal antibody of IL-6 receptor), information on biologics-drug interactions is limited.
• Up-regulation of IL-6 reduces the activity of CYP450 activities, then blocking this cytokine could reverse IL-6 induced reduction of CYP450 expression/activities.
Mallick et al. ExpOpinDrugMetabolToxicol 2017
Rheumatoid Arthritis & Biologics
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Single dose of SIM 40mg to patients with RA at baseline and one week after a single SC dose of sarilumab 200mg (n=17)
Single dose of SIM 40mg to patients with RA at baseline, and one week and 5 weeks after a single SC dose of tolicizumab (injected on day 8) (n=12)
AUC reduced by 54%
AUC reduced by 57%
Bong Lee et al. Clin Pharmacokinet 2017 Schmitt et al. Clin Pharmacol Ther 2011
Could Anti-IL-6 Therapy Reverse the Downregulation of CYP450 Activity Mediated by IL-6?
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• Concomitant oral dosing of 4-probe drugs was used:
CYP3A (MDZ), CYP2C19 (OME), CYP2C9 (warfarin) and CYP1A2 (caffeine).
No CYP2D6 probe was included : inhibition of the IL-6 signaling pathway did not seem to
impact CYP2D6 activity in vivo. (Xang et al. Clin Pharmacol 2009)
Zhuang et al. J Clin Pharmacol 2015
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AUC x30-35%
X37-45%
X18-20%
x20-34%
Zhuang et al. J Clin Pharmacol 2015
Could Anti-IL-6 Therapy Reverse the Downregulation of CYP450 Activity Mediated by IL-6 in an Isoform-dependent Manner?
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Morgan. Clin Pharmacol Ther 2009EvaluatePharma. Worldwide review 2014
• Biologics are immunomodulators including immunosupressor and immunostimulator agents: the impact of biologic treatment on drug
metabolism will be dependent on the pro- or anti-inflammatory properties of the biologics.
• Within the top 100 prescription products in 2020, biological products expected to account for more than 50% of sales.
Rheumatoid Arthritis : May Biologics Reverse Phenoconversion?
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Morgan. Clin Pharmacol Ther 2009
Reverse-REPRESSOR:molecule capable to restore/reverse cytokine-mediated suppression of DMEs and transporters.The magnitude of reversion is variable and it requires time.
Rheumatoid Arthritis : May Biologics Reverse Phenoconversion?
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• The use of advanced Clinical Decision Support Systems is of great value for the establishment of personalized, more precise and improved drug regimen.
• Pharmacogenetic results accurately predict phenotype in healthy subjects taking no medications. Correspondence in homozygous with variant alleles.
• Polypharmacy is clearly associated with risk of phenoconversion
Time of administration Order of administration
• Inflammatory diseases can modulate drug disposition e.g. T2D and RA Biologics may restore partially CYP450 activities. Biologic-drug-disease interactions could impact the safety and effectiveness of concomitant
drug regimen.
• Magnitude of these effects is also influenced by the PK properties of the drug.
Conclusion
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Thank you