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Lewis GJ, Ahire D, Taskar KS. Physiologically-based pharmacokinetic modeling of prominent oral contraceptive agents and applications in drug-drug interactions. CPT Pharmacometrics Syst Pharmacol 2024; 13:563-575. [PMID: 38130003 PMCID: PMC11015076 DOI: 10.1002/psp4.13101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 11/24/2023] [Accepted: 12/13/2023] [Indexed: 12/23/2023] Open
Abstract
Considerable interest remains across the pharmaceutical industry and regulatory landscape in capabilities to model oral contraceptives (OCs), whether combined (COCs) with ethinyl estradiol (EE) or progestin-only pill. Acceptance of COC drug-drug interaction (DDI) assessment using physiologically-based pharmacokinetic (PBPK) is often limited to the estrogen component (EE), requiring further verification, with extrapolation from EE to progestins discouraged. There is a paucity of published progestin component PBPK models to support the regulatory DDI guidance for industry to evaluate a new chemical entity's (NCE's) DDI potential with COCs. Guidance recommends a clinical interaction study to be considered if an investigational drug is a weak or moderate inducer, or a moderate/strong inhibitor, of CYP3A4. Therefore, availability of validated OC PBPK models within one software platform, will be useful in predicting the DDI potential with NCEs earlier in the clinical development. Thus, this work was focused on developing and validating PBPK models for progestins, DNG, DRSP, LNG, and NET, within Simcyp, and assessing the DDI potential with known CYP3A4 inhibitors (e.g., ketoconazole) and inducers (e.g., rifampicin) with published clinical data. In addition, this work demonstrated confidence in the Simcyp EE model for regulatory and clinical applications by extensive verification in 70+ clinical PK and CYP3A4 interaction studies. The results provide greater capability to prospectively model clinical CYP3A4 DDI with COCs using Simcyp PBPK to interrogate the regulatory decision-tree to contextualize the potential interaction by known perpetrators and NCEs, enabling model-informed decision making, clinical study designs, and delivering potential alternative COC options for women of childbearing potential.
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Affiliation(s)
- Gareth J. Lewis
- Drug Metabolism and Pharmacokinetics, In Vitro In Vivo Translation, Research, GlaxoSmithKlineStevenageUK
| | - Deepak Ahire
- Department of Pharmaceutical SciencesWashington State UniversitySpokaneWashingtonUSA
| | - Kunal S. Taskar
- Drug Metabolism and Pharmacokinetics, In Vitro In Vivo Translation, Research, GlaxoSmithKlineStevenageUK
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2
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Evangelista JE, Clarke DJB, Xie Z, Marino GB, Utti V, Jenkins SL, Ahooyi TM, Bologa CG, Yang JJ, Binder JL, Kumar P, Lambert CG, Grethe JS, Wenger E, Taylor D, Oprea TI, de Bono B, Ma'ayan A. Toxicology knowledge graph for structural birth defects. COMMUNICATIONS MEDICINE 2023; 3:98. [PMID: 37460679 PMCID: PMC10352311 DOI: 10.1038/s43856-023-00329-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 06/29/2023] [Indexed: 07/20/2023] Open
Abstract
BACKGROUND Birth defects are functional and structural abnormalities that impact about 1 in 33 births in the United States. They have been attributed to genetic and other factors such as drugs, cosmetics, food, and environmental pollutants during pregnancy, but for most birth defects there are no known causes. METHODS To further characterize associations between small molecule compounds and their potential to induce specific birth abnormalities, we gathered knowledge from multiple sources to construct a reproductive toxicity Knowledge Graph (ReproTox-KG) with a focus on associations between birth defects, drugs, and genes. Specifically, we gathered data from drug/birth-defect associations from co-mentions in published abstracts, gene/birth-defect associations from genetic studies, drug- and preclinical-compound-induced gene expression changes in cell lines, known drug targets, genetic burden scores for human genes, and placental crossing scores for small molecules. RESULTS Using ReproTox-KG and semi-supervised learning (SSL), we scored >30,000 preclinical small molecules for their potential to cross the placenta and induce birth defects, and identified >500 birth-defect/gene/drug cliques that can be used to explain molecular mechanisms for drug-induced birth defects. The ReproTox-KG can be accessed via a web-based user interface available at https://maayanlab.cloud/reprotox-kg . This site enables users to explore the associations between birth defects, approved and preclinical drugs, and all human genes. CONCLUSIONS ReproTox-KG provides a resource for exploring knowledge about the molecular mechanisms of birth defects with the potential of predicting the likelihood of genes and preclinical small molecules to induce birth defects.
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Affiliation(s)
- John Erol Evangelista
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Daniel J B Clarke
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Zhuorui Xie
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Giacomo B Marino
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Vivian Utti
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Sherry L Jenkins
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Taha Mohseni Ahooyi
- The Children's Hospital of Philadelphia, Department of Biomedical and Health Informatics; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Cristian G Bologa
- Department of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Jeremy J Yang
- Department of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Jessica L Binder
- Department of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Praveen Kumar
- Department of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Christophe G Lambert
- Department of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Jeffrey S Grethe
- Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Eric Wenger
- The Children's Hospital of Philadelphia, Department of Biomedical and Health Informatics; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Deanne Taylor
- The Children's Hospital of Philadelphia, Department of Biomedical and Health Informatics; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Tudor I Oprea
- Department of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Bernard de Bono
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Avi Ma'ayan
- Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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3
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Application of exposure bracketing to streamline the development of contraceptive products. Contracept X 2022; 4:100072. [PMID: 35243326 PMCID: PMC8857469 DOI: 10.1016/j.conx.2022.100072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 01/05/2022] [Accepted: 01/20/2022] [Indexed: 11/20/2022] Open
Abstract
Developing new long-acting products of well-characterized contraceptive drugs is one way to address some of the reasons for unmet need for modern methods of family planning among women in low- and middle-income countries. Development and approval of such products traditionally follow a conventional paradigm that includes large Phase 3 clinical trials to evaluate efficacy (pregnancy prevention) and safety of the investigational product. Exposure-bracketing is a concept that applies known pharmacokinetics and pharmacodynamics of a drug substance to inform its safe and efficacious use in humans. Several therapeutic areas have applied this concept by leveraging established drug concentration-response relationships for approved products to expedite development and shorten the timeline for the approval of an investigational product containing the same drug substance. Based on discussions at a workshop hosted by the Bill & Melinda Gates Foundation in December 2020, it appears feasible to apply exposure-bracketing to develop novel contraceptive products using well-characterized drugs.
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Srinivasan M, White A, Lott J, Williamson T, Kong SX, Plouffe L. Quantifying the economic burden of unintended pregnancies due to drug–drug interactions with hormonal contraceptives from the United States payer perspective. Gates Open Res 2021; 5:171. [DOI: 10.12688/gatesopenres.13430.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/10/2021] [Indexed: 11/20/2022] Open
Abstract
Background: In the United States of America (USA), nearly 10 million women use oral contraceptives (OCs). Concomitant administration of certain medications can result in contraceptive failure, and consequently unintended pregnancies due to drug–drug interactions (DDIs). The objective of this analysis was to estimate the economic impact of unintended pregnancies due to DDIs among women of reproductive age using an OC alone or in combination with an enzyme inducer co-medication in the USA from a payer perspective. Methods: A Markov model using a cohort of 1,000 reproductive-age women was developed to estimate costs due to contraceptive failure for OC alone versus OC with concomitant enzyme inducer drugs. All women were assumed to begin an initial state, continuing until experiencing an unintended pregnancy. Unintended pregnancies could result in birth, induced abortion, spontaneous abortion, or ectopic pregnancy. The cohort was analyzed over a time horizon of 1 year with a cycle length of 1 month. Estimates of costs and probabilities of unintended pregnancy outcomes were obtained from the literature. Probabilities from the Markov cohort trace was used to estimate number of pregnancy outcomes. Results: On average, enzyme inducers resulted in 20 additional unintended pregnancies with additional unadjusted and adjusted costs median (range) of USD136,304 (USD57,436–USD320,093) and USD65,146 (USD28,491–USD162,635), respectively. The major component of the direct cost is attributed to the cost of births. Considering the full range of events, DDIs with enzyme inducers could result in 16–25 additional unintended pregnancies and total unadjusted and adjusted costs ranging between USD46,041 to USD399,121 and USD22,839 to USD202,788 respectively. Conclusion: The direct costs associated with unintended pregnancies due to DDIs may be substantial and are potentially avoidable. Greater awareness of DDI risk with oral contraceptives among payers, physicians, pharmacists and patients may reduce unintended pregnancies in at-risk populations.
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Lingineni K, Chaturvedula A, Cicali B, Cristofoletti R, Wendl T, Hoechel J, Brown JD, Vozmediano V, Schmidt S. Determining the Exposure Threshold for Levonorgestrel Efficacy Using an Integrated Model Based Meta-Analysis Approach. Clin Pharmacol Ther 2021; 111:509-518. [PMID: 34674227 DOI: 10.1002/cpt.2457] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 10/07/2021] [Indexed: 01/16/2023]
Abstract
Combined oral contraceptive pills are the most commonly used hormonal contraceptives for the prevention of unintended pregnancies in United States. They consist of a progestin (e.g., levonorgestrel (LNG)) and an estrogen component, typically ethinyl estradiol (EE). In addition to adherence issues, drug-drug interactions (DDIs) and obesity (women with body mass index (BMI) ≥ 30 kg/m2 ) are prime suspects for decreased LNG efficacy. Therefore, we developed an integrated physiologically-based pharmacokinetic modeling and model-based meta-analysis approach to determine LNG's efficacy threshold concentrations and to evaluate the impact of DDIs and obesity on the efficacy of LNG-containing hormonal contraceptives (HCs). Based on this approach, co-administration of strong CYP3A4 inducers and LNG-containing HCs (LNG150: LNG 150 µg + EE 30 µg and LNG100: LNG 100 µg + EE 20 µg) resulted in a predicted clinically relevant decrease of LNG plasma exposure (women with BMI < 25 kg/m2 : 50-65%; obese women: 70-75%). Following administration of LNG150 or LNG100 in the presence of a CYP3A4 inducer, there was an increase in mean Pearl Index of 1.2-1.30 and 1.80-2.10, respectively, in women with BMI < 25 kg/m2 (incidence rate ratios (IRRs): 1.7-2.2), whereas it ranged from 1.6-1.80 and 2.40-2.85 in obese women (IRR: 2.2-3.0), respectively. Our results suggest that the use of backup or alternate methods of contraception is not necessarily required for oral LNG + EE formulations except within circumstances of both obesity and strong CYP3A4 inducer concomitance following administration of LNG100.
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Affiliation(s)
- Karthik Lingineni
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA
| | | | - Brian Cicali
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA
| | - Rodrigo Cristofoletti
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA
| | | | | | - Joshua D Brown
- Department of Pharmaceutical Outcomes & Policy, Center for Drug Evaluation & Safety, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Valvanera Vozmediano
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA
| | - Stephan Schmidt
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA
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Rodrigues AD. Drug Interactions Involving 17α-Ethinylestradiol: Considerations Beyond Cytochrome P450 3A Induction and Inhibition. Clin Pharmacol Ther 2021; 111:1212-1221. [PMID: 34342002 DOI: 10.1002/cpt.2383] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 07/29/2021] [Indexed: 11/08/2022]
Abstract
It is widely acknowledged that drug-drug interactions (DDIs) involving estrogen (17α-ethinylestradiol (EE))-containing oral contraceptives (OCs) are important. Consequently, sponsors of new molecular entities (NMEs) often conduct clinical studies with priority given to OCs as victims of cytochrome P450 (CYP) 3A (CYP3A) induction and inhibition. Such scenarios are reflected in the US Food and Drug Administration-issued guidance documentation related to OC DDI studies. Although CYP3A is important, OCs such as EE are metabolized by sulfotransferase 1E1 and UDP-glucuronosyltransferase (UGT) 1A1, expressed in the gut and liver, and so both can also serve as loci of victim OC DDI. Therefore, for any NME, one should carefully consider its induction and inhibition profile involving CYP3A4/5, UGT1A1, and SULT1E1. As DDI perpetrators, available clinical DDI data indicate that EE-containing OCs can induce (e.g., UGT1A4 and CYP2A6) and inhibit (CYP1A2 ≥ CYP2C19 > CYP3A4/5 > CYP2C8, CYP2B6, CYP2D6, and CYP2C9) various CYP forms. Although available in vitro CYP inhibition data do not explain such a graded inhibitory effect in vivo, it is hypothesized that EE differentially modulates CYP expression via potent agonism of the estrogen receptor expressed in the gut and liver. From the standpoint of the NME as potential OC DDI victim, therefore, it is important to assess its projected (pre-phase I) or known therapeutic index and pharmacokinetic profile (fraction absorbed, absolute oral bioavailability, clearance/extraction class, fraction metabolized by CYP1A2, CYP2C19, CYP2A6, and UGT1A4). Such information can enable the prioritization, design, and interpretation of NME-OC DDI studies.
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Affiliation(s)
- A David Rodrigues
- ADME Sciences, Medicine Design, Worldwide Research & Development, Pfizer Inc, Groton, Connecticut, USA
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7
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White A, Srinivasan M, Wingate LM, Peasah S, Fleming M. Development of a pharmacoeconomic registry: an example using hormonal contraceptives. HEALTH ECONOMICS REVIEW 2021; 11:10. [PMID: 33745016 PMCID: PMC7981865 DOI: 10.1186/s13561-021-00309-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 03/12/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Disease-specific registries, documenting costs and probabilities from pharmacoeconomic studies along with health state utility values from quality-of-life studies could serve as a resource to guide researchers in evaluating the published literature and in the conduct of future economic evaluations for their own research. Registries cataloging economic evaluations currently exist, however they are restricted by the type of economic evaluations they include. There is a need for intervention-specific registries, that document all types of complete and partial economic evaluations and auxiliary information such as quality of life studies. The objective of this study is to describe the development of a pharmacoeconomic registry and provide best practices using an example of hormonal contraceptives. METHODS An expert panel consisting of researchers with expertise in pharmacoeconomics and outcomes research was convened and the clinical focus of the registry was finalized after extensive discussion. A list of key continuous, categorical and descriptive variables was developed to capture all relevant data with each variable defined in a data dictionary. A web-based data collection tool was designed to capture and store the resulting metadata. A keyword based search strategy was developed to retrieve the published sources of literature. Finally, articles were screened for relevancy and data was extracted to populate the registry. Expert opinions were taken from the panel at each stage to arrive at consensus and ensure validity of the registry. RESULTS The registry focused on economic evaluation literature of hormonal contraceptives used for contraception. The registry consisted of 65 articles comprising of 22 cost-effectiveness analyses, 9 cost-utility analyses, 7 cost-benefit analyses, 1 cost-minimization, 14 cost analyses, 10 cost of illness studies and 2 quality of life studies. The best practices followed in the development of the registry were summarized as recommendations. The completed registry, data dictionary and associated data files can be accessed in the supplementary information files. CONCLUSION This registry is a comprehensive database of economic evaluations, including costs, clinical probabilities and health-state utility estimates. The collated data captured from published information in this registry can be used to identify trends in the literature, conduct systematic reviews and meta-analysis and develop novel pharmacoeconomic models.
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Affiliation(s)
- Annesha White
- University of North Texas System College of Pharmacy, University of North Texas Health Science Center, Fort Worth, TX 76107 USA
- Department of Pharmacotherapy, UNT System College of Pharmacy, 3500 Camp Bowie Blvd, IREB 211, Fort Worth, TX 76107 USA
| | - Meenakshi Srinivasan
- University of North Texas System College of Pharmacy, University of North Texas Health Science Center, Fort Worth, TX 76107 USA
| | | | - Samuel Peasah
- Mercer University College of Pharmacy, Atlanta, GA 30341 USA
| | - Marc Fleming
- University of North Texas System College of Pharmacy, University of North Texas Health Science Center, Fort Worth, TX 76107 USA
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8
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Sunaga T, Cicali B, Schmidt S, Brown J. Comparison of contraceptive failures associated with CYP3A4-inducing drug-drug interactions by route of hormonal contraceptive in an adverse event reporting system. Contraception 2020; 103:222-224. [PMID: 33345974 PMCID: PMC7972989 DOI: 10.1016/j.contraception.2020.12.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 12/01/2020] [Accepted: 12/04/2020] [Indexed: 11/24/2022]
Abstract
Objective To estimate associations between contraceptive failures and concomitant CYP3A4-inducing medications by route of administration. Study design Comparison of unintended pregnancy outcomes within U.S. Food and Drug Administration's Adverse Event Reporting System by couse of CYP3A4-inducing drugs and route of administration for levonorgestrel and etonogestrel/desogestrel. Results Among 14,504 levonorgestrel case reports, the reporting odds ratio (ROR) was increased for oral (ROR = 4.2 [3.0–5.7]), implants (ROR = 8.0 [5.8–11.0]), but not intrauterine (ROR = 0.9 [0.6–1.3]) levonorgestrel products. For 9348 etonogestrel/desogestrel case reports, oral and vaginal products were not associated with contraceptive failure. Etonogestrel containing implants (ROR = 4.9 [4.1–5.9]) were associated with increased contraceptive failure. Conclusion Levonorgestrel containing combination oral products and implants containing levonorgestrel or etonogestrel were prone to CYP3A4-inducing drug-drug interactions that may increase contraceptive failures. Implications The progestin components of hormonal contraceptives are susceptible to drug-drug interactions, but this susceptibility is influenced by route of administration. This study provides evidence from an Adverse Event Reporting System that CYP3A4-inducing medications increase the risk of unintended pregnancy for oral and implant contraceptives but not intrauterine or vaginal devices.
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Affiliation(s)
- Tomiko Sunaga
- Center for Drug Evaluation and Safety, Department of Pharmaceutical Outcomes and Policy, University of Florida College of Pharmacy, Gainesville, FL, United States; Showa University, School of Pharmacy, Tokyo, Japan
| | - Brian Cicali
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, University of Florida College of Pharmacy, Orlando, FL, United States
| | - Stephan Schmidt
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, University of Florida College of Pharmacy, Orlando, FL, United States
| | - Joshua Brown
- Center for Drug Evaluation and Safety, Department of Pharmaceutical Outcomes and Policy, University of Florida College of Pharmacy, Gainesville, FL, United States.
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9
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Cicali B, Lingineni K, Cristofoletti R, Wendl T, Hoechel J, Wiesinger H, Chaturvedula A, Vozmediano V, Schmidt S. Quantitative Assessment of Levonorgestrel Binding Partner Interplay and Drug-Drug Interactions Using Physiologically Based Pharmacokinetic Modeling. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2020; 10:48-58. [PMID: 33217171 PMCID: PMC7825189 DOI: 10.1002/psp4.12572] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 11/05/2020] [Accepted: 11/05/2020] [Indexed: 12/15/2022]
Abstract
Levonorgestrel (LNG) is the active moiety in many hormonal contraceptive formulations. It is typically coformulated with ethinyl estradiol (EE) to decrease intermenstrual bleeding. Due to its widespread use and CYP3A4‐mediated metabolism, there is concern regarding drug‐drug interactions (DDIs), particularly a suboptimal LNG exposure when co‐administered with CYP3A4 inducers, potentially leading to unintended pregnancies. The goal of this analysis was to determine the impact of DDIs on the systemic exposure of LNG. To this end, we developed and verified a physiologically‐based pharmacokinetic (PBPK) model for LNG in PK‐Sim (version 8.0) accounting for the impact of EE and body mass index (BMI) on LNG’s binding to sex‐hormone binding globulin. Model parameters were optimized following intravenous and oral administration of 0.09 mg LNG. The combined LNG‐EE PBPK model was verified regarding CYP3A4‐mediated interaction by comparing to published clinical DDI study data with carbamazepine, rifampicin, and efavirenz (CYP3A4 inducers). Once verified, the model was applied to predict systemic LNG exposure in normal BMI and obese women (BMI ≥ 30 kg/m2) with and without co‐administration of itraconazole (competitive CYP3A4 inhibitor) and clarithromycin (mechanism‐based CYP3A4 inhibitor). Total and free LNG exposures, when co‐administered with EE, decreased 2‐fold in the presence of rifampin, whereas they increased 1.5‐fold in the presence of itraconazole. Although changes in total and unbound exposure were decreased in obese women compared with normal BMI women, the relative impact of DDIs on LNG exposure was similar between both groups.
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Affiliation(s)
- Brian Cicali
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, Florida, USA
| | - Karthik Lingineni
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, Florida, USA
| | - Rodrigo Cristofoletti
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, Florida, USA
| | | | | | | | - Ayyappa Chaturvedula
- Department of Pharmacotherapy, System College of Pharmacy, University of Northern Texas Health Science Center, Fort Worth, Texas, USA
| | - Valvanera Vozmediano
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, Florida, USA
| | - Stephan Schmidt
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, Florida, USA
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Srinivasan M, White A, Chaturvedula A, Vozmediano V, Schmidt S, Plouffe L, Wingate LT. Incorporating Pharmacometrics into Pharmacoeconomic Models: Applications from Drug Development. PHARMACOECONOMICS 2020; 38:1031-1042. [PMID: 32734572 PMCID: PMC7578131 DOI: 10.1007/s40273-020-00944-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Pharmacometrics is the science of quantifying the relationship between the pharmacokinetics and pharmacodynamics of drugs in combination with disease models and trial information to aid in drug development and dosing optimization for clinical practice. Considering the variability in the dose-concentration-effect relationship of drugs, an opportunity exists in linking pharmacokinetic and pharmacodynamic model-based estimates with pharmacoeconomic models. This link may provide early estimates of the cost effectiveness of drug therapies, thus informing late-stage drug development, pricing, and reimbursement decisions. Published case studies have demonstrated how integrated pharmacokinetic-pharmacodynamic-pharmacoeconomic models can complement traditional pharmacoeconomic analyses by identifying the impact of specific patient sub-groups, dose, dosing schedules, and adherence on the cost effectiveness of drugs, thus providing a mechanistic basis to predict the economic value of new drugs. Greater collaboration between the pharmacoeconomics and pharmacometrics community can enable methodological improvements in pharmacokinetic-pharmacodynamic-pharmacoeconomic models to support drug development.
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Affiliation(s)
- Meenakshi Srinivasan
- University of North Texas System College of Pharmacy, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Annesha White
- University of North Texas System College of Pharmacy, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA.
| | - Ayyappa Chaturvedula
- University of North Texas System College of Pharmacy, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Valvanera Vozmediano
- Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, FL, USA
| | - Stephan Schmidt
- Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, FL, USA
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Wiesinger H, Klein S, Rottmann A, Nowotny B, Riecke K, Gashaw I, Brudny-Klöppel M, Fricke R, Höchel J, Friedrich C. The Effects of Weak and Strong CYP3A Induction by Rifampicin on the Pharmacokinetics of Five Progestins and Ethinylestradiol Compared to Midazolam. Clin Pharmacol Ther 2020; 108:798-807. [PMID: 32275771 PMCID: PMC7540325 DOI: 10.1002/cpt.1848] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 03/17/2020] [Indexed: 01/28/2023]
Abstract
It is known that co‐administration of CYP3A inducers may decrease the effectiveness of oral contraceptives containing progestins as mono‐preparations or combined with ethinylestradiol. In a randomized clinical drug‐drug interaction study, we investigated the effects of CYP3A induction on the pharmacokinetics of commonly used progestins and ethinylestradiol. Rifampicin was used to induce CYP3A. The progestins chosen as victim drugs were levonorgestrel, norethindrone, desogestrel, and dienogest as mono‐products, and drospirenone combined with ethinylestradiol. Postmenopausal women (n = 12–14 per treatment group) received, in fixed sequence, a single dose of the victim drug plus midazolam without rifampicin, with rifampicin 10 mg/day (weak induction), and with rifampicin 600 mg/day (strong induction). The effects on progestin exposure were compared with the effects on midazolam exposure (as a benchmark). Unbound concentrations were evaluated for drugs binding to sex hormone binding globulin. Weak CYP3A induction, as confirmed by a mean decrease in midazolam exposure by 46%, resulted in minor changes in progestin exposure (mean decreases: 15–37%). Strong CYP3A induction, in contrast, resulted in mean decreases by 57–90% (mean decrease in midazolam exposure: 86%). Namely, the magnitude of the observed induction effects varied from weak to strong. Our data might provide an impetus to revisit the currently applied clinical recommendations for oral contraceptives, especially for levonorgestrel and norethindrone‐containing products, and they might give an indication as to which progestin could be used, if requested, by women taking weak CYP3A inducers—although it is acknowledged that the exact exposure‐response relationship for contraceptive efficacy is currently unclear for most progestins.
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Lippert J, Burghaus R, Edginton A, Frechen S, Karlsson M, Kovar A, Lehr T, Milligan P, Nock V, Ramusovic S, Riggs M, Schaller S, Schlender J, Schmidt S, Sevestre M, Sjögren E, Solodenko J, Staab A, Teutonico D. Open Systems Pharmacology Community-An Open Access, Open Source, Open Science Approach to Modeling and Simulation in Pharmaceutical Sciences. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2019; 8:878-882. [PMID: 31671256 PMCID: PMC6930856 DOI: 10.1002/psp4.12473] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 09/23/2019] [Indexed: 12/30/2022]
Affiliation(s)
- Jörg Lippert
- Clinical Pharmacometrics, Bayer AG, Wuppertal, Germany
| | - Rolf Burghaus
- Clinical Pharmacometrics, Bayer AG, Wuppertal, Germany
| | - Andrea Edginton
- School of Pharmacy, University of Waterloo, Waterloo, Canada
| | | | - Mats Karlsson
- Faculty of Pharmacy, Uppsala University, Uppsala, Sweden
| | - Andreas Kovar
- Pharmacokinetics, Dynamics and Metabolism, Sanofi-Aventis, Frankfurt, Germany
| | - Thorsten Lehr
- Clinical Pharmacy, Saarland University, Saarbrücken, Germany
| | | | - Valerie Nock
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Sergej Ramusovic
- Pharmacokinetics, Dynamics and Metabolism, Sanofi-Aventis, Frankfurt, Germany
| | - Matthew Riggs
- Metrum Research Group, Tariffville, Connecticut, USA
| | | | - Jan Schlender
- Clinical Pharmacometrics, Bayer AG, Wuppertal, Germany
| | - Stephan Schmidt
- College of Pharmacy, University of Florida, Florida, Orlando, USA
| | | | - Erik Sjögren
- Faculty of Pharmacy, Uppsala University, Uppsala, Sweden.,Pharmetheus, Uppsala, Sweden
| | | | - Alexander Staab
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany
| | - Donato Teutonico
- Pharmacokinetics, Dynamics and Metabolism, Sanofi-Aventis R&D, Alfortville, France
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Schmidt S, Kim S, Vozmediano V, Cristofoletti R, Winterstein AG, Brown JD. Pharmacometrics, Physiologically Based Pharmacokinetics, Quantitative Systems Pharmacology-What's Next?-Joining Mechanistic and Epidemiological Approaches. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2019; 8:352-355. [PMID: 31179639 PMCID: PMC6618101 DOI: 10.1002/psp4.12425] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Accepted: 04/30/2019] [Indexed: 02/05/2023]
Abstract
The application of modeling and simulation (M&S) tools to biological, physiological, and clinical data has great potential to enhance drug development and regulatory decision making. The strategic development of multidisciplinary projects aimed at integrating methodologies from different disciplines may bridge between preclinical and clinical drug development as well as between academic curiosity and clinical practice. Herein we review the history and present the state of M&S approaches as well as our vision for future challenges and applications.
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Affiliation(s)
- Stephan Schmidt
- Center for Pharmacometrics and Systems PharmacologyDepartment of PharmaceuticsCollege of PharmacyUniversity of FloridaOrlandoFloridaUSA
| | - Sarah Kim
- Center for Pharmacometrics and Systems PharmacologyDepartment of PharmaceuticsCollege of PharmacyUniversity of FloridaOrlandoFloridaUSA
| | - Valvanera Vozmediano
- Center for Pharmacometrics and Systems PharmacologyDepartment of PharmaceuticsCollege of PharmacyUniversity of FloridaOrlandoFloridaUSA
| | - Rodrigo Cristofoletti
- Center for Pharmacometrics and Systems PharmacologyDepartment of PharmaceuticsCollege of PharmacyUniversity of FloridaOrlandoFloridaUSA
| | - Almut G. Winterstein
- Center for Drug Evaluation and SafetyDepartment of Pharmaceutical Outcomes and PolicyCollege of PharmacyUniversity of FloridaGainesvilleFloridaUSA
| | - Joshua D. Brown
- Center for Drug Evaluation and SafetyDepartment of Pharmaceutical Outcomes and PolicyCollege of PharmacyUniversity of FloridaGainesvilleFloridaUSA
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McFeely SJ, Yu J, Zhao P, Hershenson S, Kern S, Ragueneau‐Majlessi I, Hartman D. Drug-Drug Interactions of Infectious Disease Treatments in Low-Income Countries: A Neglected Topic? Clin Pharmacol Ther 2019; 105:1378-1385. [PMID: 30771252 PMCID: PMC6563420 DOI: 10.1002/cpt.1397] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 02/03/2019] [Indexed: 12/25/2022]
Abstract
Despite recent advances in recognizing and reducing the risk of drug-drug interactions (DDIs) in developed countries, there are still significant challenges in managing DDIs in low-income countries (LICs) worldwide. In the treatment of major infectious diseases in these regions, multiple factors contribute to ineffective management of DDIs that lead to loss of efficacy or increased risk of adverse events to patients. Some of these difficulties, however, can be overcome. This review aims to evaluate the inherent complexities of DDI management in LICs from pharmacological standpoints and illustrate the unique barriers to effective management of DDIs, such as the challenges of co-infection and treatment settings. A better understanding of comprehensive drug-related properties, population-specific attributes, such as physiological changes associated with infectious diseases, and the use of modeling and simulation techniques are discussed, as they can facilitate the implementation of optimal treatments for infectious diseases at the individual patient level.
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Affiliation(s)
| | - Jingjing Yu
- School of PharmacyUniversity of WashingtonSeattleWashingtonUSA
| | - Ping Zhao
- The Bill & Melinda Gates FoundationSeattleWashingtonUSA
| | | | - Steven Kern
- The Bill & Melinda Gates FoundationSeattleWashingtonUSA
| | | | - Dan Hartman
- The Bill & Melinda Gates FoundationSeattleWashingtonUSA
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