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Optimization of in vitro automated glucuronidation assays to improve pediatric-physiologically-based pharmacokinetic predictions

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Presented by Justine Badée, Ph.D.

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Optimization of in vitro automated glucuronidation assays to improve pediatric-physiologically-based pharmacokinetic predictions

  1. 1. Justine Badée, Ph.D. Postdoctoral Associate at the Center for Pharmacometrics & Systems Pharmacology, Department of Pharmaceutics, University of Florida at Lake Nona, Orlando, FL, USA PBPK Symposium - April 4, 2019 - Paris, France Optimization of in vitro automated glucuronidation assays to improve pediatric- physiologically-based pharmacokinetic predictions
  2. 2. Postdoc UGT project: A broad collaboration between pharmaceutical industry and academics Roche Postdoc Fellowship funded project (2017/2019) 1
  3. 3. What is already known ?  UGT1A and 2B isoforms = key determinants of pharmacokinetics, efficacy and safety of many drugs  Physiological and maturation changes from birth may impact PK/PD, efficacy and safety in children  Pediatric safety concerns due to immature UGT activity  Neonates and Infants  Greater risk of serious adverse events due to increased drug concentration o UGT1A1/unconjugated bilirubin, UGT1A4/antiepileptic drugs, UGT2B7/codeine  Challenges of pediatric drug development  Ethical, practical and financial limitations  Appropriate study design / dose selection to interpret PKPD based on sparse data Badée et al., 2018, Clinical Pharmacokinetics, 1-23 UGT drug substrate UDP-glucuronosyl transferase UGT drug substrate glucuronide UDPUDPGA 2
  4. 4.  For pediatric applications (EMA 2018):  Effects of ontogeny should be addressed  Posology recommendations in children that are supported by only limited clinical data and heavily rely on PBPK modelling are considered to be of high regulatory impact applications. Support dose adjustment and predict PK variability in children Clinical trials design in children  Integration of the CYP ontogeny profiles into PBPK models  Accurate prediction of drug exposure for children under 2 years of age but limited application with UGTs  Validation efforts required for PBPK predictions of UGT-metabolized drugs PBPK modelling and simulation strategy https://www.ema.europa.eu/documents/scientific-guideline/guideline-reporting-physiologically-based-pharmacokinetic-pbpk-modelling-simulation_en.pdf 3  Regulatory framework for pediatric drug development  FDAMA, 1997, BPCA, 2002, PREA, 2003, Pediatric study decision tree, 2003, PSP/PIP, 2012 Badée et al., 2018, Clinical Pharmacokinetics, 1-23
  5. 5. Aims and strategy Establish the postnatal ontogeny of major hepatic UGT isoforms • Predict the pharmacokinetics of UGT-metabolized drugsand establish rational dose adjustment in children by integrating UGT ontogeny profile • Better characterization of the liver’s metabolic capacity across age groups Development & verification of PBPK models in adults and pediatrics Optimize the experimental conditions of automated UGT assays • Improve UGT clearance and phenotyping assays in a pharmaceutical industry setting Overview of current knowledge on the UGT ontogeny • Improve our understanding and define knowledge gaps 4 1 2 3 4
  6. 6. Limited knowledge on hepatic UGT ontogeny Badée et al., 2018, Clinical Pharmacokinetics, 1-23 5 Step 1 NB: 7 isoforms (+ UGT2B15 Bhat et al., 2019)
  7. 7. Optimization of automated UGT profiling assay  Challenges of UGT phenotyping assays  Lack of standardized experimental conditions of UGT assays between laboratories  hinders the comparison of UGT activity across studies  Very limited or not available UGT-isoform inhibitors  Small number of positive control compounds as functional markers of UGT activity Badée et al., 2019, Drug Metabolism and Disposition, 47:124-34 6 Step 2 Optimize a UGT profiling assay for optimization of UGT clearance and screening in a pharmaceutical industry setting
  8. 8. Optimization of automated UGT profiling assay ? Suitable experimental conditions to simultaneously characterize the hepatic UGT activity in pooled HLM Badée et al., 2019, Drug Metabolism and Disposition, 47:124-34 7  Tecan Fluent system (F. Hoffmann-La Roche)  Metabolism time course experiments  Substrate cassetting approach: 5 cocktail incubations of selected probe substrates
  9. 9. Bovine serum albumin supplementation ? UDPGA ? Tris-HClbuffer MgCl2: 10mM UDPGA:5 mM NoBSA Incubation buffer ? MgCl2 ? 2 Which experimental conditions to optimize ? Badée et al., 2019, Drug Metabolism and Disposition, 47:124-34 8 1 3 4
  10. 10. Innovations & Impacts  Methodological and technical improvements for future in vitro UGT phenotyping assays  Substrate cocktail combination defined (no metabolic/analytical interactions)  Reduced amount of material (often sparse) and resources to be used  Reduced inter-lab discrepancies in glucuronidation activity  To improve in vitro-in vivo extrapolation of UGT-metabolized drug clearance  More effective performance of multiple-donor activity studies in a pharmaceutical industry setting  Correlation analyses  Assessment of UGT ontogeny (or polymorphism) effects on drug clearance 9 ? Age (y) Fractionofactivity Badée et al., 2019, Drug Metabolism and Disposition, 47:124-34
  11. 11. Characterization of hepatic UGT ontogeny 1. Define the ontogeny profile of major human hepatic UGT isoforms based on microsomal glucuronidation activity using : 2. Establish UGT protein expression - activity correlation using matched HLM samples  Adult (n=44),  Pediatric (n=47)  150-donor pooled HLMs  Alamethicin-treated HLMs (50 µg/mg)  HLM concentration (0.1 or 0.5 mg/mL)  19 UGT probe substrates selected o In vitro probe substrates o Clinically used drug substrates  Single concentration (3, 5, 10 or 100 µM)  Incubation time: (5 or 10 min)  Optimized incubation conditions HLMs (13 days-74 years) Automated UGT assay UGT proteomics (genentech)  Quantitative LC-MS/MS MRM-based method  Optimization of digestion conditions  Protein expression - activity correlations for UGTs and CYPs  Manuscript in preparation Manuscript under review (DMD journal) 10 Step 3
  12. 12. Ontogeny of UGT1A1, 1A4, 2B7, 2B10 and 2B15 established using multiple selective substrates 11 Unpublisheddata
  13. 13. Ontogeny of UGT1A1, 1A4, 2B7, 2B10 and 2B15 established using multiple selective substrates 12 Unpublisheddata
  14. 14. Developmental pattern of hepatic UGT isoforms 13 Unpublisheddata
  15. 15. Innovations & Impacts  New insights on the maturation of 10 major hepatic UGT isoforms  Use of multiple cross-correlated in vitro probe substrates and clinically used drugs  Ontogeny profile defined for UGT isoforms not previously described  Set up a strong basis for future UGT activity-protein expression correlation analyses  Evaluate the UGT ontogeny effect on drug clearance across pediatric age groups  Develop and verify a pediatric-PBPK model to support design of clinical trials and dose recommendation 14 Unpublisheddata
  16. 16. Research aim with UKBB (in progress) 15 Understand enzyme maturation to simplify morphine dosing schemes in neonates and infants while evaluating a developed pediatric-PBPK model with robust validation (popPK) popPKmodel workflow (Tamara,UKBB/Roche) PBPKmodel workflow (Justine, UF/Roche) Step 4 Roche: Neil Parrott,UF: Stephan Schmidt Saskia de Wildt UKBB:Mark Pfitser, John van den Anker
  17. 17. 1: Emoto et al., 2017, 2: Olsen et al., 1975, 3: Dale et al., 2006, 4: Garberg et al., 2005, 5: Avdeef 1996, 6: Lotsch et al., 2002, 7: de Gregori et al., 2012, 8: https://pdfs.semanticscholar.org/4ba3/427ca5c779dc1bba3fa27aaf591f13b15308.pdf, 9: Sverrisdottir et al., 2015, 10: Prasad et al., 2016 Parameter Value Small molecule 285.34 g/mol 1 LogP 0.77 1 Ampholyte - pKa 9.63 (A), 7.93 (B) 1 fu(binding to albumin) 0.65 2 B:P ratio 1.08 1 Papp(Caco-2 monolayers) 1.07 10-6 cm/s 3 Parameter Value F 20-30 % (oral solution) 4 18.7 % (buccal tablet) 4 IV administration in Healthy Adults Vss 2.25 L/kg 1 CLp 20-30 mL/min/kg 4 t1/2 1.5-2 h 5, 6 CLr 8 L/h 1 Dose excreted as unchanged in urine 10 % 5 Morphine – input parameters Hepatic metabolism 7-9  Glucuronidation 60-70% o Morphine-3-Glucuronide via UGT2B7 (45-55%) o Morphine-6-Glucuronide via UGT2B7 (10-15%)  Sulfation 5-10%,  N-demethylation <5% (CYP3A4>2C8) 16 Hepatic influx via OCT1 10 • Lower protein expression in children <1 year, 50% of adult levels reached at 6 months
  18. 18. Healthy adult subject studies Process Route of administration Dosage (as free base) Study duration Population Age range (years) Mean weight (range) (kg) Ref Development IV bolus SD 0.14 mg/kg over 30 sec (0.105 mg/kg) 4.5 h 4 NA 18-39 61.5 (40.9-86.4) 1 Validation IV infusion 10 mg over 10 min (7.5 mg) 12 h NA NA NA 2 IV infusion 10 mg over 5 min (7.5 mg) 12 h 12 NA NA NA 3 IV infusion 7.5 mg over 2h (5.7 mg) 14 h 18 M 20-43 71 (56-84) 4 IV bolus SD 0.1 mg/kg over 30 sec assumed (0.075 mg/kg) 8 h 5F / 1M 17-70 57 (38-76) 5 IV bolus SD 7.5 mg over 30 sec assumed (5.64 mg) 9.5 h 4F / 4M 23-30 70.5 (54-98) 6 IV bolus SD 10 mg over 288 sec (7.5 mg/kg) 8 h 6 NA 20-40 71.4 (49-102) 7 IV: intravenous, SD: single dose, M: male, F: female, NA: not available 1: Murphy et al., 1981, 54;187-92, 2: Baillie et al., 1989, 18:258-62, 3: Murthy et al., 2002, 42:569-76, 4: Drewe et al., 2000, 50:237-46, 5: Mazoit et al., 1990, 48:613-8, 6: Lotsch et al., 2002, 72;151-62, 7: Stuart-Harris et al., 2002,49:207-14 Ethic origin: NA Conversion factor: morphine sulfate = 0.75, morphine hydrochloride = 0.76 17
  19. 19. Optimized UGT methodology to improve pediatric-PBPK predictions  Strategy could be applied for other metabolic pathways (eg FMOs, CYP3A…) or special populations 21 Unpublisheddata
  20. 20. Communications Publications • Badée et al., 2018, Clinical Pharmacokinetics, 1-23 • Badée et al., 2019, Drug Metabolism and Disposition, 47:124-34 and featured on DMD’s website • Badée et al., UGT ontogeny manuscript under review (DMD journal) Past conferences: Gordon Research Conferences “Drug Metabolism” – Holderness, NH, July 2017, 2018 American College of Clinical Pharmacology – Bethesda, MA, Sept 2018 ACCP Student Award Winner and Wayne A. Colburn Award Prizes 22
  21. 21. Roche Postdoc Fellowship Program University of Florida, FL, USA Stephan Schmidt CPSP colleagues Genentech, CA, USA Ryan H. Takahashi William F. Forrest University of British Columbia, Canada Abby C. Collier Radmoud University, Netherlands Saskia N. de Wildt Acknowledgments F. Hoffmann-La Roche, Basel, Switzerland Neil Parrott Stephen Fowler Nahong Qiu Florian Klammers Massimiliano Donzelli Sandrine Simon Team management
  22. 22. Thank you for your attention ! Q & A

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