دورية أكاديمية

Supporting Prospective Pregnancy Trials via Modeling and Simulation: Lessons From the Past and Recommendations for the Future.

التفاصيل البيبلوغرافية
العنوان: Supporting Prospective Pregnancy Trials via Modeling and Simulation: Lessons From the Past and Recommendations for the Future.
المؤلفون: Cheung SYA; Certara, Princeton, NJ, USA., Barrett JS; Aridhia Bioinformatics, Glasgow, Scotland, UK.
المصدر: Journal of clinical pharmacology [J Clin Pharmacol] 2023 Jun; Vol. 63 Suppl 1, pp. S51-S61.
نوع المنشور: Journal Article; Review
اللغة: English
بيانات الدورية: Publisher: Wiley Country of Publication: England NLM ID: 0366372 Publication Model: Print Cited Medium: Internet ISSN: 1552-4604 (Electronic) Linking ISSN: 00912700 NLM ISO Abbreviation: J Clin Pharmacol Subsets: MEDLINE
أسماء مطبوعة: Publication: 2013- : Oxford : Wiley
Original Publication: Stamford, Conn., Hall Associates.
مواضيع طبية MeSH: Breast Feeding* , Lactation*, Female ; Humans ; Infant, Newborn ; Pregnancy ; Computer Simulation ; Milk, Human ; Prospective Studies
مستخلص: Despite the increasing awareness and guidance to support drug research and development in the pregnant population, there is still a high unmet medical need and off-label use in the pregnant population for mainstream, acute, chronic, rare disease, and vaccination/prophylactic use. There are many obstacles to enrolling the pregnant population in a study, ranging from ethical considerations, the complexity of the pregnancy stages, postpartum, fetus-mother interaction, and drug transfer to breast milk during lactation and impacts on neonates. This review will outline the common challenges of incorporating physiological differences in the pregnant population and historical but noninformative practice in a past clinical trial in pregnant women that led to labeling difficulties. The recommendations of different modeling approaches, such as a population pharmacokinetic model, physiologically based pharmacokinetic modeling, model-based meta-analysis, and quantitative system pharmacology modeling, are presented with some examples. Finally, we outline the gaps in the medical need for the pregnant population by classifying various types of diseases and some considerations that exist to support the use of medicines in this area. Ideas on the potential framework to support clinical trials and collaboration examples are also presented that could also accelerate understanding of drug research and medicine/prophylactics/vaccines in the pregnant population.
(© 2023, The American College of Clinical Pharmacology.)
References: Sedgh G, Singh S, Hussain R. Intended and unintended pregnancies worldwide in 2012 and recent trends. Stud Fam Plann. 2014;45(3):301-314.
Ammon Avalos L, Galindo C, Li DK. A systematic review to calculate background miscarriage rates using life table analysis. Birth Defects Res A Clin Mol Teratol. 2012;94(6):417-423.
Birmingha BHP. The healthy mum, healthy baby, healthy future: The case for UK leadership in the development of safe, effective and accessible medicines for use in pregnancy report 2022. https://www.birminghamhealthpartners.co.uk/wp-content/uploads/2022/05/Final-Healthy-Mum-Healthy-Baby-Healthy-Future-Report-AW_Accessible-PDF-REDUCED-FILE-SIZE.pdf.
Franceschini R, Wicks SL. ClinicalTrials.Gov: pitfalls for pregnant women looking to enroll in studies. Contemp Clin Trials Commun. 2022;26:100890.
Kaye DK. The moral imperative to approve pregnant women's participation in randomized clinical trials for pregnancy and newborn complications. Philos Ethics Humanit Med. 2019;14(1):11.
FDA. Pharmacokinetic Evaluation in Pregnancy- VIRTUAL PUBLIC WORKSHOP, 2022. https://www.fda.gov/media/158925/download.
Marshall S, Madabushi R, Manolis E, et al. Model-informed drug discovery and development: current industry good practice and regulatory expectations and future perspectives. CPT Pharmacometrics Syst Pharmacol. 2019;8(2):87-96.
Marshall SF, Burghaus R, Cosson V, et al. Good practices in model-informed drug discovery and development: practice, application, and documentation. CPT Pharmacometrics Syst Pharmacol. 2016;5(3):93-122.
Manolis E, Brogren J, Cole S, et al. Commentary on the MID3 good practices paper. CPT Pharmacometrics Syst Pharmacol. 2017;6(7):416-417.
Mulugeta Y, Barrett JS, Nelson R, et al. Exposure matching for extrapolation of efficacy in pediatric drug development. J Clin Pharmacol. 2016;56(11):1326-1334.
Barrett JS, Bishai R, Bucci-Rechtweg C, et al. Challenges and opportunities in the development of medical therapies for pediatric populations and the role of extrapolation. Clin Pharmacol Ther. 2018;103(3):419-433.
Barrett JS, Bucci-Rechtweg C, Amy Cheung SY, et al. Pediatric extrapolation in type 2 diabetes: future implications of a workshop. Clin Pharmacol Ther. 2020;108(1): 29-39.
Kons KM, Wood ML, Peck LC, et al. Exclusion of reproductive-aged women in COVID-19 vaccination and clinical trials. Women's Health Issues. 2022;32(6):557-563.
Taylor MM, Kobeissi L, Kim C, et al. Inclusion of pregnant women in COVID-19 treatment trials: a review and global call to action. Lancet Glob Health. 2021;9(3):e366-e371.
Zavala E, Krubiner CB, Jaffe EF, et al. Global disparities in public health guidance for the use of COVID-19 vaccines in pregnancy. BMJ Global Health. 2022;7(2):e007730.
McDonald CR, Weckman AM, Wright JK, Conroy AL, Kain KC. Pregnant women in low- and middle-income countries require a special focus during the COVID-19 pandemic. Front Glob Womens Health. 2020;1:564560.
EMA. Reflection paper on extrapolation of efficacy and safety in paediatric medicine development 2017. https://www.ema.europa.eu/en/extrapolation-efficacy-safety-paediatric-medicine-development-scientific-guideline.
EMA. Public workshop on extrapolation of efficacy and safety in medicine development across age groups. Outcome of a multi-stakeholder meeting with experts and regulators 2016. https://www.ema.europa.eu/en/documents/other/ema-public-workshop-extrapolation-efficacy-safety-medicine-development-outcome-multi-stakeholder_en.pdf.
Maas BM, Lommerse J, Plock N, et al. Forward and reverse translational approaches to predict efficacy of neutralizing respiratory syncytial virus (RSV) antibody prophylaxis. EBioMedicine. 2021;73:103651.
Roes KCB, van der Zande ISE, van Smeden M, van der Graaf R. Towards an appropriate framework to facilitate responsible inclusion of pregnant women in drug development programs. Trials. 2018;19(1):123-123.
Okae H, Toh H, Sato T, et al. Derivation of human trophoblast stem cells. Cell Stem Cell. 2018;22(1):50-63.e56.
Chen Y, Siriwardena D, Penfold C, Pavlinek A, Boroviak TE. An integrated atlas of human placental development delineates essential regulators of trophoblast stem cells. Development. 2022;149(13):1-22. https://journals.biologists.com/dev/article/149/13/dev200171/275917/An-integrated-atlas-of-human-placental-development.
Hakomäki H, Kokki H, Lehtonen M, et al. Pharmacokinetics of buprenorphine in pregnant sheep after intravenous injection. Pharmacol Res Perspect. 2021;9(2):e00726.
Rijken MJ, McGready R, Phyo AP, et al. Pharmacokinetics of dihydroartemisinin and piperaquine in pregnant and nonpregnant women with uncomplicated falciparum malaria. Antimicrob Agents Chemother. 2011;55(12):5500-5506.
Wangboonskul J, White NJ, Nosten F, ter Kuile F, Moody RR, Taylor RB. Single dose pharmacokinetics of proguanil and its metabolites in pregnancy. Eur J Clin Pharmacol. 1993;44(3):247-251.
Liao MZ, Flood Nichols SK, Ahmed M, et al. Effects of pregnancy on the pharmacokinetics of metformin. Drug Metab Dispos. 2020;48(4):264-271.
Ryu RJ, Eyal S, Kaplan HG, et al. Pharmacokinetics of doxorubicin in pregnant women. Cancer Chemother Pharmacol. 2014;73(4):789-797.
Stek AM, Best BM, Luo W, et al. Effect of pregnancy on emtricitabine pharmacokinetics. HIV Med. 2012;13(4):226-235.
Colbers A, Best B, Schalkwijk S, et al. Maraviroc pharmacokinetics in HIV-1-infected pregnant women. Clin Infect Dis. 2015;61(10):1582-1589.
Colbers A, Moltó J, Ivanovic J, et al. Pharmacokinetics of total and unbound darunavir in HIV-1-infected pregnant women*. J Antimicrob Chemother. 2014;70(2):534-542.
Wade NA, Unadkat JD, Huang S, et al. Pharmacokinetics and safety of stavudine in HIV-infected pregnant women and their infants: pediatric AIDS clinical trials group protocol 332. J Infect Dis. 2004;190(12):2167-2174.
Osiyemi O, Yasin S, Zorrilla C, et al. Pharmacokinetics, antiviral activity, and safety of rilpivirine in pregnant women with HIV-1 infection: results of a phase 3b, multicenter, open-label study. Infect Dis Ther. 2018;7(1):147-159.
Xia B, Heimbach T, Gollen R, Nanavati C, He H. A simplified PBPK modeling approach for prediction of pharmacokinetics of four primarily renally excreted and CYP3A metabolized compounds during pregnancy. AAPS J. 2013;15(4):1012-1024.
Ke AB, Nallani SC, Zhao P, Rostami-Hodjegan A, Unadkat JD. Expansion of a PBPK model to predict disposition in pregnant women of drugs cleared via multiple CYP enzymes, including CYP2B6, CYP2C9 and CYP2C19. Br J Clin Pharmacol. 2014;77(3):554-570.
Zhou W, Johnson TN, Bui KH, et al. Predictive performance of physiologically based pharmacokinetic (PBPK) modeling of drugs extensively metabolized by major cytochrome P450s in children. Clin Pharmacol Ther. 2018;104(1):188-200.
Zhou W, Johnson TN, Xu H, et al. Predictive performance of physiologically based pharmacokinetic and population pharmacokinetic modeling of renally cleared drugs in children. CPT Pharmacometrics Syst Pharmacol. 2016;5(9):475-483.
Coppola P, Kerwash E, Cole S. Physiologically based pharmacokinetics model in pregnancy: a regulatory perspective on model evaluation. Front Pediatr. 2021;9:687978.
Green DJ, Park K, Bhatt-Mehta V, Snyder D, Burckart GJ. Regulatory considerations for the mother, fetus and neonate in fetal pharmacology modeling. Front Pediatr. 2021;9:698611.
Foulkes MA, Grady C, Spong CY, Bates A, Clayton JA. Clinical research enrolling pregnant women: a workshop summary. J Womens Health (Larchmt). 2011;20(10):1429-1432.
Dallmann A, van den Anker J, Pfister M, Koch G. Characterization of maternal and neonatal pharmacokinetic behavior of ceftazidime. J Clin Pharmacol. 2019;59(1):74-82.
Goyal RK, Moffett BS, Gobburu JVS, Al Mohajer M. Population pharmacokinetics of vancomycin in pregnant women. Front Pharmacol. 2022;13:873439.
Tita AT, Szychowski JM, Boggess K, et al. Treatment for mild chronic hypertension during pregnancy. N Engl J Med. 2022;386(19):1781-1792.
Kandala B, Plock N, Chawla A, et al. Accelerating model-informed decisions for COVID-19 vaccine candidates using a model-based meta-analysis approach. EBioMedicine. 2022;84:104264.
Barrett JS, Azer K. Opportunities for systems biology and quantitative systems pharmacology (QSP) to address knowledge gaps for drug development in pregnancy. J Clin Pharmacol. 2022, manuscript submitted for publication.
Hoegh S, Thellesen L, Christensen KB, Bergholt T, Hedegaard M, Sorensen JL. Incidences of obstetric outcomes and sample size calculations: a Danish National Registry Study based on all deliveries from 2008 to 2015. Acta Obstet Gynecol Scand. 2020;99(1):34-41.
Patson N, Mukaka M, Otwombe KN, et al. Systematic review of statistical methods for safety data in malaria chemoprevention in pregnancy trials. Malar J. 2020;19(1):119.
Cheung SYA, Yates JWT, Aarons L. Structural identifiability of parallel pharmacokinetic experiments as constrained systems. IFAC Proceedings Volumes. 2006;39(18):99-104.
Cheung SY, Majid O, Yates JW, Aarons L. Structural identifiability analysis and reparameterisation (parameter reduction) of a cardiovascular feedback model. Eur J Pharm Sci. 2012;46(4):259-271.
Lommerse J, Clarke D, Kerbusch T, et al. Maternal-neonatal raltegravir population pharmacokinetics modeling: implications for initial neonatal dosing. CPT Pharmacometrics Syst Pharmacol. 2019;8(9):643-653.
Sharma S, Caritis S, Hankins G, et al. Population pharmacokinetics of 17α-hydroxyprogesterone caproate in singleton gestation. Br J Clin Pharmacol. 2016;82(4):1084-1093.
Hirt D, Urien S, Rey E, et al. Population pharmacokinetics of emtricitabine in human immunodeficiency virus type 1-infected pregnant women and their neonates. Antimicrob Agents Chemother. 2009;53(3):1067-1073.
Benaboud S, Ekouévi DK, Urien S, et al. Population pharmacokinetics of nevirapine in HIV-1-infected pregnant women and their neonates. Antimicrob Agents Chemother. 2011;55(1):331-337.
Elkayal O, Allegaert K, Spriet I, et al. Population pharmacokinetics of cefazolin in maternal and umbilical cord plasma, and simulated exposure in term neonates. J Antimicrob Chemother. 2021;76(12):3229-3236.
Bustinduy AL, Kolamunnage-Dona R, Mirochnick MH, et al. Population pharmacokinetics of praziquantel in pregnant and lactating Filipino women infected with Schistosoma japonicum. Antimicrob Agents Chemother. 2020;64(9):1-13. https://journals.asm.org/doi/pdf/10.1128/AAC.00566-20.
Tanoshima R, Bournissen FG, Tanigawara Y, et al. Population PK modelling and simulation based on fluoxetine and norfluoxetine concentrations in milk: a milk concentration-based prediction model. Br J Clin Pharmacol. 2014;78(4):918-928.
Maas BMPN, Vora KA, Gheyas F, et al. Clinical trial simulation predicts higher efficacy against RSV for clesrovimab (MK-1654) thanfor maternal vaccination. Presented at the 12th International RSV Symposium (RSV2022); September 29-October. Belfast, Northern Ireland; 2022.
Abduljalil K, Pansari A, Jamei M. Prediction of maternal pharmacokinetics using physiologically based pharmacokinetic models: assessing the impact of the longitudinal changes in the activity of CYP1A2, CYP2D6 and CYP3A4 enzymes during pregnancy. J Pharmacokinet Pharmacodyn. 2020;47(4):361-383.
Jogiraju VK, Avvari S, Gollen R, Taft DR. Application of physiologically based pharmacokinetic modeling to predict drug disposition in pregnant populations. Biopharm Drug Dispos. 2017;38(7):426-438.
EMA. Guideline on the qualification and reporting of physiologically based pharmacokinetic (PBPK) modelling and simulation; 2016. https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-reporting-physiologically-based-pharmacokinetic-pbpk-modelling-simulation_en.pdf.
Yates JW. Structural identifiability of physiologically based pharmacokinetic models. J Pharmacokinet Pharmacodyn. 2006;33(4):421-439.
Olafuyi O, Badhan RKS. Dose optimization of chloroquine by pharmacokinetic modeling during pregnancy for the treatment of zika virus infection. J Pharm Sci. 2019;108(1):661-673.
Schalkwijk S, Buaben AO, Freriksen JJM, et al. Prediction of fetal darunavir exposure by integrating human ex-vivo placental transfer and physiologically based pharmacokinetic modeling. Clin Pharmacokinet. 2018;57(6):705-716.
Olafuyi O, Coleman M, Badhan RKS. The application of physiologically based pharmacokinetic modelling to assess the impact of antiretroviral-mediated drug-drug interactions on piperaquine antimalarial therapy during pregnancy. Biopharm Drug Dispos. 2017;38(8):464-478.
Badhan RKS, Macfarlane H. Quetiapine dose optimisation during gestation: a pharmacokinetic modelling study. J Pharm Pharmacol. 2020;72(5):670-681.
Chetty M, Danckwerts MP, Julsing A. Prediction of the exposure to a 400-mg daily dose of efavirenz in pregnancy: is this dose adequate in extensive metabolisers of CYP2B6? Eur J Clin Pharmacol. 2020;76(8):1143-1150.
Abduljalil K, Pansari A, Ning J, Jamei M. Prediction of maternal and fetal acyclovir, emtricitabine, lamivudine, and metformin concentrations during pregnancy using a physiologically based pharmacokinetic modeling approach. Clin Pharmacokinet. 2022;61(5):725-748.
Abduljalil K, Gardner I, Jamei M. Application of a physiologically based pharmacokinetic approach to predict theophylline pharmacokinetics using virtual non-pregnant, pregnant, fetal, breast-feeding, and neonatal populations. Front Pediatr. 2022;10:840710.
Polasek TM, Tucker GT, Sorich MJ, et al. Prediction of olanzapine exposure in individual patients using physiologically based pharmacokinetic modelling and simulation. Br J Clin Pharmacol. 2018;84(3):462-476.
Zheng L, Yang H, Dallmann A, Jiang X, Wang L, Hu W. Physiologically based pharmacokinetic modeling in pregnant women suggests minor decrease in maternal exposure to olanzapine. Front Pharmacol. 2021;12:793346.
Abduljalil K, Pansari A, Ning J, Jamei M. Prediction of drug concentrations in milk during breastfeeding, integrating predictive algorithms within a physiologically-based pharmacokinetic model. CPT Pharmacometrics Syst Pharmacol. 2021;10(8):878-889.
Olagunju A, Rajoli RKR, Atoyebi SA, et al. Physiologically-based pharmacokinetic modelling of infant exposure to efavirenz through breastfeeding [version 1; peer review: 2 approved with reservations]. AAS Open Res. 2018;1:16. https://doi.org/10.12688/aasopenres.12860.1.
Collier A-RY, McMahan K, Yu J, et al. Immunogenicity of COVID-19 mRNA vaccines in pregnant and lactating women. JAMA. 2021;325(23):2370-2380.
Hepner A, Negrini D, Hase EA, et al. Cancer During Pregnancy: The Oncologist Overview. World J Oncol. 2019;10(1):28-34.
فهرسة مساهمة: Keywords: clinical trial; modeling and simulation; pharmacokinetic; pregnancy
تواريخ الأحداث: Date Created: 20230615 Date Completed: 20230619 Latest Revision: 20230619
رمز التحديث: 20231215
DOI: 10.1002/jcph.2284
PMID: 37317497
قاعدة البيانات: MEDLINE
الوصف
تدمد:1552-4604
DOI:10.1002/jcph.2284