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Achieving big with small: quantitative clinical pharmacology tools for drug development in pediatric rare diseases

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Abstract

Pediatric populations represent a major fraction of rare diseases and compound the intrinsic challenges of pediatric drug development and drug development for rare diseases. The intertwined complexities of pediatric and rare disease populations impose unique challenges to clinical pharmacologists and require integration of novel clinical pharmacology and quantitative tools to overcome multiple hurdles during the discovery and development of new therapies. Drug development strategies for pediatric rare diseases continue to evolve to meet the inherent challenges and produce new medicines. Advances in quantitative clinical pharmacology research have been a key component in advancing pediatric rare disease research to accelerate drug development and inform regulatory decisions. This article will discuss the evolution of the regulatory landscape in pediatric rare diseases, the challenges encountered during the design of rare disease drug development programs and will highlight the use of innovative tools and potential solutions for future development programs.

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References

  1. Braun MM, Farag-El-Massah S, Xu K, Coté TR (2010) Emergence of orphan drugs in the United States: a quantitative assessment of the first 25 years. Nat Rev Drug Discov 9(7):519–522

    Article  CAS  PubMed  Google Scholar 

  2. Epps C, Bax R, Croker A, Green D, Gropman A, Klein AV, Landry H, Pariser A, Rosenman M, Sakiyama M (2022) Global regulatory and public health initiatives to advance pediatric drug development for rare diseases. Ther Innov Regul Sci 56:1–12

    Article  Google Scholar 

  3. Smits RM, Vissers E, Te Pas R, Roebbers N, Feitz WF, van Rooij IA, de Blaauw I, Verhaak CM (2022) Common needs in uncommon conditions: a qualitative study to explore the need for care in pediatric patients with rare diseases. Orphanet J Rare Dis 17(1):1–9

    Article  Google Scholar 

  4. Lalonde E, Rentas S, Lin F, Dulik MC, Skraban CM, Spinner NB (2020) Genomic diagnosis for pediatric disorders: revolution and evolution. Front Pediatr 8:373

    Article  PubMed  PubMed Central  Google Scholar 

  5. Hartley T, Lemire G, Kernohan KD, Howley HE, Adams DR, Boycott KM (2020) New diagnostic approaches for undiagnosed rare genetic diseases. Annu Rev Genom Hum Genet 21(1):351–372

    Article  CAS  Google Scholar 

  6. Sinclair A, Islam S, Jones S Gene therapy: an overview of approved and pipeline technologies, 2016, 171.

  7. Mukherjee K (2019) Care for rare: spotlight on rare diseases. Trends Pharmacol Sci 40(4):227–228

    Article  CAS  PubMed  Google Scholar 

  8. Bell SA, Tudur Smith C (2014) A comparison of interventional clinical trials in rare versus non-rare diseases: an analysis of ClinicalTrials.gov. Orphanet J Rare Dis 9(1):1–11

    Article  Google Scholar 

  9. Ball K, Bouzom F, Scherrmann JM, Walther B, Decleves X (2014) Comparing translational population-PBPK modelling of brain microdialysis with bottom-up prediction of brain-to-plasma distribution in rat and human. Biopharm Drug Dispos 35(8):485–499. https://doi.org/10.1002/bdd.1908

    Article  CAS  PubMed  Google Scholar 

  10. Shiomi M, Matsuki S, Ikeda A, Ishikawa T, Nishino N, Kimura M, Irie S (2014) Effects of a protein-rich drink or a standard meal on the pharmacokinetics of elvitegravir, cobicistat, emtricitabine and tenofovir in healthy Japanese male subjects: a randomized, three-way crossover study. J Clin Pharmacol 54(6):640–648. https://doi.org/10.1002/jcph.283

    Article  CAS  PubMed  Google Scholar 

  11. Manzardo C, Gatell JM (2014) Stribild(R) (elvitegravir/cobicistat/emtricitabine/tenofovir disoproxil fumarate): a new paradigm for HIV-1 treatment. AIDS Rev 16(1):35–42

    PubMed  Google Scholar 

  12. Custodio JM, Wang H, Hao J, Lepist EI, Ray AS, Andrews J, Ling KH, Cheng A, Kearney BP, Ramanathan S (2014) Pharmacokinetics of cobicistat boosted-elvitegravir administered in combination with rosuvastatin. J Clin Pharmacol 54(6):649–656. https://doi.org/10.1002/jcph.256

    Article  CAS  PubMed  Google Scholar 

  13. Chou DB, Frismantas V, Milton Y, David R, Pop-Damkov P, Ferguson D, MacDonald A, Vargel Bölükbaşı Ö, Joyce CE, Moreira Teixeira LS (2020) On-chip recapitulation of clinical bone marrow toxicities and patient-specific pathophysiology. Nat Biomed Eng 4(4):394–406

    Article  PubMed  PubMed Central  Google Scholar 

  14. Bavdekar SB (2013) Pediatric clinical trials. Perspect Clin Res 4(1):89–99. https://doi.org/10.4103/2229-3485.106403

    Article  PubMed  PubMed Central  Google Scholar 

  15. Burckart GJ, Kim C (2020) The revolution in pediatric drug development and drug use: therapeutic orphans no more. J Pediatr Pharmacol Ther 25(7):565–573. https://doi.org/10.5863/1551-6776-25.7.565

    Article  PubMed  PubMed Central  Google Scholar 

  16. Bourgeois FT, Hwang TJ (2018) Improving the study of new medicines for children with rare diseases. JAMA Pediatr 172(1):7–9. https://doi.org/10.1001/jamapediatrics.2017.4012

    Article  PubMed  Google Scholar 

  17. Office of Inspector General Department of Health and Human Services (2001) The orphan drug act: implementation and impact.

  18. Best Pharmaceuticals for Children Act (2002) S.1789. 107th Congress

  19. Pediatric Research Equity Act (2003) S.650. 108th Congress

  20. U.S. Food and Drug Administration. (2005) How to comply with the pediatric research equity act. https://www.fda.gov/media/72274/download

  21. Khosla N, Valdez R (2018) A compilation of national plans, policies and government actions for rare diseases in 23 countries. Intractable Rare Dis Res 7(4):213–222. https://doi.org/10.5582/irdr.2018.01085

    Article  PubMed  PubMed Central  Google Scholar 

  22. U.S. Food and Drug Administration (2013) Orphan drug act—relevant excerpts. https://www.fda.gov/industry/designating-orphan-product-drugs-and-biological-products/orphan-drug-act-relevant-excerpts. Accessed 01/19/2023

  23. U.S. Food and Drug Administration Designating an orphan product: drugs and biological products. https://www.fda.gov/industry/medical-products-rare-diseases-and-conditions/designating-orphan-product-drugs-and-biological-products. Accessed 01/19/2023

  24. Creating Hope Reauthorization Act (2020) H.R.4439. 116th Congress

  25. U.S. Food and Drug Administration (2019) Rare pediatric disease priority review vouchers. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/rare-pediatric-disease-priority-review-vouchers

  26. RACE for Children Act (2017) H.R.1231. 115th congress

  27. Therapeutic Goods Administration (2021) Orphan drug designation eligibility criteria. https://www.tga.gov.au/resources/resource/guidance/orphan-drug-designation-eligibility-criteria. Accessed 01/19/2023

  28. European medicines agency orphan designation: overview. https://www.ema.europa.eu/en/human-regulatory/overview/orphan-designation-overview. Accessed 01/19/2023

  29. Ethical Considerations for Clinical Investigations of Medical Products Involving Children: Draft Guidance for Industry, Sponsors, and IRBs (2022). https://www.fda.gov/regulatory-information/search-fda-guidance-documents/ethical-considerations-clinical-investigations-medical-products-involving-children.

  30. General Clinical Pharmacology Considerations for Pediatric Studies of Drugs, Including Biological Products (2022). https://www.fda.gov/regulatory-information/search-fda-guidance-documents/general-clinical-pharmacology-considerations-pediatric-studies-drugs-including-biological-products.

  31. Bhatnagar M, Sheehan S, Sharma I, Baer G, Green D, McCune S, Joffe S, Snyder D (2021) Prospect of direct benefit in pediatric trials: practical challenges and potential solutions. Pediatrics. https://doi.org/10.1542/peds.2020-049602

    Article  PubMed  Google Scholar 

  32. ICH Guideline E11A on Pediatric Extrapolation (2022). https://www.ema.europa.eu/en/documents/scientific-guideline/draft-ich-guideline-e11a-pediatric-extrapolation-step-2b_en.pdf. Accessed 11/11/2022

  33. Pottackal G, Travis J, Neuner R, Rothwell R, Levin G, Nie L, Niu J, Marathe A, Nikolov N (2019) Application of Bayesian statistics to support approval of intravenous Belimumab in children with systemic lupus erythematosus in the United States. In: Arthritis & rheumatology. Wiley: NJ

  34. Ahmed MA, Okour M, Brundage R, Kartha RV (2019) Orphan drug development: the increasing role of clinical pharmacology. J Pharmacokinet Pharmacodyn 46(5):395–409

    Article  CAS  PubMed  Google Scholar 

  35. Balevic SJ, Niu J, Chen J, Green D, McMahon A, Hornik CP, Schanberg LE, Glaser R, Gonzalez D, Burckart GJ (2022) Extrapolation of adult efficacy data to pediatric systemic lupus erythematosus: evaluating similarities in exposure-response. J Clin Pharmacol 63:105–118

    Article  PubMed  Google Scholar 

  36. Azer K, Barrett JS (2022) Quantitative system pharmacology as a legitimate approach to examine extrapolation strategies used to support pediatric drug development. CPT: Pharmacometrics Syst Pharmacol 11:797–804

    CAS  PubMed  Google Scholar 

  37. Kaddi CD, Niesner B, Baek R, Jasper P, Pappas J, Tolsma J, Li J, van Rijn Z, Tao M, Ortemann-Renon C (2018) Quantitative systems pharmacology modeling of acid sphingomyelinase deficiency and the enzyme replacement therapy olipudase alfa is an innovative tool for linking pathophysiology and pharmacology. CPT: Pharmacometrics Syst. Pharmacol. 7(7):442–452

    CAS  PubMed  Google Scholar 

  38. Halpern-Cohen V, Blumberg EA (2022) New perspectives on antimicrobial agents: Maribavir. Antimicrob Agents Chemother 66(9):e02405-02421

    Article  PubMed  PubMed Central  Google Scholar 

  39. Bi Y, Liu J, Li L, Yu J, Bhattaram A, Bewernitz M, Rj Li, Liu C, Earp J, Ma L (2019) Role of model-informed drug development in pediatric drug development, regulatory evaluation, and labeling. J Clin Pharmacol 59:S104–S111

    Article  CAS  PubMed  Google Scholar 

  40. Cheung KWK, van Groen BD, Burckart GJ, Zhang L, de Wildt SN, Huang SM (2019) Incorporating ontogeny in physiologically based pharmacokinetic modeling to improve pediatric drug development: what we know about developmental changes in membrane transporters. J Clin Pharmacol 59:S56–S69

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Portney LG, Watkins MP (2009) Foundations of clinical research: applications to practice, vol 892. Pearson/Prentice, Upper Saddle River

    Google Scholar 

  42. Cornu C, Kassai B, Fisch R, Chiron C, Alberti C, Guerrini R, Rosati A, Pons G, Tiddens H, Chabaud S (2013) Experimental designs for small randomised clinical trials: an algorithm for choice. Orphanet J Rare Dis 8(1):1–12

    Article  Google Scholar 

  43. Day S, Jonker AH, Lau LPL, Hilgers R-D, Irony I, Larsson K, Roes KC, Stallard N (2018) Recommendations for the design of small population clinical trials. Orphanet J Rare Dis 13(1):1–9

    Article  Google Scholar 

  44. O’Connell K, Pariser AR (2014) Clinical trial safety population size: analysis of drug approvals for rare and common indications by FDA center for drug evaluation and research. Expert Opin Orphan Drugs 2(9):869–875

    Article  CAS  Google Scholar 

  45. Kesselheim AS, Myers JA, Avorn J (2011) Characteristics of clinical trials to support approval of orphan vs nonorphan drugs for cancer. JAMA 305(22):2320–2326. https://doi.org/10.1001/jama.2011.769

    Article  CAS  PubMed  Google Scholar 

  46. Smpokou P (2018) Clinical trial design in rare diseases: special considerations. https://cersi.umd.edu/sites/cersi.umd.edu/files/S01%20-%2008%20Smpokou.pdf. Accessed 02/10/2023 2022

  47. Sasinowski F (2019) Clinical trial design considerations in rare disease studies. https://www.fda.gov/media/131881/download. Accessed 02/10/2023

  48. Maynard J (2019) FDA is working to bridge the gaps and meet needs for rare disease product development. https://www.fda.gov/news-events/fda-voices/fda-working-bridge-gaps-and-meet-needs-rare-disease-product-development. Accessed 02/10/2023

  49. Sriram P (2020) Beyond placebo: alternative options to the randomized control trial design in rare disease studies. Clin Trial Pract Open J 1(1):42–45

    Google Scholar 

  50. Post FA, Winston J, Andrade-Villanueva JF, Fisher M, Liu Y, Beraud C, Abram ME, Graham H, Rhee MS, Cheng AK, Szwarcberg J, Study T (2015) Elvitegravir/cobicistyat/emtricitabine/tenofovir DF in HIV-infected patients with mild-to-moderate renal impairment. J Acquir Immune Defic Syndr 68(3):310–313. https://doi.org/10.1097/QAI.0000000000000476

    Article  CAS  PubMed  Google Scholar 

  51. Mulberg AE, Bucci-Rechtweg C, Giuliano J, Jacoby D, Johnson FK, Liu Q, Marsden D, McGoohan S, Nelson R, Patel N (2019) Regulatory strategies for rare diseases under current global regulatory statutes: a discussion with stakeholders. Orphanet J Rare Dis 14(1):1–10

    Article  Google Scholar 

  52. Gagne JJ, Thompson L, O’Keefe K, Kesselheim AS (2014) Innovative research methods for studying treatments for rare diseases: methodological review. BMJ. https://doi.org/10.1136/bmj.g6802

    Article  PubMed  PubMed Central  Google Scholar 

  53. Quan H, Xu Y, Chen Y, Gao L, Chen X (2018) A case study of an adaptive design for a clinical trial with 2 doses and 2 endpoints in a rare disease area. Pharm Stat 17(6):797–810

    Article  PubMed  Google Scholar 

  54. Hilgers RD, König F, Molenberghs G, Senn S (2016) Design and analysis of clinical trials for small rare disease populations. J Rare Dis Res Treatment 1(1):53–60

    Article  Google Scholar 

  55. Nony P, Kassai B, Cornu C (2020) A methodological framework for drug development in rare diseases: the CRESim program: epilogue and perspectives. Therapies 75(2):149–156

    Article  Google Scholar 

  56. Jacqmin P, Laveille C, Snoeck E, Jordan MB, Locatelli F, Ballabio M, de Min C (2022) Emapalumab in primary haemophagocytic lymphohistiocytosis and the pathogenic role of interferon gamma: a pharmacometric model-based approach. Br J Clin Pharmacol 88(5):2128–2139

    Article  CAS  PubMed  Google Scholar 

  57. Locatelli F, Jordan MB, Allen C, Cesaro S, Rizzari C, Rao A, Degar B, Garrington TP, Sevilla J, Putti M-C (2020) Emapalumab in children with primary hemophagocytic lymphohistiocytosis. N Engl J Med 382(19):1811–1822

    Article  PubMed  Google Scholar 

  58. Johnson TN, Abduljalil K, Nicolas JM, Muglia P, Chanteux H, Nicolai J, Gillent E, Cornet M, Sciberras D (2021) Use of a physiologically based pharmacokinetic–pharmacodynamic model for initial dose prediction and escalation during a paediatric clinical trial. Br J Clin Pharmacol 87(3):1378–1389

    Article  CAS  PubMed  Google Scholar 

  59. Johnson TN, Small BG, Berglund EG, Rowland Yeo K (2021) A best practice framework for applying physiologically-based pharmacokinetic modeling to pediatric drug development. CPT: Pharmacometrics Syst Pharmacol 10(9):967–972

    CAS  PubMed  Google Scholar 

  60. Dumortier T, Heimann G, Fink M (2021) Exposure-response modeling for extrapolation from adult to pediatric patients who differ with respect to prognostic factors: application to everolimus. CPT: Pharmacometrics Syst Pharmacol 10(6):589–598

    CAS  PubMed  Google Scholar 

  61. Yoneyama K, Schmitt C, Chang T, Dhalluin C, Nagami S, Petry C, Levy GG (2022) A model-based framework to inform the dose selection and study design of emicizumab for pediatric patients with hemophilia A. J Clin Pharmacol 62(2):232–244

    Article  CAS  PubMed  Google Scholar 

  62. Robbie GJ, Zhao L, Mondick J, Losonsky G, Roskos LK (2012) Population pharmacokinetics of palivizumab, a humanized anti-respiratory syncytial virus monoclonal antibody, in adults and children. Antimicrob Agents Chemother 56(9):4927–4936

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Loscher W, Potschka H (2005) Role of drug efflux transporters in the brain for drug disposition and treatment of brain diseases. Prog Neurobiol 76(1):22–76. https://doi.org/10.1016/j.pneurobio.2005.04.006

    Article  CAS  PubMed  Google Scholar 

  64. Sahasrabudhe SA, Cheng S, Al-Kofahi M, Jarnes JR, Weinreb NJ, Kartha RV (2022) PBPK model development, validation, and application for prediction of eliglustat drug-drug interactions. Clin Pharmacol Therap 112:1254–1263

    Article  CAS  Google Scholar 

  65. Vu L, Cox GF, Ibrahim J, Peterschmitt MJ, Ross L, Thibault N, Turpault S (2020) Effects of paroxetine, ketoconazole, and rifampin on the metabolism of eliglustat, an oral substrate reduction therapy for Gaucher disease type 1. Mol Genet Metabol Rep 22:100552

    CAS  Google Scholar 

  66. Phillips D, Pokrzywinski R. Clinical Outcomes Assessments.

  67. Urach S, Gaasterland C, Posch M, Jilma B, Roes K, Rosenkranz G, Van der Lee J, Ristl R (2019) Statistical analysis of goal attainment scaling endpoints in randomised trials. Stat Methods Med Res 28(6):1893–1910

    Article  CAS  PubMed  Google Scholar 

  68. Taylor RW, Turnbull DM (2005) Mitochondrial DNA mutations in human disease. Nat Rev Genet 6(5):389–402

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Lennie JL, Mondick JT, Gastonguay MR (2022) Bayesian modeling and simulation to inform rare disease drug development early decision-making: application to Duchenne muscular dystrophy. PLoS ONE 17(4):e0247286

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Johnson TN (2008) The problems in scaling adult drug doses to children. Arch Dis Child 93(3):207–211. https://doi.org/10.1136/adc.2006.114835

    Article  CAS  PubMed  Google Scholar 

  71. Emoto C, Fukuda T, Johnson TN, Adams DM, Vinks AA (2015) Development of a pediatric physiologically based pharmacokinetic model for sirolimus: applying principles of growth and maturation in neonates and infants. CPT Pharmacometrics Syst Pharmacol 4(2):e17. https://doi.org/10.1002/psp4.17

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Rakhit A, Kochak GM, Tipnis V, Hurley ME (1987) Inhibition of renal clearance of furosemide by pentopril, an angiotensin-converting enzyme inhibitor. Clin Pharmacol Ther 41(5):580–586

    Article  CAS  PubMed  Google Scholar 

  73. US Food and Drug Administration. Center for drug evaluation and research application number: 761047orig1s000 clinical review(s). (10/22/2017). https://www.accessdata.fda.gov/drugsatfda_docs/nda/2017/761047Orig1s000MedR.pdf. Accessed 09/09/2022

  74. Barrett J, Knab T, Roddy W, Beusmans J, Jordie E, Singh K, Davis J, Romero K, Padula M, Thebaud B (2022) Landscape analysis for a neonatal disease progression model of bronchopulmonary dysplasia: Leveraging clinical trial experience and real-world data. Front Pharmacol 13:988974

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Gordon LB, Shappell H, Massaro J, D’Agostino RB Sr, Brazier J, Campbell SE, Kleinman ME, Kieran MW (2018) Association of lonafarnib treatment vs no treatment with mortality rate in patients with Hutchinson-Gilford progeria syndrome. JAMA 319(16):1687–1695. https://doi.org/10.1001/jama.2018.3264

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. US Food and Drug Administration Center for Drug Evaluation and Research (2020) Lonafarnib integrated review. 213969Orig1s000.

  77. U.S. Food and Drug Administration. (2023) Considerations for the design and conduct of externally controlled trials for drug and biological products. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-design-and-conduct-externally-controlled-trials-drug-and-biological-products. Accessed 02/10/2023

  78. Barrett JS, Nicholas T, Azer K, Corrigan BW (2022) Role of disease progression models in drug development. Pharm Res 39(8):1803–1815. https://doi.org/10.1007/s11095-022-03257-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Hill-McManus D, Hughes DA (2021) Combining model-based clinical trial simulation, pharmacoeconomics, and value of information to optimize trial design. CPT Pharmacometrics Syst Pharmacol 10(1):75–83. https://doi.org/10.1002/psp4.12579

    Article  CAS  PubMed  Google Scholar 

  80. Marion J, Ruiz J, Saville BR (2022) Bayesian model of disease progression in mucopolysaccaridosis IIIA. Stat Med 41(18):3579–3595. https://doi.org/10.1002/sim.9435

    Article  PubMed  Google Scholar 

  81. Barrett JS, Cala Pane M, Knab T, Roddy W, Beusmans J, Jordie E, Singh K, Davis JM, Romero K, Padula M, Thebaud B, Turner M (2022) Landscape analysis for a neonatal disease progression model of bronchopulmonary dysplasia: Leveraging clinical trial experience and real-world data. Front Pharmacol 13:988974

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Rudebeck M, Scott C, Rhodes NP, van Kan C, Olsson B, Al-Sbou M, Hall AK, Sireau N, Ranganath LR (2021) Clinical development innovation in rare diseases: lessons learned and best practices from the DevelopAKUre consortium. Orphanet J Rare Dis 16(1):1–10

    Article  Google Scholar 

  83. Moore J, Goodson N, Wicks P, Reites J (2022) What role can decentralized trial designs play to improve rare disease studies? Orphanet J Rare Dis 17(1):1–4

    Article  Google Scholar 

  84. Crossnohere NL, Fischer R, Crossley E, Vroom E, Bridges JF (2020) The evolution of patient-focused drug development and Duchenne muscular dystrophy. Expert Rev Pharmacoecon Outcomes Res 20(1):57–68

    Article  PubMed  Google Scholar 

  85. van Koningsbruggen-Rietschel S, Dunlevy F, Bulteel V, Hayes K, Verbrugge A, Janssens HM, Dufeu N, Simmonds NJ, Dupont LJ, Downey DG (2021) Protecting clinical trials in cystic fibrosis during the SARS-CoV-2 pandemic: risks and mitigation measures. Trials 22(1):1–7

    Article  Google Scholar 

  86. U.S. Food and Drug Administration (2022) General clinical pharmacology considerations for neonatal studies for drugs and biological products. https://www.fda.gov/media/129532/download.

  87. Raju KS, Taneja I, Singh SP, Wahajuddin (2013) Utility of noninvasive biomatrices in pharmacokinetic studies. Biomed Chromatogr 27(10):1354–1366. https://doi.org/10.1002/bmc.2996

    Article  CAS  PubMed  Google Scholar 

  88. Vinks A, Emoto C, Fukuda T (2015) Modeling and simulation in pediatric drug therapy: application of pharmacometrics to define the right dose for children. Clin Pharmacol Ther 98(3):298–308

    Article  CAS  PubMed  Google Scholar 

  89. Bauer RJ, Hooker AC, Mentre F (2021) Tutorial for $ DESIGN in NONMEM: Clinical trial evaluation and optimization. CPT: Pharmacometrics Syst Pharmacol 10(12):1452–1465

    CAS  PubMed  Google Scholar 

  90. Feng K, Leary RH, Dunlavey M, Rostami-Hodjegan A (2017) Simulation re-estimation and Bayesian optimal design for population pharmacokinetic studies. In: Journal of pharmacokinetics and pharmacodynamics. Springer/Plenum Publishers, New York, pp S58–S58

  91. Inoue S, Howgate E, Rowland-Yeo K, Shimada T, Yamazaki H, Tucker G, Rostami-Hodjegan A (2006) Prediction of in vivo drug clearance from in vitro data: II—potential inter-ethnic differences. Xenobiotica 36(6):499–513

    Article  CAS  PubMed  Google Scholar 

  92. Barter ZE, Tucker GT, Rowland-Yeo K (2013) Differences in cytochrome p450-mediated pharmacokinetics between Chinese and Caucasian populations predicted by mechanistic physiologically based pharmacokinetic modelling. Clin Pharmacokinet 52(12):1085–1100

    Article  CAS  PubMed  Google Scholar 

  93. Malinowski HJ, Westelinck A, Sato J, Ong T (2008) Same drug, different dosing: differences in dosing for drugs approved in the United States, Europe, and Japan. J Clin Pharmacol 48(8):900–908

    Article  CAS  PubMed  Google Scholar 

  94. Yasuda S, Zhang L, Huang SM (2008) The role of ethnicity in variability in response to drugs: focus on clinical pharmacology studies. Clin Pharmacol Ther 84(3):417–423

    Article  CAS  PubMed  Google Scholar 

  95. Miller KL, Fermaglich LJ, Maynard J (2021) Using four decades of FDA orphan drug designations to describe trends in rare disease drug development: substantial growth seen in development of drugs for rare oncologic, neurologic, and pediatric-onset diseases. Orphanet J Rare Dis 16(1):1–10

    Article  Google Scholar 

  96. Marks P (2022) Enhancing gene therapy regulatory interactions. Expert Opin Biol Ther 22:1–2

    Article  Google Scholar 

  97. Cohen E, Berry JG, Sanders L, Schor EL, Wise PH (2018) Status complexicus? The emergence of pediatric complex care. Pediatrics 141(Supplement 3):S202–S211

    Article  PubMed  Google Scholar 

  98. Cada DJ, Torres S, Levien TL, Baker DE (2013) Elvitegravir/Cobicistat/Emtricitabine/Tenofovir disoproxil fumarate tablets. Hosp Pharm 48(1):48–56. https://doi.org/10.1310/hpj4801-48.test

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Xu L, Liu H, Hong A, Vivian R, Murray BP, Callebaut C, Choi YC, Lee MS, Chau J, Tsai LK, Stray KM, Strickley RG, Wang J, Tong L, Swaminathan S, Rhodes GR, Desai MC (2014) Structure-activity relationships of diamine inhibitors of cytochrome P450 (CYP) 3A as novel pharmacoenhancers: part II—P2/P3 region and discovery of cobicistat (GS-9350). Bioorg Med Chem Lett 24(3):995–999. https://doi.org/10.1016/j.bmcl.2013.12.057

    Article  CAS  PubMed  Google Scholar 

  100. Blumenrath SH, Lee BY, Low L, Prithviraj R, Tagle D (2020) Tackling rare diseases: clinical trials on chips. Exp Biol Med 245(13):1155–1162

    Article  CAS  Google Scholar 

  101. Freel BA, Sheets JN, Francis KR (2020) iPSC modeling of rare pediatric disorders. J Neurosci Methods 332:108533

    Article  CAS  PubMed  Google Scholar 

  102. Kinarivala N, Morsy A, Patel R, Carmona AV, Sajib MS, Raut S, Mikelis CM, Al-Ahmad A, Trippier PC (2020) An iPSC-derived neuron model of CLN3 disease facilitates small molecule phenotypic screening. ACS Pharmacol Transl Sci 3(5):931–947

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Cohen JL, Chakraborty P, Fung-Kee-Fung K, Schwab ME, Bali D, Young SP, Gelb MH, Khaledi H, DiBattista A, Smallshaw S (2022) In utero enzyme-replacement therapy for infantile-onset Pompe’s disease. New Engl J Med 135:S33

    Google Scholar 

  104. Azer K, Kaddi CD, Barrett JS, Bai JP, McQuade ST, Merrill NJ, Piccoli B, Neves-Zaph S, Marchetti L, Lombardo R (2021) History and future perspectives on the discipline of quantitative systems pharmacology modeling and its applications. Front Physiol 12:637999

    Article  PubMed  PubMed Central  Google Scholar 

  105. Parolo S, Tomasoni D, Bora P, Ramponi A, Kaddi C, Azer K, Domenici E, Neves-Zaph S, Lombardo R (2021) Reconstruction of the cytokine signaling in lysosomal storage diseases by literature mining and network analysis. Front Cell Dev Biol. https://doi.org/10.3389/fcell.2021.703489

    Article  PubMed  PubMed Central  Google Scholar 

  106. Dagenais S, Russo L, Madsen A, Webster J, Becnel L (2022) Use of real-world evidence to drive drug development strategy and inform clinical trial design. Clin Pharmacol Ther 111(1):77–89

    Article  PubMed  Google Scholar 

  107. Musuamba FT, Skottheim Rusten I, Lesage R, Russo G, Bursi R, Emili L, Wangorsch G, Manolis E, Karlsson KE, Kulesza A (2021) Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility. CPT: Pharmacometrics Syst Pharmacol 10(8):804–825

    CAS  PubMed  Google Scholar 

  108. Therapeutic Goods Administration (2018) Orphan drug designation. https://www.tga.gov.au/resources/resource/guidance/orphan-drug-designation. Accessed 01/19/2023

  109. European Medicines Agency Horizon 2020 research funding https://www.ema.europa.eu/en/partners-networks/academia/horizon-2020-research-funding. Accessed 04/20/2023

  110. ERA-LEARN E-Rare: ERA-NET for research programmes on rare diseases. https://www.era-learn.eu/network-information/networks/e-rare. Accessed 04/20/2023

  111. European Medicines Agency Orphan incentives. https://www.ema.europa.eu/en/human-regulatory/research-development/orphan-designation/orphan-incentives. Accessed 01/19/2023

  112. European Medicines Agency Scientific advice and protocol assistance. https://www.ema.europa.eu/en/human-regulatory/research-development/scientific-advice-protocol-assistance. Accessed 04/20/2023

  113. National Institutes of Biomedical Innovation Health and Nutrition (2018) Orphan products development support program. https://www.nibiohn.go.jp/en/activities/orphan-support.html. Accessed 01/19/2023

  114. Pharmaceutical and Medical Devices Agency. Regulatory approach to promote orphan drug development in Japan. https://www.pmda.go.jp/files/000247217.pdf. Accessed 02/10/2023

  115. Sugai H (2012) Overview of consultation system in Japan. https://www.pmda.go.jp/files/000157641.pdf. Accessed 02/10/2023

  116. Pharmaceutical and medical devices agency incentives and regulatory considerations in orphan drug/medical device development—situation in Japan.

  117. U.S. Food and Drug Administration Center for Drug Evaluation and Research. Accelerating rare disease cures (ARC) program. https://www.fda.gov/about-fda/center-drug-evaluation-and-research-cder/accelerating-rare-disease-cures-arc-program?utm_medium=email&utm_source=govdelivery. Accessed 01/19/2023

  118. Critical Path Institute Rare disease cures accelerator—data and analytics platform. https://c-path.org/programs/rdca-dap/. Accessed 01/19/2023

  119. U.S. Food and Drug Administration. Rare disease cures accelerator. https://www.fda.gov/drugs/regulatory-science-research-and-education/rare-disease-cures-accelerator. Accessed 01/19/2023

  120. U.S. Food and Drug Administration. (2022) Rare disease endpoint advancement pilot program. https://www.fda.gov/drugs/development-resources/rare-disease-endpoint-advancement-pilot-program. Accessed 01/19/2023

  121. U.S. Food and Drug Administration (2020) Human gene therapy for rare diseases. https://www.fda.gov/media/113807/download.

  122. U.S. Food and Drug Administration. (2019) Rare diseases: Natural history studies for drug development. https://www.fda.gov/media/122425/download.

  123. U.S. Food and Drug Administration. (2019) Rare diseases: Common issues in drug development. https://www.fda.gov/media/119757/download.

  124. U.S. Food and Drug Administration. (2018) Rare diseases: Early drug development and the role or pre-IND meetings. https://www.fda.gov/media/119757/download.

  125. U.S. Food and Drug Administration (2020) Slowly progressive, low-prevalence rare diseases with substrate deposition that result from single enzyme defects: providing evidence of effectiveness for replacement or corrective therapies. https://www.fda.gov/media/136058/download

  126. U.S. Food and Drug Administration. (2017) Pediatric rare diseases—a collaborative approach for drug development using Gaucher disease as a model. https://www.fda.gov/media/109465/download

  127. European Commission How Horizon Europe was developed. https://research-and-innovation.ec.europa.eu/funding/funding-opportunities/funding-programmes-and-open-calls/horizon-europe/how-horizon-europe-was-developed_en. Accessed 04/20/2023

  128. U.S. Food and Drug Administration (2023) Considerations for the design and conduct of externally controlled trials for drug and biological products. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-design-and-conduct-externally-controlled-trials-drug-and-biological-products.

  129. Lowes LP, Alfano LN, Arnold WD, Shell R, Prior TW, McColly M, Lehman KJ, Church K, Sproule DM, Nagendran S (2019) Impact of age and motor function in a phase 1/2A study of infants with SMA type 1 receiving single-dose gene replacement therapy. Pediatr Neurol 98:39–45

    Article  PubMed  Google Scholar 

  130. Lovell DJ, Giannini EH, Reiff A, Cawkwell GD, Silverman ED, Nocton JJ, Stein LD, Gedalia A, Ilowite NT, Wallace CA (2000) Etanercept in children with polyarticular juvenile rheumatoid arthritis. N Engl J Med 342(11):763–769

    Article  CAS  PubMed  Google Scholar 

  131. Chabane M, Dioh W, Dilda P, Lafont R, Veillet S, Voit T, Agus S (2019) P. 149The MYODA operational seamless clinical trial design phase I to III: a new approach for rare diseases to evaluate the safety, efficacy, pharmacokinetics, and pharmacodynamics of BIO101 (MAS activator) in paediatric patients with a genetically confirmed diagnosis of Duchenne muscular dystrophy. Neuromusc Disord 29:S92

    Article  Google Scholar 

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MAA designed the review, wrote most of the clinical Pharmacology section. JB wrote the regulatory section, contributed to the clinical pharmacology section. GD contributed to the clinical pharmacology section. BA wrote the conclusion section, contributed to the clinical pharmacology section. All authors reviewed the manuscript.

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Correspondence to Mariam A. Ahmed.

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Ahmed, M.A., Burnham, J., Dwivedi, G. et al. Achieving big with small: quantitative clinical pharmacology tools for drug development in pediatric rare diseases. J Pharmacokinet Pharmacodyn 50, 429–444 (2023). https://doi.org/10.1007/s10928-023-09863-x

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