Prediction of Drug Clearance in Preterm and Term Neonates by Minimal Physiologically Based Pharmacokinetic Model and Allometry: A Comparison with Whole BODY Physiologically Based Pharmacokinetic Model
Main Article Content
Abstract
Objectives: The objective of this study is to compare the predictive performance of a minimal physiologically based Pharmacokinetic model (mPBPK) and an allometric model with a whole body physiologically based pharmacokinetic Model (PBPK) to predict clearance of drugs in preterm and term neonates.
Methods: From the literature, 6 studies were identified in which clearance of drugs in preterm and term neonates were predicted by whole body PBPK model. The mPBPK model consisted of four physiological parameters; liver and kidney weights and blood flow to these organs. From allometric models, the values of these physiological parameters were predicted in the neonates. The sum of these four physiological parameters were then used to predict CL in the neonates using adult CL values. The allometric model was based on Age Dependent Exponent Model (ADE). ADE uses different allometric exponents across the age groups. These exponents are 1.2 for preterm and 1.1 for term neonates for age 0-3 months, exponents 1.0, 0.90, and 0.75 for >3 months-2 years, >2-5 years, and >5 years, respectively. For the prediction of CL in the neonates from allometry adult CL values were used. The predicted clearance values using PBPK and mPBPK and ADE model were compared with the experimental (clinical) values. The acceptable prediction error was within 0.5-1.5-fold.
Results: There were 26 drugs with 86 observations. From PBPK, mPBPK, and allometric models, 90.7%, 98.8%, and 93.0% observations were within 2-fold prediction error, respectively. From PBPK, mPBPK, and allometric models, 81.4%, 90.7%, and 84.9% observations were within 0.5-2-fold prediction error, respectively.
Conclusions: This study indicates that the predictive performance of whole body PBPK, mPBPK and allometric models are essentially similar for the prediction of drug clearance in preterm and term neonates. mPBPK and allometry are much easier to develop than whole body PBPK and are as accurate and robust as whole body PBPK.
Keywords:
Preterm and term neonates, whole body PBPK model, minimal PBPK model, allometry, clearance
Article Details
How to Cite
MAHMOOD, Iftekhar.
Prediction of Drug Clearance in Preterm and Term Neonates by Minimal Physiologically Based Pharmacokinetic Model and Allometry: A Comparison with Whole BODY Physiologically Based Pharmacokinetic Model.
Medical Research Archives, [S.l.], v. 11, n. 8, aug. 2023.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/4315>. Date accessed: 04 dec. 2024.
doi: https://doi.org/10.18103/mra.v11i8.4315.
Section
Research Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
References
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28. Mahmood I. Prediction of total and renal clearance of renally secreted drugs in neonates and infants (≤3 months of age). Journal of Clinical and Translational Research 2022; 8:445-52.
29. Huisinga W, Solms A, Fronton L, Pilari S. Modeling interindividual variability in physiologically based pharmacokinetics and its link to mechanistic covariate modeling. CPT Pharmacometrics Syst Pharmacol. 2012 Sep 26;1:e4.
30. Calvier EA, Krekels EH, Välitalo PA, Rostami-Hodjegan A, Tibboel D, Danhof M, Knibbe CA. Allometric Scaling of Clearance in Paediatric Patients: When Does the Magic of 0.75 Fade? Clin Pharmacokinet. 2017;56:273-285.
31. Glazier D. Variable metabolic scaling breaks the law: from 'Newtonian' to 'Darwinian' approaches. In Proceedings of the Royal Society B: Biological Sciences. October 2022. 289: 20221605.
32. Wang C, Peeters MY, Allegaert K, van Oud-Alblas HJ, Krekels EH, et al. A bodyweight-dependent allometric exponent for scaling clearance across the human life-span. Pharm Res 2012;29:1570-81.
33. Mahmood I. Prediction of drug clearance in preterm and term neonates: different exponents for different age groups? In: Pharmacokinetic allometric scaling in pediatric drug development. Rockville: Pine House Publishers; 2013; p. 88-100.
34. Knell JM. On the analysis of non-linear allometries. Ecological Entomology 2009; 34, 1-11.
35. Heizman P, Eckert M, Ziegler W. Pharmacokinetics and bioavailability of midazolam in man. Br. J Clin Pharmacol 1983;16:43S-9S.
36. Martin W, Koselowske G, Töberich H, Kerkmann T, Mangold B, Augustin J. Pharmacokinetics and absolute bioavailability of ibuprofen after oral administration of ibuprofen lysine in man. Biopharm Drug Dispos 1990;11:265-78.
37. Golper T, Noonan H, Elzinga L et al. Vancomycin pharmacokinetics, renal handling, and nonrenal clearances in normal human subjects. Clin Pharmacol Therap. 1988;43:565-70.
38. The Bantam Medical Dictionary (2nd edition). New York, Bantam Books, 1996;313.
39. Alcorn J, McNamara PJ. Ontogeny of hepatic and renal systemic clearance pathways in infants: part I. Clin Pharmacokinet 2002;41:959-98.
40. Alcorn J, McNamara PJ. Ontogeny of hepatic and renal systemic clearance pathways in infants: part II. Clin Pharmacokinet 2002; 41:1077-94.
41. Kanamori M, Takahashi H, Echizen H. Developmental changes in the liver weight- and body weight-normalized clearance of theophylline, phenytoin and cyclosporine in children. Int J Clin Pharmacol Ther 2002;40:485-92.
42. Wang C, Allegaert K, Peeters MY, Tibboel D, Danhof M, Knibbe CA. The allometric exponent for scaling clearance varies with age: a study on seven propofol datasets ranging from preterm neonates to adults. Br J Clin Pharmacol 2014;77:149-159.
43. Bartelink IH, Boelens JJ, Bredius RG, Egberts AC, Wang C, et al. Body weight-dependent pharmacokinetics of busulfan in paediatric haematopoietic stem cell transplantation patients: towards individualized dosing. Clin Pharmacokinet 2012; 51:331-45.
44. Mahmood I, Staschen CM, Goteti K. Prediction of drug clearance in children: an evaluation of the predictive performance of several models. AAPS J 2014; 16:1334-43.
2. Kearns G, Abdel-Rahman S, Alander S, etal. Developmental Pharmacology: Drug Disposition, Action, and Therapy in Infants and Children. N Engl J Med 2003;349:1157-67.
3. Abernethy D, Burckart G. Pediatric dose Selection. Clin Pharmacol Ther 2010;87:270-1.
4. Green D, Zineh I, Burckart G. Pediatric Drug Development: Outlook for Science-Based Innovation. Clin Pharmacol Ther 2018;103:376-8.
5. Rowland M, Peck C, Tucker G. Physiologically-based pharmacokinetics in drug development and regulatory science. Annu Rev Pharmacol Toxicol. 2011;51:45-73.
6. Zhou W, Johnson TN, Xu H, Cheung S, Bui KH, Li J, Al-Huniti N, Zhou D. Predictive Performance of Physiologically Based Pharmacokinetic and Population Pharmacokinetic Modeling of Renally Cleared Drugs in Children. CPT Pharmacometrics Syst Pharmacol 2016;5:475-83.
7. Edginton AN, Theil FP, Schmitt W, Willmann S. Whole body physiologically-based pharmacokinetic models: their use in clinical drug development. Expert Opin Drug Metab Toxicol. 2008;4:1143-1152.
8. Mahmood I. Prediction of drug clearance in premature and mature neonates, infants, and children ≤2 years of age: A comparison of the predictive performance of 4 allometric models. J Clin Pharmacol 2015; 56:733-39.
9. Edginton AN, Willmann S. Physiology-based versus allometric scaling of clearance in children: an eliminating process based comparison. Paediatr Perinat Drug Ther. 2006;7:146-53.
10. Abduljalil K, Pan Z, Pansari A, et al. Preterm Physiologically Based Pharmacokinetic Model. Part II: Applications of the Model to Predict Drug Pharmacokinetics in the Preterm Population. Clinical Pharmacokinet. 2020; 59:501-18.
11. Edginton AN, Schmitt W, Voith B, Willmann S. A mechanistic approach for the scaling of clearance in children. Clin Pharmacokinet. 2006;45:683-704.
12. Upreti VV, Wahlstrom JL. Meta-analysis of hepatic cytochrome P450 ontogeny to underwrite the prediction of pediatric pharmacokinetics using physiologically based pharmacokinetic modeling. J Clin Pharmacol 2016;56:266-83.
13. Heijden J, Feriksen J, Hoop-Sommen M, et al. Feasibility of a Pragmatic PBPK Modeling Approach: Towards Model-Informed Dosing in Pediatric Clinical Care. Clinical Pharmacokinet. 2022;61:1705-17.
14. Duan P, Fisher JW, Yoshida K,et al. Physiologically Based Pharmacokinetic Prediction of Linezolid and Emtricitabine in Neonates and Infants. Clin Pharmacokinet 2017;56:383-394.
15. Cao Y, Balthasar JP, Jusko WJ. Second-generation minimal physiologically-based pharmacokinetic model for monoclonal antibodies. J Pharmacokinet Pharmacodyn. 2013 (Epub ahead of print).
16. Cao Y, Jusko WJ. Applications of minimal physiologicallybased pharmacokinetic models. J Pharmacokinet Pharmacodyn. 2012;39:711-23.
17. Björkman S. Reduction and lumping of physiologically based pharmacokinetic models: prediction of the disposition of fentanyl and pethidine in humans by successively simplified models. J Pharmacokinet Pharmacodyn. 2003;30:285-307.
18. Björkman S. Prediction of drug disposition in infants and children by means of physiologically based pharmacokinetic (PBPK) modelling: theophylline and midazolam as model drugs. Br J Clin Pharmacol 2004; 59:691-704.
19. Hardiansyah D, Ng CM. Effects of the FcRn developmental pharmacology on the pharmacokinetics of therapeutic monoclonal IgG antibody in pediatric subjects using minimal physiologically-based pharmacokinetic modelling. MAbs. 2018;10(7): 1144-1156.
20. Mahmood I, Tegenge MA. A Comparative Study Between Allometric Scaling and Physiologically Based Pharmacokinetic Modeling for the Prediction of Drug Clearance From Neonates to Adolescents. J Clin Pharmacol. 2019;59:189-197.
21. Mahmood I, Tegenge MA. Spreadsheet-Based Minimal Physiological Models for the Prediction of Clearance of Therapeutic Proteins in Pediatric Patients. Journal of Clinical Pharmacology 2021, 61(S1), S108-S116.
22. Mahmood I, Ahmad T, Mansoor N, Sharib SM. Prediction of clearance in neonates and infants (≤3 months of age) for drugs which are glucuronidated: a comparative study between allometric scaling and physiologically based pharmacokinetic modeling. J Clin Pharmacol. 2017;57:476-83.
23. Mahmood I. A comparison of different methods for the first-in-pediatric dose selection. Journal of Clinical and Translational Research 2022; 8:369-81.
24. Mansoor N, Ahmad T, Alam Khan R, Sharib SM, Mahmood I. Prediction of clearance and dose of midazolam in preterm and term neonates: a comparative study between allometric scaling and physiologically based pharmacokinetic modeling. Am J Ther. 2019;26: e32-7.
25. Mahmood I. Prediction of Clearance of Monoclonal and Polyclonal Antibodies and Non-Antibody Proteins in Children: Application of Allometric Scaling. Antibodies (Basel) 2020; 9, 40.
26. Tegenge MA, Mahmood I. Age- and Bodyweight-dependent Allometric Exponent Model for Scaling Clearance and Maintenance Dose of Theophylline From Neonates to Adults. Ther Drug Monit. 2018; 40:635-41.
27. Mahmood I. Prediction of clearance, volume of distribution, and half-life of drugs in extremely low to low-birth-weight neonates: An allometric approach. Eur J Drug Metab Pharmacokinet. 2017; 42:601-10.
28. Mahmood I. Prediction of total and renal clearance of renally secreted drugs in neonates and infants (≤3 months of age). Journal of Clinical and Translational Research 2022; 8:445-52.
29. Huisinga W, Solms A, Fronton L, Pilari S. Modeling interindividual variability in physiologically based pharmacokinetics and its link to mechanistic covariate modeling. CPT Pharmacometrics Syst Pharmacol. 2012 Sep 26;1:e4.
30. Calvier EA, Krekels EH, Välitalo PA, Rostami-Hodjegan A, Tibboel D, Danhof M, Knibbe CA. Allometric Scaling of Clearance in Paediatric Patients: When Does the Magic of 0.75 Fade? Clin Pharmacokinet. 2017;56:273-285.
31. Glazier D. Variable metabolic scaling breaks the law: from 'Newtonian' to 'Darwinian' approaches. In Proceedings of the Royal Society B: Biological Sciences. October 2022. 289: 20221605.
32. Wang C, Peeters MY, Allegaert K, van Oud-Alblas HJ, Krekels EH, et al. A bodyweight-dependent allometric exponent for scaling clearance across the human life-span. Pharm Res 2012;29:1570-81.
33. Mahmood I. Prediction of drug clearance in preterm and term neonates: different exponents for different age groups? In: Pharmacokinetic allometric scaling in pediatric drug development. Rockville: Pine House Publishers; 2013; p. 88-100.
34. Knell JM. On the analysis of non-linear allometries. Ecological Entomology 2009; 34, 1-11.
35. Heizman P, Eckert M, Ziegler W. Pharmacokinetics and bioavailability of midazolam in man. Br. J Clin Pharmacol 1983;16:43S-9S.
36. Martin W, Koselowske G, Töberich H, Kerkmann T, Mangold B, Augustin J. Pharmacokinetics and absolute bioavailability of ibuprofen after oral administration of ibuprofen lysine in man. Biopharm Drug Dispos 1990;11:265-78.
37. Golper T, Noonan H, Elzinga L et al. Vancomycin pharmacokinetics, renal handling, and nonrenal clearances in normal human subjects. Clin Pharmacol Therap. 1988;43:565-70.
38. The Bantam Medical Dictionary (2nd edition). New York, Bantam Books, 1996;313.
39. Alcorn J, McNamara PJ. Ontogeny of hepatic and renal systemic clearance pathways in infants: part I. Clin Pharmacokinet 2002;41:959-98.
40. Alcorn J, McNamara PJ. Ontogeny of hepatic and renal systemic clearance pathways in infants: part II. Clin Pharmacokinet 2002; 41:1077-94.
41. Kanamori M, Takahashi H, Echizen H. Developmental changes in the liver weight- and body weight-normalized clearance of theophylline, phenytoin and cyclosporine in children. Int J Clin Pharmacol Ther 2002;40:485-92.
42. Wang C, Allegaert K, Peeters MY, Tibboel D, Danhof M, Knibbe CA. The allometric exponent for scaling clearance varies with age: a study on seven propofol datasets ranging from preterm neonates to adults. Br J Clin Pharmacol 2014;77:149-159.
43. Bartelink IH, Boelens JJ, Bredius RG, Egberts AC, Wang C, et al. Body weight-dependent pharmacokinetics of busulfan in paediatric haematopoietic stem cell transplantation patients: towards individualized dosing. Clin Pharmacokinet 2012; 51:331-45.
44. Mahmood I, Staschen CM, Goteti K. Prediction of drug clearance in children: an evaluation of the predictive performance of several models. AAPS J 2014; 16:1334-43.