Two simple methods to predict Pediatric Dose of Antituberculosis Medicines: Application of Allometry and Salisbury Rule

Background: In drug development, selecting the first-in-human dose is crucial. Similarly, in pediatric drug development, determining the first-in-pediatric dose is of paramount importance. Given that the pharmacokinetic, safety, and efficacy of a product are generally well established in adults, this information can be used to select an appropriate first-in-pediatric dose for pediatric clinical trials. Methods: Two simple methods – Salisbury Rule and allometric scaling – were evaluated for predicting the first-in-pediatric dose to initiate a clinical trial for antituberculosis medicines. To assess the predictive performance of these methods, the predicted doses were compared with the observed doses recommended by the World Health Organization (WHO) or the United States Food and Drug Administration (US FDA). Results: This study included seven antituberculosis drugs with 62 observations across different body weight groups. The predictive accuracy of both methods was excellent, with over 80% of the observations falling within a 30% prediction error. Conclusion: The predicted pediatric doses of antituberculosis drugs using the two proposed methods reconciled well with the recommended human doses from WHO or the US FDA. The methods are simple and can easily be calculated on a spreadsheet or calculator in a short amount of time. Relevance for patients: These two approaches are helpful for optimizing the selection of appropriate antituberculosis medication dosages in pediatric patients with tuberculosis, ensuring effective treatment, and minimizing potential risks.
- WHO. Operational Handbook on Tuberculosis Module 5: Management of Tuberculosis in Children and Adolescents; 2022. Available from: https://www.who.int/publications/i/ item/9789240046832 [Last accessed on 2024 Aug 19].
- World Health Organization. WHO Operational Handbook on Tuberculosis. Module 4: Treatment: Drug-susceptible Tuberculosis Treatment; 2022. Available from: https://apps. who.int/iris/handle/10665/354548 [Last accessed on 2024 Aug 19].
- World Health Organization. Global Tuberculosis Report; 2020. Available from: https://apps.who.int/iris/bitstream/ handle/10665/336069/9789240013131-eng.pdf [Last accessed on 2024 Aug 19].
- Drobac PC, Shin SS, Huamani P, et al. Risk factors for in-hospital mortality among children with tuberculosis: The 25-year experience in Peru. Pediatrics. 2012;130(2):e373-e379. doi: 10.1542/peds.2011-3048
- World Health Organization. Implementing the End TB Strategy: The Essentials; 2022. Available from: https://www. who.int/publications/i/item/9789240065093 [Last accessed on 2024 Aug 19].
- World Health Organization. Technical Report on the Pharmacokinetics and Pharmacodynamics (PK/PD) of Medicines Used in the Treatment of Drug-resistant Tuberculosis. World Health Organization; 2018. Available from: https://apps.who.int/iris/handle/10665/260440 [Last accessed on 2024 Aug 20].
- European Medicines Agency. Joint Evaluation of Regulation (EC) No 1901/2006 of the European Parliament and of the Council of 12 December 2006 on Medicinal Products for Paediatric Use and Regulation (EC) No 141/2000 of the European Parliament and of the Council of 16 December 1999 on Orphan Medicinal Products. Available from: https://health.ec.europa.eu/system/files/2020-08/orphan-regulation_eval_swd_2020-163_part-1_0.pdf [Last accessed on 2024 Aug 20].
- US Food and Drug Administration. General Clinical Pharmacology Considerations for Pediatric Studies for Medicines and Biological Products. Draft Guidance. Available from: https://www.fda.gov/downloads/medicines/ guidancecomplianceregulatoryinformation/guidances/ ucm425885.pdf [Last accessed on 2024 Aug 20].
- Antwi S, Yang H, Enimil A, et al. Pharmacokinetics of the first-line antituberculosis drugs in Ghanaian children with tuberculosis with or without HIV coinfection. Antimicrob Agents Chemother. 2017;61:e01701-e01716. doi: 10.1128/AAC.01701-16
- Bekker A, Schaaf HS, Draper HR, et al. Pharmacokinetics of rifampin, isoniazid, pyrazinamide, and ethambutol in infants dosed according to revised WHO-recommended treatment guidelines. Antimicrob Agents Chemother. 2016;60:2171-2179. doi: 10.1128/AAC.02600-15
- Justine M, Yeconia A, Nicodemu I, et al. Pharmacokinetics of first-line drugs among children with tuberculosis in rural Tanzania. J Pediatr Infect Dis Soc. 2020;9(1):14-20. doi: 10.1093/jpids/piy106
- Mahmood I. Dosing in children: A critical review of the pharmacokinetic allometric scaling and modelling approaches in paediatric drug development and clinical settings. Clin Pharmacokinet. 2014;53:327-346. doi: 10.1007/s40262-014-0134-5
- Green DJ, Zineh I, Burckart GJ. Pediatric drug development: Outlook for science-based innovation. Clin Pharmacol Ther. 2018;103:376-378. doi: 10.1002/cpt.1001
- Abernethy DR, Burckart GJ. Pediatric dose selection. Clin Pharmacol Ther. 2010;87:270-271. doi: 10.1038/clpt.2009.292
- Mahmood I. Dose selection in children. In: Pharmacokinetic Allometric Scaling in Pediatric Drug Development. Rockville: Pine House Publishers; 2013. p. 151-60.
- Rowland M, Peck C, Tucker G. Physiologically-based pharmacokinetics in drug development and regulatory science. Annu Rev Pharmacol Toxicol. 2011;51:45-73. doi: 10.1146/annurev-pharmtox-010510-100540
- 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;5:475-483. doi: 10.1002/psp4.12101
- 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. doi: 10.1517/17425255.4.9.1143
- 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;56:733-739. doi: 10.1002/jcph.652
- Cao Y, Balthasar JP, Jusko WJ. Second-generation minimal physiologically-based pharmacokinetic model for monoclonal antibodies. J Pharmacokinet Pharmacodyn. 2013;40:597-607. doi: 10.1007/s10928-013-9332-2
- Cao Y, Jusko WJ. Applications of minimal physiologically-based pharmacokinetic models. J Pharmacokinet Pharmacodyn. 2012;39:711-723. doi: 10.1007/s10928-012-9280-2
- 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. doi: 10.1023/a:1026194618660
- 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. doi: 10.1111/j.1365-2125.2004.02225.x
- 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. doi: 10.1002/jcph.1310
- Mahmood I, Tegenge MA. Spreadsheet-based minimal physiological models for the prediction of clearance of therapeutic proteins in pediatric patients. J Clin Pharmacol. 2021;61:S108-S116. doi: 10.1002/jcph.1846
- Mahmood I. A comparison of different methods for the first-in-pediatric dose selection. J Clin Transl Res. 2022; 8:369-81.
- Mahmood I, Ahmad T, Mansoor N, Sharib SM. Prediction of clearance in neonates and infants (≤ 3 months of age) for drugs that are glucuronidated: A comparative study between allometric scaling and physiologically based pharmacokinetic modeling. J Clin Pharmacol. 2017;57:476-483. doi: 10.1002/jcph.837
- Elias GP, Antoniali C, Mariano RC. Comparative study of rules employed for calculation of pediatric drug dosage. J Appl Oral Sci. 2005;13:114-119. doi: 10.1590/s1678-77572005000200004
- Munzenberger PJ, McKercher P. Pediatric dosing—the pharmacist’s dilemma. Contemp Pharm Pract. 1980;3:11-4.
- Lack JA, Stuart-Taylor ME. Calculation of drug dosage and body surface area of children. Br J Anaesth. 1997;78(5):601-605. doi: 10.1093/bja/78.5.601
- Mahmood I. A simple method for the prediction of therapeutic proteins (monoclonal and polyclonal antibodies and non-antibody proteins) for first-in-pediatric dose selection: Application of salisbury rule. Antibodies (Basel). 2022;11:66. doi: 10.3390/antib11040066
- Mahmood I. Application of allometric scaling and salisbury rule for the prediction of antimalarial drugs for first-in-pediatric dose selection. Eur J Drug Metab Pharmacokinet. 2023;48:587-594. doi: 10.1007/s13318-023-00848-2
- Jing W, Zong Z, Tang B. Population pharmacokinetic analysis of isoniazid among pulmonary tuberculosis patients from China. Antimicrob Agents Chemother. 2020;64:e01736-19. doi: 10.1128/AAC.01736-19
- Thomas L, Raju A, Sekhar C, et al. Influence of N-acetyltransferase 2 (NAT2) genotype/single nucleotide polymorphisms on clearance of isoniazid in tuberculosis patients: A systematic review of population pharmacokinetic models. Eur J Clin Pharmacol. 2022;78:1535-1553. doi: 10.1007/s00228-022-03362-7
- Box GE. Science and Statistics. J Am Stat Assoc. 1976;71:791-799. doi: 10.2307/2286841
- Mahmood I. Misconceptions and issues regarding allometric scaling during the drug development process. Expert Opin Drug Metab Toxicol. 2018;14:843-854. doi: 10.1080/17425255.2018.1499725
- Glazier DS. Variable metabolic scaling breaks the law: From ‘Newtonian’ to ‘Darwinian’ approaches. Proc Biol Sci. 2022;289:20221605. doi: 10.1098/rspb.2022.1605
- Valkengoed D, Krekels E, Knibbe C. All you need to know about allometric scaling: An integrative review on the theoretical basis, empirical evidence, and application in human pharmacology. Clin Pharmacokinet. 2024;64:173-192. doi: 10.1007/s40262-024-01444-6