Population pharmacokinetics of TLD-1, a novel liposomal doxorubicin, in a phase I trial.
Doxorubicin
Liposomes
Nanoparticles
Nonlinear mixed-effects model
Pharmacokinetics
Pharmacometrics
Journal
Cancer chemotherapy and pharmacology
ISSN: 1432-0843
Titre abrégé: Cancer Chemother Pharmacol
Pays: Germany
ID NLM: 7806519
Informations de publication
Date de publication:
15 Jun 2024
15 Jun 2024
Historique:
received:
04
02
2024
accepted:
18
05
2024
medline:
15
6
2024
pubmed:
15
6
2024
entrez:
15
6
2024
Statut:
aheadofprint
Résumé
TLD-1 is a novel pegylated liposomal doxorubicin (PLD) formulation aiming to optimise the PLD efficacy-toxicity ratio. We aimed to characterise TLD-1's population pharmacokinetics using non-compartmental analysis and nonlinear mixed-effects modelling. The PK of TLD-1 was analysed by performing a non-compartmental analysis of longitudinal doxorubicin plasma concentration measurements obtained from a clinical trial in 30 patients with advanced solid tumours across a 4.5-fold dose range. Furthermore, a joint parent-metabolite PK model of doxorubicin Medians The population PK of TLD-1, including its release and main metabolite, were successfully characterised using non-compartmental and compartmental analyses. Based on its long half-life, TLD-1 presents a promising candidate for further clinical development. The PK characteristics form the basis to investigate TLD-1 exposure-response (i.e., clinical efficacy) and exposure-toxicity relationships in the future. Once such relationships have been established, the developed population PK model can be further used in model-informed precision dosing strategies. ClinicalTrials.gov-NCT03387917-January 2, 2018.
Identifiants
pubmed: 38878207
doi: 10.1007/s00280-024-04679-z
pii: 10.1007/s00280-024-04679-z
doi:
Banques de données
ClinicalTrials.gov
['NCT03387917']
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. The Author(s).
Références
Tacar O, Sriamornsak P, Dass CR (2013) Doxorubicin: an update on anticancer molecular action, toxicity and novel drug delivery systems. J Pharm Pharmacol 65:157–170. https://doi.org/10.1111/j.2042-7158.2012.01567.x
doi: 10.1111/j.2042-7158.2012.01567.x
pubmed: 23278683
Rahman AM, Yusuf SW, Ewer MS (2007) Anthracycline-induced cardiotoxicity and the cardiac-sparing effect of liposomal formulation. Int J Nanomed 2:567–583
Speth PAJ, van Hoesel QGCM, Haanen C (1988) Clinical pharmacokinetics of doxorubicin. Clin Pharmacokinet 14:287–310. https://doi.org/10.2165/00003088-198814050-00002
doi: 10.2165/00003088-198814050-00002
Joerger M, Huitema ADR, Meenhorst PL et al (2005) Pharmacokinetics of low-dose doxorubicin and metabolites in patients with AIDS-related Kaposi sarcoma. Cancer Chemother Pharmacol 55:488–496. https://doi.org/10.1007/s00280-004-0900-4
doi: 10.1007/s00280-004-0900-4
pubmed: 15726371
O’Brien MER, Wigler N, Inbar M et al (2004) Reduced cardiotoxicity and comparable efficacy in a phase III trial of pegylated liposomal doxorubicin HCl (CAELYX
doi: 10.1093/annonc/mdh097
pubmed: 14998846
Olson RD, Mushlin PS, Brenner DE et al (1988) Doxorubicin cardiotoxicity may be caused by its metabolite, doxorubicinol. Proc Natl Acad Sci USA 85:3585–3589. https://doi.org/10.1073/pnas.85.10.3585
doi: 10.1073/pnas.85.10.3585
pubmed: 2897122
pmcid: 280258
Boucek RJ, Kunkel EM, Graham TP et al (1987) Doxorubicinol, the metabolite of doxorubucin, is more cardiotoxic than doxorubicin. Pediatr Res 21:187A-187A. https://doi.org/10.1203/00006450-198704010-00127
doi: 10.1203/00006450-198704010-00127
Committee for Medicinal Products for Human Use (CHMP) European Medicines Agency. Caelyx summary of product characteristics. https://www.ema.europa.eu/en/documents/product-information/caelyx-pegylated-liposomal-epar-product-information_en.pdf . Accessed 20 Nov 2020
Symon Z, Peyser A, Tzemach D et al (1999) Selective delivery of doxorubicin to patients with breast carcinoma metastases by stealth liposomes. Cancer 86:72–78. https://doi.org/10.1002/(SICI)1097-0142(19990701)86:1%3c72::AID-CNCR12%3e3.0.CO;2-1
doi: 10.1002/(SICI)1097-0142(19990701)86:1<72::AID-CNCR12>3.0.CO;2-1
pubmed: 10391566
Gabizon A, Shmeeda H, Barenholz Y (2003) Pharmacokinetics of pegylated liposomal doxorubicin: review of animal and human studies. Clin Pharmacokinet 42:419–436. https://doi.org/10.2165/00003088-200342050-00002
doi: 10.2165/00003088-200342050-00002
pubmed: 12739982
Maeda H, Wu J, Sawa T et al (2000) Tumor vascular permeability and the EPR effect in macromolecular therapeutics: a review. J Control Release 65:271–284. https://doi.org/10.1016/S0168-3659(99)00248-5
doi: 10.1016/S0168-3659(99)00248-5
pubmed: 10699287
Rosenblum D, Joshi N, Tao W et al (2018) Progress and challenges towards targeted delivery of cancer therapeutics. Nat Commun 9:1410. https://doi.org/10.1038/s41467-018-03705-y
doi: 10.1038/s41467-018-03705-y
pubmed: 29650952
pmcid: 5897557
Gordon AN, Fleagle JT, Guthrie D et al (2001) Recurrent epithelial ovarian carcinoma: a randomized phase III study of pegylated liposomal doxorubicin versus topotecan. J Clin Oncol 19:3312–3322. https://doi.org/10.1200/JCO.2001.19.14.3312
doi: 10.1200/JCO.2001.19.14.3312
pubmed: 11454878
Amantea MA, Forrest A, Northfelt DW, Mamelok R (1997) Population pharmacokinetics and pharmacodynamics of pegylated-liposomal doxorubicin in patients with AIDS-related Kaposi’s sarcoma. Clin Pharmacol Ther 61:301–311. https://doi.org/10.1016/S0009-9236(97)90162-4
doi: 10.1016/S0009-9236(97)90162-4
pubmed: 9084455
Xu L, Wang W, Sheng YC, Zheng QS (2010) Pharmacokinetics and its relation to toxicity of pegylated-liposomal doxorubicin in chinese patients with breast tumours. J Clin Pharm Ther 35:593–601. https://doi.org/10.1111/j.1365-2710.2009.01128.x
doi: 10.1111/j.1365-2710.2009.01128.x
pubmed: 20831683
Yokomichi N, Nagasawa T, Coler-Reilly A et al (2013) Pathogenesis of hand-foot syndrome induced by PEG-modified liposomal doxorubicin. Hum Cell 26:8–18. https://doi.org/10.1007/s13577-012-0057-0
doi: 10.1007/s13577-012-0057-0
pubmed: 23386177
pmcid: 3595474
Charrois GJR, Allen TM (2004) Drug release rate influences the pharmacokinetics, biodistribution, therapeutic activity, and toxicity of pegylated liposomal doxorubicin formulations in murine breast cancer. Biochim Biophys Acta Biomembr 1663:167–177. https://doi.org/10.1016/j.bbamem.2004.03.006
doi: 10.1016/j.bbamem.2004.03.006
Innomedica Talidox Brochure. https://relaunch.innomedica.com/wp-content/uploads/2021/04/Talidox.pdf . Accessed 4 Jan 2022
Hess D, Colombo I, Haefliger S et al (2020) 575P TLD-1, a novel liposomal doxorubicin, in patients (pts) with advanced solid tumours: dose escalation part of a multicenter open-label phase I trial (SAKK 65/16). Ann Oncol 31:S490. https://doi.org/10.1016/j.annonc.2020.08.689
doi: 10.1016/j.annonc.2020.08.689
Methaneethorn J, Tengcharoen K, Leelakanok N, AlEjielat R (2023) Population pharmacokinetics of doxorubicin: a systematic review. Asia Pac J Clin Oncol 19:9–26. https://doi.org/10.1111/ajco.13776
doi: 10.1111/ajco.13776
pubmed: 35415961
Wheeler GM, Mander AP, Bedding A et al (2019) How to design a dose-finding study using the continual reassessment method. BMC Med Res Methodol 19:1–15. https://doi.org/10.1186/s12874-018-0638-z
doi: 10.1186/s12874-018-0638-z
Garrett-Mayer E (2006) The continual reassessment method for dose-finding studies: a tutorial. Clin Trials 3:57–71. https://doi.org/10.1191/1740774506cn134oa
doi: 10.1191/1740774506cn134oa
pubmed: 16539090
Levey AS, Stevens LA, Schmid CH et al (2009) A new equation to estimate glomerular filtration rate. Ann Intern Med 150:604–612. https://doi.org/10.7326/0003-4819-150-9-200905050-00006
doi: 10.7326/0003-4819-150-9-200905050-00006
pubmed: 19414839
pmcid: 2763564
Janmahasatian S, Duffull SB, Ash S et al (2005) Quantification of lean bodyweight. Clin Pharmacokinet 44:1051–1065. https://doi.org/10.2165/00003088-200544100-00004
doi: 10.2165/00003088-200544100-00004
pubmed: 16176118
R Core Team (2022) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.r-project.org/.
Calvo E, Zafar H, Goetz A et al (2005) Analysis of dose proportionality testing methods in phase I clinical trials of anticancer agents. Cancer Res 65:973–974
Owen JS, Fiedler-Kelly J (2014) Introduction to population pharmacokinetic/pharmacodynamic analysis with nonlinear mixed effects models, 1st edn. John Wiley and Sons Ltd, Hoboken
doi: 10.1002/9781118784860
Mould DR, Upton RN (2013) Basic concepts in population modeling, simulation, and model-based drug development–part 2: introduction to pharmacokinetic modeling methods. CPT Pharmacometrics Syst Pharmacol 2:e38. https://doi.org/10.1038/psp.2013.14
doi: 10.1038/psp.2013.14
pubmed: 23887688
pmcid: 3636497
Dosne AG, Bergstrand M, Karlsson MO (2017) An automated sampling importance resampling procedure for estimating parameter uncertainty. J Pharmacokinet Pharmacodyn 44:509–520. https://doi.org/10.1007/s10928-017-9542-0
doi: 10.1007/s10928-017-9542-0
pubmed: 28887735
pmcid: 5686280
Dosne AG, Bergstrand M, Harling K, Karlsson MO (2016) Improving the estimation of parameter uncertainty distributions in nonlinear mixed effects models using sampling importance resampling. J Pharmacokinet Pharmacodyn 43:583–596. https://doi.org/10.1007/s10928-016-9487-8
doi: 10.1007/s10928-016-9487-8
pubmed: 27730482
pmcid: 5110709
Dosne AG, Niebecker R, Karlsson MO (2016) dOFV distributions: a new diagnostic for the adequacy of parameter uncertainty in nonlinear mixed-effects models applied to the bootstrap. J Pharmacokinet Pharmacodyn 43:597–608. https://doi.org/10.1007/s10928-016-9496-7
doi: 10.1007/s10928-016-9496-7
pubmed: 27730481
pmcid: 5110608
Broeker A, Wicha SG (2020) Assessing parameter uncertainty in small-n pharmacometric analyses: value of the log-likelihood profiling-based sampling importance resampling (LLP-SIR) technique. J Pharmacokinet Pharmacodyn 47:219–228. https://doi.org/10.1007/s10928-020-09682-4
doi: 10.1007/s10928-020-09682-4
pubmed: 32248328
pmcid: 7289778
Harashima H, Tsuchihashi M, Iida S et al (1999) Pharmacokinetic/pharmacodynamic modeling of antitumor agents encapsulated into liposomes. Adv Drug Deliv Rev 40:39–61. https://doi.org/10.1016/S0169-409X(99)00039-3
doi: 10.1016/S0169-409X(99)00039-3
pubmed: 10837779
Hsu L (2018) Investigation of the discriminatory ability of pharmacokinetic metrics for the bioequivalence assessment of PEGylated liposomal doxorubicin. Pharm Res 35:106. https://doi.org/10.1007/s11095-018-2387-4
doi: 10.1007/s11095-018-2387-4
pubmed: 29564719
Völler S, Boos J, Krischke M et al (2015) Age-dependent pharmacokinetics of doxorubicin in children with cancer. Clin Pharmacokinet 54:1139–1149. https://doi.org/10.1007/s40262-015-0272-4
doi: 10.1007/s40262-015-0272-4
pubmed: 25925711
Kontny NE, Würthwein G, Joachim B et al (2013) Population pharmacokinetics of doxorubicin: establishment of a NONMEM model for adults and children older than 3 years. Cancer Chemother Pharmacol 71:749–763. https://doi.org/10.1007/s00280-013-2069-1
doi: 10.1007/s00280-013-2069-1
pubmed: 23314734
García MJ, FernándezdeGatta MD, Martín A et al (2016) Population pharmacokinetics of doxorubicin and doxorubicinol in patients diagnosed with non-Hodgkin’s lymphoma. Br J Clin Pharmacol 82:1517–1527. https://doi.org/10.1111/bcp.13070
doi: 10.1111/bcp.13070
pubmed: 27447545
pmcid: 5099548
Bonate PL, Strougo A, Desai A et al (2012) Guidelines for the quality control of population pharmacokinetic–pharmacodynamic analyses: an industry perspective. AAPS J 14:749–758. https://doi.org/10.1208/s12248-012-9387-9
doi: 10.1208/s12248-012-9387-9
pubmed: 22826033
pmcid: 3475847
Joerger M, Huitema ADR, Richel DJ et al (2007) Population pharmacokinetics and pharmacodynamics of doxorubicin and cyclophosphamide in breast cancer patients. Clin Pharmacokinet 46:1051–1068. https://doi.org/10.2165/00003088-200746120-00005
doi: 10.2165/00003088-200746120-00005
pubmed: 18027989
Jonsson EN, Karlsson MO (1998) Automated covariate model building within NONMEM. Pharm Res 15:1463–1468
doi: 10.1023/A:1011970125687
pubmed: 9755901
Bergstrand M, Hooker AC, Wallin JE, Karlsson MO (2011) Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models. AAPS J 13:143–151. https://doi.org/10.1208/s12248-011-9255-z
doi: 10.1208/s12248-011-9255-z
pubmed: 21302010
pmcid: 3085712
Xu G, Yang D, He C et al (2023) Population pharmacokinetics and toxicity correlation analysis of free and liposome-encapsulated doxorubicin in Chinese patients with advanced breast cancer. Cancer Chemother Pharmacol 92:181–192. https://doi.org/10.1007/s00280-023-04559-y
doi: 10.1007/s00280-023-04559-y
pubmed: 37378676
Gabizon AA, Tahover E, Golan T et al (2020) Pharmacokinetics of mitomycin-c lipidic prodrug entrapped in liposomes and clinical correlations in metastatic colorectal cancer patients. Invest New Drugs 38:1411–1420. https://doi.org/10.1007/s10637-020-00897-3
doi: 10.1007/s10637-020-00897-3
pubmed: 31955309
Colombo I, Koster KL, Holer L et al (2024) TLD-1, a novel liposomal doxorubicin, in patients with advanced solid tumors: dose escalation and expansion part of a multicenter open-label phase I trial (SAKK 65/16). Eur J Cancer 201:113588. https://doi.org/10.1016/j.ejca.2024.113588
doi: 10.1016/j.ejca.2024.113588
pubmed: 38377773
Kluwe F, Michelet R, Mueller-Schoell A et al (2021) Perspectives on model-informed precision dosing in the digital health era: challenges, opportunities, and recommendations. Clin Pharmacol Ther 109:29–36. https://doi.org/10.1002/cpt.2049
doi: 10.1002/cpt.2049
pubmed: 33068303