Quantitative Systems Pharmacology (QSP) Analysis of Medicinal Mechanisms for Heart and Kidney Function Enhancement, and Optimal Dosage Strategies for Odronextamab in B-NHL Patients
DOI:
https://doi.org/10.52783/jns.v14.2251Keywords:
Quantitative Systems Pharmacology (QSP), Medication Mechanisms, Odronextamab Dosing, Clinical ImplicationsAbstract
This study investigates the mechanisms of medications impacting heart and kidney function and optimizes dosing strategies for Odronextamab. Utilizing secondary source data and a comprehensive Quantitative systems pharmacology (QSP), the research unveils hidden salt loss mechanisms, explores medication impacts on cardiovascular health, and recommends a personalized dosing regimen for Odronextamab. Validation against real-world data ensures the model's accuracy. Clinical implications emphasize the model's role in understanding drug safety and efficacy, providing guidance for B-NHL patients.
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Helmlinger, G. et al. (2019) Quantitative Systems Pharmacology: An Exemplar Model‐Building Workflow With Applications in Cardiovascular, Metabolic, and Oncology Drug Development. CPT: Pharmacokinetics & Systems Pharmacology, 8(6).
Masuda, T. et al. (2020) Osmotic diuresis by SGLT2 inhibition stimulates vasopressin-induced water reabsorption to maintain body fluid volume. Physiological Reports, 8(2).
Fioretto, P., Zambon, A., Rossato, M., Busetto, L. & Vettor, R. (2016) SGLT2 Inhibitors and the Diabetic Kidney. Diabetes Care, 39.
Boran, A. D. W. & Iyengar, R. (2011) Systems Pharmacology. Mount Sinai Journal of Medicine, 77(4). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3113679/
Danhof, M., Lange, E. C. M., Pasqua, O. E. D., Ploeger, B. A. & Voskuyl, R. A. (2008) Mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) modeling in translational drug research. Trends in pharmacological sciences, 29(4).
Miller, W. L. (2016) Fluid Volume Overload and Congestion in Heart Failure. Circulation: Heart Failure, 9(8).
VM, Biasetti L, Veroli Di JG, Almarza PC, Kimko H et al. Quantitative systems modeling approaches towards model-informed drug development: perspective through case studies research square. 2022;1:1-21.
Bradshaw EL, Spilker ME, Zang R, Bansal L, He H, Jones RDO et al. Applications of quantitative systems pharmacology in model-informed drug discovery: perspective on impact and opportunities. CPT Pharmacometrics Syst Pharmacol. 2019;8(11):777-91. doi: 10.1002/psp4.12463, PMID 31535440.
Loewe L, Hillston J. Computational models in systems biology. Genome Biol. 2008;9(12):328. doi: 10.1186/gb-2008-9-12-328, PMID 19090975.
Nijsen MJMA, Wu F, Bansal L, Bradshaw-Pierce E, Chan JR, Liederer BM et al. Preclinical QSP modeling in the pharmaceutical industry. An IQ consortium survey examining the current landscape. CPT Pharmacometrics Syst Pharmacol. 2018;7(3):135-46. doi: 10.1002/psp4.12282, PMID 29349875.
Gadkar K, Kirouac DC, Mager DE, van der Graaf PH, Ramanujan S. A six-stage workflow for robust application of systems pharmacology. CPT Pharmacometrics Syst Pharmacol. 2016;5(5):235-49. doi: 10.1002/psp4.12071, PMID 27299936.
Friedrich CM. A model qualification method for mechanistic physiological QSP models to support model-informed drug development. CPT Pharmacometrics Syst Pharmacol. 2016;5(2):43-53. doi: 10.1002/psp4.12056, PMID 26933515.
Gadkar K, Kirouac D, Parrott N, Ramanujan S. Quantitative systems pharmacology: a promising approach for translational pharmacology. Drug Discov Today Technol. 2016;21-22:57-65. doi: 10.1016/j.ddtec.2016.11.001, PMID 27978989.
Van der Graaf PH, Benson N. Systems pharmacology: bridging systems biology and pharmacokinetics pharmacodynamics (PKPD) in drug discovery and development. Pharm Res. 2011;28(7):1460-64. doi: 10.1007/s11095-011-0467-9, PMID 21560018.
Leil TA, Bertz R. Quantitative systems pharmacology can reduce attrition and improve productivity in pharmaceutical research and development. Front Pharmacol. 2014;5:247. doi: 10.3389/fphar.2014.00247, PMID 25426074.
Rao, Hartmanshenn C, Bae SA, Androulakis IP. On the analysis of complex biological supply chains: from process systems engineering to quantitative systems pharmacology. R.T., Scherholz, M. L. Comput Chem Eng. 2017;107:100-10.
Ribba B, Grimm HP, Agoram B, Davies MR, Gadkar K, Niederer S et al. Methodologies for quantitative systems pharmacology (QSP) models: design and estimation. CPT Pharmacometr Syst Pharmacol. 2017;6: 496–498:20.
Timmis J, Alden K, Andrews P, Clark E, Nellis A, Naylor B et al. Building confidence in quantitative systems pharmacology models: an engineer’s guide to exploring the rationale in model design and development. CPT Pharmacometrics Syst Pharmacol. 2017;6(3):156-67. doi: 10.1002/psp4.12157, PMID 27863172.
PLOS is a nonprofit publisher of open-access journals in science, technology, and medicine, and other scientific literature, under an open-content license. It was founded in 2000 and launched its first journal, Biology PLOS. In: October 2003.
Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0183794
Rogers M, Lyster P, Okita R. NIH support for the emergence of quantitative and systems pharmacology. CPT Pharmacometrics Syst Pharmacol. 2013;2(4):e37. doi: 10.1038/psp.2013.13, PMID 23887687.
Wist AD, Berger SI, Iyengar R. Systems pharmacology and genome medicine: a future perspective. Genome Med. 2009;1(1):11. doi: 10.1186/gm11, PMID 19348698.
Zhou W, Wang Y, Lu A, Zhang G. Systems pharmacology in small molecule drug discovery. Int J Mol Sci. 2016;17(2):246. doi: 10.3390/ijms17020246, PMID 26901192.
Gu J, Zhang X, Ma Y, Li N, Luo F, Cao L, et al. Quantitative modeling of dose-response and drug combination based on pathway network. J Cheminform. 2015;7:19. doi: 10.1186/s13321-015-0066-6, PMID 26101547.
Spiros A, Roberts P, Geerts H. A computer-based quantitative systems pharmacology model of negative symptoms in schizophrenia: exploring glycine modulation of excitation inhibition balance. Front Pharmacol. 2014;5:229. doi: 10.3389/fphar.2014.00229, PMID 25374541.
Fang J, Wu Z, Cai C, Wang Q, Tang Y, Cheng F. Quantitative and systems pharmacology. 1. In silico prediction of drug-target interactions of natural products enables new targeted cancer therapy. J Chem Inf Model. 2017;57(11):2657-71. doi: 10.1021/acs.jcim.7b00216, PMID 28956927.
Fleisher B, Brown AN, Ait-Oudhia S. Application of pharmacometrics and quantitative systems pharmacology to cancer therapy: the example of luminal a breast cancer. Pharmacol Res. 2017;124:20-33. doi: 10.1016/j.phrs.2017.07.015, PMID 28735000.
Chen B, Dong JQ, Pan WJ, Ruiz A. Pharmacokinetics/pharmacodynamics model-supported early drug development. Curr Pharm Biotechnol. 2012;13(7):1360-75. doi: 10.2174/138920112800624436, PMID 22201585.
Lave T et al. Translational PK/PD modeling to increase the probability of success in drug discovery and early development. Drug Discov Today Technol. 2016:21-2, 27-34.
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