Beyond Population-Level Targets for Drug Concentrations: Precision Dosing Needs Individual-Level Targets that Include Superior Biomarkers of Drug Responses.
Journal
Clinical pharmacology and therapeutics
ISSN: 1532-6535
Titre abrégé: Clin Pharmacol Ther
Pays: United States
ID NLM: 0372741
Informations de publication
Date de publication:
08 Feb 2024
08 Feb 2024
Historique:
received:
05
11
2023
accepted:
17
01
2024
medline:
8
2
2024
pubmed:
8
2
2024
entrez:
8
2
2024
Statut:
aheadofprint
Résumé
The purpose of precision dosing is to increase the chances of therapeutic success in individual patients. This is achieved in practice by adjusting doses to reach precision dosing targets determined previously in relevant populations, ideally with robust supportive evidence showing improved clinical outcomes compared with standard dosing. But is this implicit assumption of translatable population-level precision dosing targets correct and the best for all patients? In this review, the types of precision dosing targets and how they are determined are outlined, problems with the translatability of these targets to individual patients are identified, and ways forward to address these challengers are proposed. Achieving improved clinical outcomes to support precision dosing over standard dosing is currently hampered by applying population-level targets to all patients. Just as "one-dose-fits-all" may be an inappropriate philosophy for drug treatment overall, a "one-target-fits-all" philosophy may limit the broad clinical benefits of precision dosing. Defining individual-level precision dosing targets may be needed for greatest therapeutic success. Superior future precision dosing targets will integrate several biomarkers that together account for the multiple sources of drug response variability.
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.
Références
Polasek, T.M., Shakib, S. & Rostami-Hodjegan, A. Precision dosing in clinical medicine: present and future. Expert. Rev. Clin. Pharmacol. 11, 743-746 (2018).
Collins, F.S. & Varmus, H. A new initiative on precision medicine. N. Engl. J. Med. 372, 793-795 (2015).
Winship, I. Precision medicine: are we there? Med. J. Aust. 203, 132-133.e1 (2015).
Hawcutt, D.B., Cooney, L., Oni, L. & Pirmohamed, M. Precision dosing in children. Exp. Rev. Precision Med. Drug Develop. 1, 69-78 (2016).
Wicha, S.G., Martson, A.G., Nielsen, E.I. et al. From therapeutic drug monitoring to model-informed precision dosing for antibiotics. Clin. Pharmacol. Ther. 109, 928-941 (2021).
Hilmer, S.N., McLachlan, A.J. & Le Couteur, D.G. Clinical pharmacology in the geriatric patient. Fundam. Clin. Pharmacol. 21, 217-230 (2007).
Lucas, C.J. & Martin, J.H. Pharmacokinetic-guided dosing of new Oral cancer agents. J. Clin. Pharmacol. 57(Suppl 10), S78-S98 (2017).
Gonzalez, D. et al. Precision dosing: public health need, proposed framework, and anticipated impact. Clin. Transl. Sci. 10, 443-454 (2017).
Darwich, A.S. et al. Model-informed precision dosing: background, requirements, validation, implementation, and forward trajectory of individualizing drug therapy. Annu. Rev. Pharmacol. Toxicol. 61, 225-245 (2021).
Darwich, A.S. et al. Why has model-informed precision dosing not yet become common clinical reality? Lessons from the past and a roadmap for the future. Clin. Pharmacol. Ther. 101, 646-656 (2017).
Polasek, T.M. et al. What does it take to make model-informed precision dosing common practice? Report from the 1st Asian symposium on precision dosing. AAPS J. 21, 17 (2019).
Maxfield, K. et al. Proceedings of a workshop: precision dosing: defining the need and approaches to deliver individualized drug dosing in the real-world setting. Clin. Pharmacol. Ther. 109, 25-28 (2021).
Peck, R.W., Shahin, M.H. & Vinks, A.A. Precision dosing: the clinical pharmacology of goldilocks. Clin. Pharmacol. Ther. 109, 11-14 (2021).
Angehrn, Z. et al. Artificial intelligence and machine learning applied at the point of care. Front. Pharmacol. 11, 759 (2020).
Neely, M.N. Editorial: in memory of Roger Jelliffe, MD. Ther. Drug Monit. 43, 459-460 (2021).
Maxfield, K. & Zineh, I. Precision dosing: A clinical and public health imperative. JAMA 325, 1505-1506 (2021).
Tyson, R.J. et al. Precision dosing priority criteria: drug, disease, and patient population variables. Front. Pharmacol. 11, 420 (2020).
Wright, D.F.B., Martin, J.H. & Cremers, S. Spotlight commentary: model-informed precision dosing must demonstrate improved patient outcomes. Br. J. Clin. Pharmacol. 85, 2238-2240 (2019).
Peck, R.W. Precision medicine is not just genomics: the right dose for every patient. Annu. Rev. Pharmacol. Toxicol. 58, 105-122 (2018).
Johnson, J.A. & Cavallari, L.H. Warfarin pharmacogenetics. Trends Cardiovasc. Med. 25, 33-41 (2015).
Mostafa, S. et al. Delineating gene-environment effects using virtual twins of patients treated with clozapine. CPT Pharmacometrics Syst. Pharmacol. 12, 168-179 (2023).
Fendt, R. et al. Data-driven personalization of a physiologically based pharmacokinetic model for caffeine: a systematic assessment. CPT Pharmacometrics Syst. Pharmacol. 10, 782-793 (2021).
Keeling, D. et al. Guidelines on oral anticoagulation with warfarin - fourth edition. Br. J. Haematol. 154, 311-324 (2011).
Levy, G. Predicting effective drug concentrations for individual patients: determinants of pharmacodynamic variability. Clin. Pharmacokinet. 34, 323-333 (1998).
Levy, G. Impact of pharmacodynamic variability on drug delivery. Adv. Drug Deliv. Rev. 33, 201-206 (1998).
Pavord, I.D. et al. Mepolizumab for severe eosinophilic asthma (DREAM): a multicentre, double-blind, placebo-controlled trial. Lancet 380, 651-659 (2012).
Combes, F.P., Li, Y.F., Hoch, M., Lorenzo, S., Ho, Y.Y. & Sy, S.K.B. Exposure-efficacy analysis of Asciminib in Philadelphia chromosome-positive chronic myeloid leukemia in chronic phase. Clin. Pharmacol. Ther. 112, 1040-1050 (2022).
Santini, C., Schindler, E., Attig, J. et al. (eds.). Development of a quantitative systems pharmacology model for clinical dose and schedule optimization of forimtamig, a T cell engaging antibody targeting GPRC5D in multiple myeloma. American Association for Cancer Research Annual Meeting 2023; Orlando, Florida, USA (2023).
de Witte, C.J. et al. Patient-derived ovarian cancer organoids mimic clinical response and exhibit heterogeneous inter- and Intrapatient drug responses. Cell Rep. 31, 107762 (2020).
Barnes, K.J., Rowland, A., Polasek, T.M. & Miners, J.O. Inhibition of human drug-metabolising cytochrome P450 and UDP-glucuronosyltransferase enzyme activities in vitro by uremic toxins. Eur. J. Clin. Pharmacol. 70, 1097-1106 (2014).
Wilcox, C.S., Testani, J.M. & Pitt, B. Pathophysiology of diuretic resistance and its implications for the management of chronic heart failure. Hypertension 76, 1045-1054 (2020).
Gaedigk, A., Dinh, J.C., Jeong, H., Prasad, B. & Leeder, J. Ten Years' experience with the CYP2D6 activity score: a perspective on future investigations to improve clinical predictions for precision therapeutics. J. Pers. Med. 8, 15 (2018).
Webster, A. Transgender individuals deserve compassionate, personalized care: A transgender patient perspective. Clin. Pharmacol. Ther. 113, 480-482 (2023).
Polasek, T.M., Patel, F., Jensen, B.P., Sorich, M.J., Wiese, M.D. & Doogue, M.P. Predicted metabolic drug clearance with increasing adult age. Br. J. Clin. Pharmacol. 75, 1019-1028 (2013).
Bespalov, A., Muller, R., Relo, A.L. & Hudzik, T. Drug tolerance: A known unknown in translational neuroscience. Trends Pharmacol. Sci. 37, 364-378 (2016).
Osteberg, L. & Blaschke, T. Adherence to medication. N. Engl. J. Med. 353, 487-497 (2005).
Assawasuwannakit, P., Braund, R. & Duffull, S.B. Quantification of the forgiveness of drugs to imperfect adherence. CPT Pharmacometrics Syst. Pharmacol. 4, e00004 (2015).
Polasek, T.M. Calculation of the pharmacogenomics benefit score for patients with medication-related problems. Front. Genet. 14, 1152585 (2023).
Keizer, R.J., Ter Heine, R., Frymoyer, A. et al. Model-informed precision dosing at the bedside: scientific challenges and opportunities. CPT Pharmacometrics Syst. Pharmacol. 7, 785-787 (2018).
Hiemke, C. et al. Consensus guidelines for therapeutic drug monitoring in neuropsychopharmacology: update 2017. Pharmacopsychiatry 51, 9-62 (2018).
Hopkins, A.M. et al. Nuances to precision dosing strategies of targeted cancer medicines. Pharmacol. Res. Perspect. 8, e00625 (2020).
Holford, N., Ma, G. & Metz, D. TDM is dead. Long live TCI! Br. J. Clin. Pharmacol. 88, 1406-1413 (2022).
Abdel-Rahman, S.M., Casey, K.L., Garg, U. & Dalal, J. Intravenous busulfan dose individualization - impact of modeling approach on dose recommendation. Pediatr. Transplant. 20, 443-448 (2016).
Le Meur, Y., Buchler, M., Thierry, A. et al. Individualized mycophenolate mofetil dosing based on drug exposure significantly improves patient outcomes after renal transplantation. Am. J. Transplant. 7, 2496-2503 (2007).
Rayner, C.R. et al. Model-informed drug development for anti-infectives: state of the art and future. Clin. Pharmacol. Ther. 109, 867-891 (2021).
Hochhaus, A. et al. Long-term outcomes of imatinib treatment for chronic myeloid leukemia. N. Engl. J. Med. 376, 917-927 (2017).
Nelson, E.C., Eftimovska, E., Lind, C., Hager, A., Wasson, J.H. & Lindblad, S. Patient reported outcome measures in practice. BMJ 350, g7818 (2015).
Wilbaux, M. et al. Integration of pharmacokinetics, pharmacodynamics, safety, and efficacy into model-informed dose selection in oncology first-in-human study: a case of Roblitinib (FGF401). Clin. Pharmacol. Ther. 112, 1329-1339 (2022).
Ryeznik, Y., Sverdlov, O., Svensson, E.M., Montepiedra, G., Hooker, A.C. & Wong, W.K. Pharmacometrics meets statistics-A synergy for modern drug development. CPT Pharmacometrics Syst. Pharmacol. 10, 1134-1149 (2021).
Hennig, S. et al. Pharmacometrics in Australasia-twenty years of population approach Group of Australia and New Zealand. CPT Pharmacometrics Syst. Pharmacol. 8, 701-704 (2019).
Lesko, L.J. Perspective on model-informed drug development. CPT Pharmacometrics Syst. Pharmacol. 10, 1127-1129 (2021).
Mahmood, S.S., Levy, D., Vasan, R.S. & Wang, T.J. The Framingham heart study and the epidemiology of cardiovascular disease: a historical perspective. Lancet 383, 999-1008 (2014).
Ismail-Beigi, F., Moghissi, E., Tiktin, M., Hirsch, I.B., Inzucchi, S.E. & Genuth, S. Individualizing glycemic targets in type 2 diabetes mellitus: implications of recent clinical trials. Ann. Intern. Med. 154, 554-559 (2011).
Molden, E. Therapeutic drug monitoring of clozapine in adults with schizophrenia: a review of challenges and strategies. Expert Opin. Drug Metab. Toxicol. 17, 1211-1221 (2021).
Peck, R.W. The right dose for every patient: a key step for precision medicine. Nat. Rev. Drug Discov. 15, 145-146 (2016).
Mukherjee, A. et al. Exposure-response characterization of tofacitinib efficacy in moderate to severe ulcerative colitis: results from phase II and phase III induction and maintenance studies. Clin. Pharmacol. Ther. 112, 90-100 (2022).
Colloca, L. et al. Predicting treatment responses in patients with osteoarthritis: results from two phase III tanezumab randomized clinical trials. Clin. Pharmacol. Ther. 113, 878-886 (2023).
Patil, V.M. et al. Low-dose immunotherapy in head and neck cancer: a randomized study. J. Clin. Oncol. 41, 222-232 (2023).
Ribba, B., Roller, A., Helms, H.J. et al. Circulating tumor DNA: opportunities and challenges for pharmacometric approaches. Front. Pharmacol. 13, 1058220 (2022).
Assaf, Z.J.F. et al. A longitudinal circulating tumor DNA-based model associated with survival in metastatic non-small-cell lung cancer. Nat. Med. 29, 859-868 (2023).
Anagnostou, V. et al. ctDNA response after pembrolizumab in non-small cell lung cancer: phase 2 adaptive trial results. Nat. Med. 29, 2559-2569 (2023).
Doogue, M.P. & Polasek, T.M. Drug dosing in renal disease. Clin. Biochem. Rev. 32, 69-73 (2011).
Tadros, R. & Shakib, S. Warfarin: indications, risks and drug interactions. Aust. Fam. Physician 39, 476-479 (2010).
Nimmo, A.F. et al. Guidelines for the safe practice of total intravenous anaesthesia (TIVA): joint guidelines from the Association of Anaesthetists and the Society for Intravenous Anaesthesia. Anaesthesia 74, 211-224 (2019).
Bressler, B. & Steinhart, A.H. Has the time come to say goodbye to therapeutic drug monitoring as we know it? Gastroenterology 162, 1831-1832 (2022).
Peñas-LLedó, E. & Lerena, A. Clinical use of pre-emptive pharmacogenetic programmes. Lancet 401, 320-321 (2023).
Argyriou, A.A., Iconomou, G. & Kalofonos, H.P. Bortezomib-induced peripheral neuropathy in multiple myeloma: a comprehensive review of the literature. Blood 112, 1593-1599 (2008).
Peck, R.W. Precision dosing: an industry perspective. Clin. Pharmacol. Ther. 109, 47-50 (2021).
Wykoff, C.C. et al. Efficacy, durability, and safety of intravitreal faricimab with extended dosing up to every 16 weeks in patients with diabetic macular oedema (YOSEMITE and RHINE): two randomised, double-masked, phase 3 trials. Lancet 399, 741-755 (2022).
Heier, J.S. et al. Efficacy, durability, and safety of intravitreal faricimab up to every 16 weeks for neovascular age-related macular degeneration (TENAYA and LUCERNE): two randomised, double-masked, phase 3, non-inferiority trials. Lancet 399, 729-740 (2022).
Grahnén, A. & Karlsson, M.O. Concentration-controlled or effect-controlled trials: useful alternatives to conventional dose-controlled trials? Clin. Pharmacokinet. 40, 317-325 (2001).
Shah, M., Rahman, A., Theoret, M.R. & Pazdur, R. The drug-dosing conundrum in oncology - when less is more. N. Engl. J. Med. 385, 1445-1447 (2021).
US Food and Drug Administration. Diversity plans to improve enrollment of participants from underrepresented racial and ethnic populations in clinical trials guidance for industry; draft guidance. (2022).
Powell, J.R., Cook, J., Wang, Y., Peck, R. & Weiner, D. Drug dosing recommendations for all patients: a roadmap for change. Clin. Pharmacol. Ther. 109, 65-72 (2021).
Dennis, J.M. et al. Development of a treatment selection algorithm for SGLT2 and DPP-4 inhibitor therapies in people with type 2 diabetes: a retrospective cohort study. Lancet Digit Health. 4, e873-e883 (2022).
Shields, B.M. et al. Patient stratification for determining optimal second-line and third-line therapy for type 2 diabetes: the TriMaster study. Nat. Med. 29, 376-383 (2023).
Barbieri, C. et al. How to assess the risks associated with the usage of a medical device based on predictive modeling: the case of an anemia control model certified as medical device. Expert Rev. Med. Devices 18, 1117-1121 (2021).
Tie, J. et al. Circulating tumor DNA analysis guiding adjuvant therapy in stage II colon cancer. N. Engl. J. Med. 386, 2261-2272 (2022).
Wijnsma, K.L., Ter Heine, R., Moes, D. et al. Pharmacology, pharmacokinetics and pharmacodynamics of eculizumab, and possibilities for an individualized approach to eculizumab. Clin. Pharmacokinet. 58, 859-874 (2019).
Volokhina, E. et al. Eculizumab dosing regimen in atypical HUS: possibilities for individualized treatment. Clin. Pharmacol. Ther. 102, 671-678 (2017).
Bouwmeester, R.N. et al. Early eculizumab withdrawal in patients with atypical hemolytic uremic syndrome in native kidneys is safe and cost-effective: results of the CUREiHUS study. Kidney Int. Rep. 8, 91-102 (2023).
Gaweda, A.E., Lederer, E.D. & Brier, M.E. Artificial intelligence-guided precision treatment of chronic kidney disease-mineral bone disorder. CPT Pharmacometrics Syst. Pharmacol. 11, 1305-1315 (2022).
Yauney, G. & Shah, P. Reinforcement learning with action-derived rewards for chemotherapy and clinical trial dosing regimen selection. Proc. Mach. Learn. Res. 85, 1-49 (2018).
Qian, Z., Zame, W., Fleuren, L. et al. Integrating expert ODEs into neural ODEs: pharmacology and disease progression. Adv. Neural Inf. Proces. Syst. 34, 11364-11383 (2021).