{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T12:04:08Z","timestamp":1788437048898,"version":"build-2803163510"},"reference-count":105,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T00:00:00Z","timestamp":1761868800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JPM"],"abstract":"<jats:p>Cancer therapy is rapidly evolving from a one-size-fits-all paradigm toward highly personalized approaches. Traditional chemotherapies and radiotherapies, while broadly applied, often yield suboptimal outcomes due to tumor heterogeneity and are limited by significant toxicities. In contrast, precision oncology tailors prevention, diagnosis, and treatment to the individual patient\u2019s genetic and molecular profile. Key advancements underscore this shift: molecularly targeted drugs (e.g., trastuzumab for HER2-positive breast cancer, EGFR and ALK inhibitors for lung cancer) have improved efficacy and reduced toxicity compared to conventional therapy. Pharmacokinetic (PK) and pharmacodynamic (PD) considerations are central to personalizing treatment, explaining variability in drug exposure and response among patients and guiding dose optimization. Modern strategies like therapeutic drug monitoring and model-informed precision dosing seek to maintain drug levels in the therapeutic range, improving outcomes. Immunotherapies, including checkpoint inhibitors and CAR-T cells, have transformed oncology, though patient selection via biomarkers (such as PD-L1 expression or tumor mutational burden) is critical to identify likely responders. Innovative drug delivery systems, notably nanomedicine, address PK challenges by enhancing tumor-specific drug accumulation and enabling novel therapeutics. Furthermore, rational combination regimens (informed by PK\/PD and tumor biology) are being designed to achieve synergistic efficacy and overcome resistance. Key barriers include the high cost of biomarker testing, insufficient laboratory infrastructure, and inconsistent reimbursement policies. Operational inefficiencies such as long turnaround times or lack of clinician awareness further limit the use of precision diagnostics. Regulatory processes also remain complex, particularly around the co-development of targeted drugs and companion diagnostics, and the evidentiary requirements for rare subgroups. Addressing these barriers will require harmonized policies, investment in infrastructure, and educational initiatives to ensure that the promise of personalized medicine becomes accessible to all patients. Ensuring that advances are implemented responsibly\u2014guided by pharmacological insights, supported by real-world evidence, and evaluated within ethical and economic frameworks\u2014will be critical to realizing the full potential of personalized cancer medicine.<\/jats:p>","DOI":"10.3390\/jpm15110516","type":"journal-article","created":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T17:32:01Z","timestamp":1762191121000},"page":"516","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["The Three Musketeers in Cancer Therapy: Pharmacokinetics, Pharmacodynamics and Personalised Approach"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7004-2239","authenticated-orcid":false,"given":"Milan","family":"Zari\u0107","sequence":"first","affiliation":[{"name":"Department of Biochemistry, Faculty of Medical Sciences, University of Kragujevac, Svetozara Markovi\u0107a 69, 34000 Kragujevac, Serbia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Petar","family":"\u010canovi\u0107","sequence":"additional","affiliation":[{"name":"Department of Biochemistry, Faculty of Medical Sciences, University of Kragujevac, Svetozara Markovi\u0107a 69, 34000 Kragujevac, Serbia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Radica","family":"\u017divkovi\u0107 Zari\u0107","sequence":"additional","affiliation":[{"name":"Department of Pharmacology and Toxicology, Faculty of Medical Sciences, University of Kragujevac, Svetozara Markovi\u0107a 69, 34000 Kragujevac, Serbia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simona","family":"Protrka","sequence":"additional","affiliation":[{"name":"Faculty of Medical Sciences, University of Kragujevac, Svetozara Markovi\u0107a 69, 34000 Kragujevac, Serbia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0890-8094","authenticated-orcid":false,"given":"Miona","family":"Gli\u0161i\u0107","sequence":"additional","affiliation":[{"name":"Department of Dentistry, Faculty of Medical Sciences, University of Kragujevac, Svetozara Markovi\u0107a 69, 34000 Kragujevac, Serbia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,31]]},"reference":[{"key":"ref_1","first-page":"229","article-title":"Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"74","author":"Bray","year":"2024","journal-title":"CA Cancer J. Clin."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Marques, L., Rodrigues, M., Silva, P., Rocha, J., Pereira, A., Oliveira, T., and Fernandes, R. (2024). Advancing precision medicine: A review of innovative in silico approaches for drug development, clinical pharmacology, and personalized healthcare. Pharmaceutics, 16.","DOI":"10.3390\/pharmaceutics16030332"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"104464","DOI":"10.1016\/j.critrevonc.2024.104464","article-title":"Precision oncology targeting FGFRs: A systematic review on pre-clinical activity and clinical outcomes of pemigatinib","volume":"202","author":"Gnagni","year":"2024","journal-title":"Crit. Rev. Oncol. Hematol."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Wang, R.C., and Wang, Z. (2023). Precision medicine: Disease subtyping and tailored treatment. Cancers, 15.","DOI":"10.3390\/cancers15153837"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1002\/psp4.12588","article-title":"Reinforcement learning and Bayesian data assimilation for model-informed precision dosing in oncology","volume":"10","author":"Maier","year":"2021","journal-title":"CPT Pharmacomet. Syst. Pharmacol."},{"key":"ref_6","first-page":"1123","article-title":"Towards AI-based precision oncology: Machine learning for personalized counterfactual treatment suggestions based on multi-omics data","volume":"6","author":"Boos","year":"2024","journal-title":"Nat. Mach. Intell."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Widmer, N., Guidi, M., and Buclin, T. (2024). Population pharmacokinetics in oncology and its clinical applications. Pharmaceutics, 16.","DOI":"10.3390\/pharmaceutics16060711"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1146\/annurev-pharmtox-033020-113257","article-title":"Model-informed precision dosing: Background, requirements, validation, implementation, and forward trajectory of individualizing drug therapy","volume":"61","author":"Darwich","year":"2021","journal-title":"Annu. Rev. Pharmacol. Toxicol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1038\/s41571-023-00824-4","article-title":"Molecular tumour boards\u2014Current and future considerations for precision oncology","volume":"20","author":"Tsimberidou","year":"2023","journal-title":"Nat. Rev. Clin. Oncol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"315","DOI":"10.2217\/pgs.12.213","article-title":"Pharmacogenetics and pharmacogenomics: A bridge to individualized cancer therapy","volume":"14","author":"Weng","year":"2013","journal-title":"Pharmacogenomics"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Chen, H.-H., Wu, Y.-J., and Wu, F.-Z. (2025). Precision medicine in lung cancer screening: A paradigm shift in early detection\u2014Precision screening for lung cancer. Diagnostics, 15.","DOI":"10.3390\/diagnostics15121562"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Mechahougui, H., Gutmans, J., Colarusso, G., Gouasmi, R., and Friedlaender, A. (2024). Advances in personalized oncology. Cancers, 16.","DOI":"10.3390\/cancers16162862"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Levantini, E. (2023). Novel therapeutic targets in cancers. Int. J. Mol. Sci., 24.","DOI":"10.3390\/ijms241914660"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"9","DOI":"10.6004\/jadpro.2023.14.3.16","article-title":"Biomarker-driven oncology clinical trials: Novel designs in the era of precision medicine","volume":"14","author":"Moore","year":"2023","journal-title":"J. Adv. Pract. Oncol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Ioele, G., Chieffallo, M., Occhiuzzi, M.A., De Luca, M., Garofalo, A., Ragno, G., and Grande, F. (2022). Anticancer drugs: Recent strategies to improve stability profile, pharmacokinetic and pharmacodynamic properties. Molecules, 27.","DOI":"10.3390\/molecules27175436"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Papachristos, A., Patel, J., Vasileiou, M., and Patrinos, G.P. (2023). Dose optimization in oncology drug development: The emerging role of pharmacogenomics, pharmacokinetics, and pharmacodynamics. Cancers, 15.","DOI":"10.3390\/cancers15123233"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.soc.2023.12.004","article-title":"Evolution of precision oncology, personalized medicine, and molecular tumor boards","volume":"33","author":"Fujiwara","year":"2024","journal-title":"Surg. Oncol. Clin. N. Am."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Sissung, T.M., and Figg, W.D. (2022). Pharmacogenomics testing in phase I oncology clinical trials: Constructive criticism is warranted. Cancers, 14.","DOI":"10.3390\/cancers14051131"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1016\/j.eururo.2015.04.018","article-title":"CYP3A5 and ABCB1 Polymorphisms as Predictors for Sunitinib Outcome in Metastatic Renal Cell Carcinoma","volume":"68","author":"Diekstra","year":"2015","journal-title":"Eur. Urol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.phrs.2018.02.005","article-title":"Impact of SLC22A1 and CYP3A5 Genotypes on Imatinib Response in Chronic Myeloid Leukemia: A Systematic Review and Meta-Analysis","volume":"131","author":"Cargnin","year":"2018","journal-title":"Pharmacol. Res."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Wu, X., and Xiong, H. (2024). The Role of Pharmacogenetic-Based Pharmacokinetic Analysis in Precise Breast Cancer Treatment. Pharmaceutics, 16.","DOI":"10.3390\/pharmaceutics16111407"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Suzumura, T., Kimura, T., Kudoh, S., Umekawa, K., Nagata, M., Matsuura, K., Tanaka, H., Mitsuoka, S., Yoshimura, N., and Kira, Y. (2012). Reduced CYP2D6 Function Is Associated with Gefitinib-Induced Rash in Patients with Non-Small Cell Lung Cancer. BMC Cancer, 12.","DOI":"10.1186\/1471-2407-12-568"},{"key":"ref_23","unstructured":"Pratt, V.M., Scott, S.A., Pirmohamed, M., Esquivel, B., and Kattman, B.L. (2025, September 14). Belinostat Therapy and UGT1A1 Genotype, Medical Genetics Summaries, Available online: https:\/\/www.ncbi.nlm.nih.gov\/books\/NBK593302\/."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Loscocco, F., Visani, G., Ruzzo, A., Bagaloni, I., Fuligni, F., Galimberti, S., Di Paolo, A., Stagno, F., Pregno, P., and Annunziata, M. (2021). Clinical Relevance of ABCB1, ABCG2, and ABCC2 Gene Polymorphisms in Chronic Myeloid Leukemia Patients Treated with Nilotinib. Front. Oncol., 11.","DOI":"10.3389\/fonc.2021.672287"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Rajamani, B.M., Benjamin, E.S.B., Abraham, A., Ganesan, S., Lakshmi, K.M., Anandan, S., Karathedath, S., Varatharajan, S., Mohanan, E., and Janet, N.B. (2020). Plasma Imatinib Levels and ABCB1 Polymorphism Influence Early Molecular Response and Failure-Free Survival in Newly Diagnosed Chronic Phase CML Patients. Sci. Rep., 10.","DOI":"10.1038\/s41598-020-77140-9"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"432","DOI":"10.4161\/cbt.6.3.3763","article-title":"Association of Variant ABCG2 and the Pharmacokinetics of Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Cancer Patients","volume":"6","author":"Li","year":"2007","journal-title":"Cancer Biol. Ther."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Zazo, H., Aguazul, Y., and Lanao, J.M. (2024). Dosing Evaluation of Ceftazidime\u2013Avibactam in Intensive Care Unit Patients Based on Pharmacokinetic\/Pharmacodynamic (PK\/PD) Modeling and Simulation. Antibiotics, 13.","DOI":"10.3390\/antibiotics13090861"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1007\/s12672-025-02198-8","article-title":"Advancements and limitations in traditional anti-cancer therapies: A comprehensive review of surgery, chemotherapy, radiation therapy, and hormonal therapy","volume":"16","author":"Zafar","year":"2025","journal-title":"Discov. Oncol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"11559","DOI":"10.18632\/oncotarget.24338","article-title":"5-FU Therapeutic Drug Monitoring as a Valuable Option to Reduce Toxicity in Patients with Gastrointestinal Cancer","volume":"9","author":"Morawska","year":"2018","journal-title":"Oncotarget"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"17588359241250130","DOI":"10.1177\/17588359241250130","article-title":"Therapeutic Drug Monitoring Guidelines in Oncology: What Do We Know and How to Move Forward? Insights from a Systematic Review","volume":"16","author":"Li","year":"2024","journal-title":"Ther. Adv. Med. Oncol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1007\/s00228-020-03014-8","article-title":"Therapeutic Drug Monitoring of Oral Targeted Antineoplastic Drugs","volume":"77","author":"Groenland","year":"2021","journal-title":"Eur. J. Clin. Pharmacol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3349\/ymj.2017.58.1.1","article-title":"A Review of Modeling Approaches to Predict Drug Response in Clinical Oncology","volume":"58","author":"Park","year":"2017","journal-title":"Yonsei Med. J."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1200\/EDBK_180460","article-title":"Pharmacokinetic\/Pharmacodynamic Modeling for Drug Development in Oncology","volume":"37","author":"Garralda","year":"2017","journal-title":"Am. Soc. Clin. Oncol. Educ. Book"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1333","DOI":"10.1007\/s40262-023-01293-9","article-title":"Therapeutic Drug Monitoring of Kinase Inhibitors in Oncology","volume":"62","author":"Guchelaar","year":"2023","journal-title":"Clin. Pharmacokinet."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez-Nava, C., Ortu\u00f1o-Pineda, C., Illades-Aguiar, B., Flores-Alfaro, E., Leyva-V\u00e1zquez, M.A., Parra-Rojas, I., del Moral-Hern\u00e1ndez, O., Vences-Vel\u00e1zquez, A., Cort\u00e9s-Sarabia, K., and Alarc\u00f3n-Romero, L.d.C. (2023). Mechanisms of Action and Limitations of Monoclonal Antibodies and Single Chain Fragment Variable (scFv) in the Treatment of Cancer. Biomedicines, 11.","DOI":"10.3390\/biomedicines11061610"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zahavi, D., and Weiner, L. (2020). Monoclonal Antibodies in Cancer Therapy. Antibodies, 9.","DOI":"10.3390\/antib9030034"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1038\/s41416-024-02789-2","article-title":"Reasons for non-feasibility of therapeutic drug monitoring of oral targeted therapies in oncology\u2014An analysis of a multicentre prospective study","volume":"131","author":"Guchelaar","year":"2024","journal-title":"Br. J. Cancer"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Kumar, M., Lanke, S., Yadav, A., Patel, M., Sharma, V., Singh, A., and Choudhary, A. (2024). Inter-antibody variability in the clinical pharmacokinetics of monoclonal antibodies characterized using population PBPK modeling. Antibodies, 13.","DOI":"10.3390\/antib13030054"},{"key":"ref_39","first-page":"e61983","article-title":"A Comprehensive Review of Monoclonal Antibodies in Modern Medicine: Tracing the Evolution of a Revolutionary Therapeutic Approach","volume":"16","author":"Kothari","year":"2024","journal-title":"Cureus"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1038\/s41408-021-00459-7","article-title":"CAR-T Cell Therapy: Current Limitations and Potential Strategies","volume":"11","author":"Sterner","year":"2021","journal-title":"Blood Cancer J."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2349796","DOI":"10.1080\/07853890.2024.2349796","article-title":"Comprehensive Analysis of the Efficacy and Safety of CAR T-Cell Therapy in Patients with Relapsed or Refractory B-Cell Acute Lymphoblastic Leukaemia: A Systematic Review and Meta-Analysis","volume":"56","author":"Willyanto","year":"2024","journal-title":"Ann. Med."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Jiang, M., and Hu, Y. (2022). Dosing regimens of immune checkpoint inhibitors: Attempts at lower dose, less frequency, shorter course. Front. Oncol., 12.","DOI":"10.3389\/fonc.2022.906251"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Le Louedec, F., Leenhardt, F., Marin, C., Vassal, G., and Chatelut, E. (2020). Cancer immunotherapy dosing: A pharmacokinetic\/pharmacodynamic perspective. Vaccines, 8.","DOI":"10.3390\/vaccines8040632"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Jian, J., He, D., Gao, S., Tao, X., and Dong, X. (2023). Pharmacokinetics in pharmacometabolomics: Towards personalized medication. Pharmaceuticals, 16.","DOI":"10.3390\/ph16111568"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Gambardella, V., Tarazona, N., Cejalvo, J.M., Lombardi, P., Huerta, M., Rosell\u00f3, S., Fleitas, T., Roda, D., and Cervantes, A. (2020). Personalized medicine: Recent progress in cancer therapy. Cancers, 12.","DOI":"10.3390\/cancers12041009"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Jantararoungtong, T., Wiwattanakul, S., Tiyasirichokchai, R., Prommas, S., Sukprasong, R., Koomdee, N., Jinda, P., Rachanakul, J., Nuntharadthanaphong, N., and Pakakasama, S. (2021). TPMT*3C as a predictor of 6-mercaptopurine-induced myelotoxicity in Thai children with acute lymphoblastic leukemia. J. Pers. Med., 11.","DOI":"10.3390\/jpm11080783"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Dini\u0107, J., Jovanovi\u0107 Stojanov, S., Dragoj, M., Grozdani\u0107, M., Podolski-Reni\u0107, A., and Pe\u0161i\u0107, M. (2024). Cancer patient-derived cell-based models: Applications and challenges in functional precision medicine. Life, 14.","DOI":"10.3390\/life14091142"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Zettler, M.E. (2024). Dose optimization of targeted therapies for oncologic indications. Cancers, 16.","DOI":"10.3390\/cancers16122180"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Sankar, K., Ye, J.C., Li, Z., Guo, H., Lee, K., Zhang, Y., and Wong, S.T.C. (2022). The role of biomarkers in personalized immunotherapy. Biomark. Res., 10.","DOI":"10.1186\/s40364-022-00378-0"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Gottumukkala, S.B., Ganesan, T.S., and Palanisamy, A. (2024). Comprehensive molecular interaction map of TGF\u03b2 induced epithelial to mesenchymal transition in breast cancer. NPJ Syst. Biol. Appl., 10.","DOI":"10.1038\/s41540-024-00378-w"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1038\/s41392-023-01536-y","article-title":"Nanomedicine in cancer therapy","volume":"8","author":"Fan","year":"2023","journal-title":"Signal Transduct. Target. Ther."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Frieboes, H.B., Raghavan, S., and Godin, B. (2020). Modeling of Nanotherapy Response as a Function of the Tumor Microenvironment: Focus on Liver Metastasis. Front. Bioeng. Biotechnol., 8.","DOI":"10.3389\/fbioe.2020.01011"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1146\/annurev-cancerbio-061421-020411","article-title":"Rationales for combining therapies to treat cancer: Independent action, response correlation, and collateral sensitivity versus synergy","volume":"7","author":"Schmidt","year":"2023","journal-title":"Annu. Rev. Cancer Biol."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Hu, K., Xia, Y., Yuan, T., Lin, Y., and Yang, J. (2025). Pharmacodynamic-Driven Sequence-Dependent Synergy Effects in Pemetrexed-Osimertinib Combination Against Non-Small Cell Lung Cancer (NSCLC): Optimizing Synergy Through Sequential Interval. Pharmaceutics, 17.","DOI":"10.3390\/pharmaceutics17081044"},{"key":"ref_55","unstructured":"U.S. Food and Drug Administration (2025, September 15). Doxil Label, Available online: https:\/\/www.accessdata.fda.gov\/drugsatfda_docs\/label\/2007\/050718s029lbl.pdf."},{"key":"ref_56","unstructured":"National Cancer Institute (2025, September 17). Cancer Nano-Therapies in the Clinic and Clinical Trials, Available online: https:\/\/dctd.cancer.gov\/research\/research-areas\/nanotech\/cancer-nano\/current-therapies."},{"key":"ref_57","unstructured":"Drugs.com (2025, September 15). DaunoXome: Package Insert\/Prescribing Information. Available online: https:\/\/www.drugs.com\/pro\/daunoxome.html."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Ibrahim, M., Abuwatfa, W.H., Awad, N.S., Sabouni, R., and Husseini, G.A. (2022). Encapsulation, Release, and Cytotoxicity of Doxorubicin Loaded in Liposomes, Micelles, and Metal-Organic Frameworks: A Review. Pharmaceutics, 14.","DOI":"10.3390\/pharmaceutics14020254"},{"key":"ref_59","unstructured":"European Medicines Agency (2025, September 17). Myocet Liposomal. Available online: https:\/\/www.ema.europa.eu\/en\/medicines\/human\/EPAR\/myocet-liposomal."},{"key":"ref_60","unstructured":"Sercombe, L., Veerati, T., Moheimani, F., Wu, S.Y., Sood, A.K., and Hua, S. (2017). Liposomal Formulations in Clinical Use: An Updated Review. Pharmaceutics, 9."},{"key":"ref_61","unstructured":"European Medicines Agency (2025, September 17). Mepact. Available online: https:\/\/www.ema.europa.eu\/en\/medicines\/human\/EPAR\/mepact."},{"key":"ref_62","unstructured":"RxList (2025, September 17). Marqibo (Vincristine Sulfate Liposome Injection): Side Effects, Uses, Dosage, Interactions, Warnings. Available online: https:\/\/www.rxlist.com\/marqibo-drug.htm."},{"key":"ref_63","unstructured":"Medsafe (2025, September 17). Onivyde Injection Datasheet, Available online: https:\/\/www.medsafe.govt.nz\/profs\/datasheet\/o\/onivydeinj.pdf."},{"key":"ref_64","unstructured":"Therapeutic Goods Administration (2025, September 14). Australian Public Assessment Report for Vyxeos, Available online: https:\/\/www.tga.gov.au\/sites\/default\/files\/2023-02\/auspar-vyxeos-230210.pdf."},{"key":"ref_65","unstructured":"Lymphoma Research Foundation (2025, September 14). VYXEOS Demonstrated Superior Overall Survival, Higher CR and CR+CRi Rates, and a Better Chance to Reach HSCT vs 7 + 3. Available online: https:\/\/lymphoma.org\/wp-content\/uploads\/2020\/06\/Treatment-Guide-for-AML-Therapy.pdf."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Zhao, M., Lei, C., Yang, Y., Bu, X., Ma, H., Gong, H., Liu, J., Fang, X., Hu, Z., and Fang, Q. (2015). Abraxane, the Nanoparticle Formulation of Paclitaxel Can Induce Drug Resistance by Up-Regulation of P-gp. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0131429"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez, F., Caruana, P., De la Fuente, N., Espa\u00f1ol, P., G\u00e1mez, M., Balart, J., Llurba, E., Rovira, R., Ruiz, R., and Mart\u00edn-Lorente, C. (2022). Nano-Based Approved Pharmaceuticals for Cancer Treatment: Present and Future Challenges. Biomolecules, 12.","DOI":"10.3390\/biom12060784"},{"key":"ref_68","first-page":"24","article-title":"Recent Advanced Lipid-Based Nanomedicines for Overcoming Cancer Resistance","volume":"7","author":"Dechbumroong","year":"2024","journal-title":"Cancer Drug Resist."},{"key":"ref_69","unstructured":"GlobeNewswire (2025, September 15). Oasmia Pharmaceutical Receives Approval from European Commission for Apealea. Available online: https:\/\/www.globenewswire.com\/news-release\/2018\/11\/22\/1655521\/0\/en\/Oasmia-Pharmaceutical-Receives-Approval-from-European-Commission-for-Apealea-paclitaxel-micellar-in-the-European-Union.html."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Anselmo, A.C., and Mitragotri, S. (2019). Nanoparticles in the Clinic: An Update. Bioeng. Transl. Med., 4.","DOI":"10.1002\/btm2.10143"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1177\/1758834014539183","article-title":"Ado-Trastuzumab Emtansine (T-DM1) in Human Epidermal Growth Factor Receptor 2 (HER2)-Positive Metastatic Breast Cancer: Latest Evidence and Clinical Potential","volume":"6","author":"Peddi","year":"2014","journal-title":"Ther. Adv. Med. Oncol."},{"key":"ref_72","unstructured":"CarelonRx (2025, September 15). Fyarro (Sirolimus Albumin Bound)\u2014Medical Drug Clinical Criteria. Available online: https:\/\/www.carelonrx.com\/ms\/pharmacyinformation\/Fyarro.pdf."},{"key":"ref_73","unstructured":"U.S. Food and Drug Administration (2025, September 14). FDA Approves Sirolimus Protein-Bound Particles for Malignant Perivascular Epithelioid Cell Tumor, Available online: https:\/\/www.fda.gov\/drugs\/resources-information-approved-drugs\/fda-approves-sirolimus-protein-bound-particles-malignant-perivascular-epithelioid-cell-tumor."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1038\/s41392-023-01642-x","article-title":"Smart nanoparticles for cancer therapy","volume":"8","author":"Sun","year":"2023","journal-title":"Signal Transduct. Target. Ther."},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Giri, P.M., Banerjee, A., and Layek, B. (2023). A Recent Review on Cancer Nanomedicine. Cancers, 15.","DOI":"10.3390\/cancers15082256"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"104404","DOI":"10.1016\/j.jddst.2023.104404","article-title":"Pharmacokinetics and Tumor Delivery of Nanoparticles","volume":"83","author":"Yuan","year":"2023","journal-title":"J. Drug Deliv. Sci. Technol."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/s40164-025-00602-1","article-title":"Applications of Liposomes and Lipid Nanoparticles in Cancer Therapy: Current Advances and Prospects","volume":"14","author":"Cheng","year":"2025","journal-title":"Exp. Hematol. Oncol."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1038\/s41571-020-0352-8","article-title":"Moving towards personalized treatments of immune-related adverse events","volume":"17","author":"Esfahani","year":"2020","journal-title":"Nat. Rev. Clin. Oncol."},{"key":"ref_79","first-page":"1411","article-title":"High-throughput genomics and clinical outcome in oncology","volume":"30","author":"Massard","year":"2019","journal-title":"Ann. Oncol."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1038\/nrc.2017.7","article-title":"Liquid biopsies come of age: Towards implementation of circulating tumour DNA","volume":"17","author":"Wan","year":"2019","journal-title":"Nat. Rev. Cancer"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"858","DOI":"10.1158\/2159-8290.CD-20-1311","article-title":"Liquid biopsy: From discovery to clinical application","volume":"11","author":"Pantel","year":"2021","journal-title":"Cancer Discov."},{"key":"ref_82","first-page":"297","article-title":"Liquid biopsy for advanced NSCLC: A consensus statement","volume":"18","author":"Rolfo","year":"2021","journal-title":"Nat. Rev. Clin. Oncol."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1159\/000492710","article-title":"Liquid biopsy and lung cancer","volume":"63","author":"Pisapia","year":"2019","journal-title":"Acta Cytol."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"1702","DOI":"10.1345\/aph.1D374","article-title":"Population pharmacokinetics I: Background, concepts, and models","volume":"38","author":"Ette","year":"2004","journal-title":"Ann. Pharmacother."},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Huang, H., Zhao, W., Qin, N., and Duan, X. (2024). Recent progress on physiologically based pharmacokinetic (PBPK) model: A review based on bibliometrics. Toxics, 12.","DOI":"10.3390\/toxics12060433"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1038\/clpt.2010.298","article-title":"Applications of physiologically based pharmacokinetic (PBPK) modeling and simulation during regulatory review","volume":"89","author":"Zhao","year":"2011","journal-title":"Clin. Pharmacol. Ther."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1038\/s41746-025-01471-y","article-title":"Convergence of evolving artificial intelligence and machine learning techniques in precision oncology","volume":"8","author":"Fountzilas","year":"2025","journal-title":"NPJ Digit. Med."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.csbj.2014.11.005","article-title":"Machine learning applications in cancer prognosis and prediction","volume":"13","author":"Kourou","year":"2014","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"1559","DOI":"10.1038\/s41591-018-0177-5","article-title":"Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning","volume":"24","author":"Coudray","year":"2019","journal-title":"Nat. Med."},{"key":"ref_90","unstructured":"National Academy of Medicine, Whicher, D., Ahmed, M., Israni, S.T., and Matheny, M. (2023). Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril, National Academies Press."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1007\/s11523-021-00796-4","article-title":"An overview of PARP inhibitors for the treatment of breast cancer","volume":"16","author":"Cortesi","year":"2021","journal-title":"Target. Oncol."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1093\/jnci\/djx187","article-title":"Real-world data for clinical evidence generation in oncology","volume":"109","author":"Khozin","year":"2017","journal-title":"J. Natl. Cancer Inst."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1056\/NEJMra1510062","article-title":"Master protocols to study multiple therapies, multiple diseases, or both","volume":"377","author":"Woodcock","year":"2017","journal-title":"N. Engl. J. Med."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1002\/cpt.3298","article-title":"Dose optimization in oncology drug development: An international consortium for innovation and quality in pharmaceutical development white paper","volume":"116","author":"Samineni","year":"2024","journal-title":"Clin. Pharmacol. Ther."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1002\/cpt.3636","article-title":"Impact of model-informed drug development on drug development cycle times and clinical trial cost","volume":"118","author":"Sahasrabudhe","year":"2025","journal-title":"Clin. Pharmacol. Ther."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"e929474","DOI":"10.12659\/MSM.929474","article-title":"Clinical benefit of therapeutic drug monitoring in colorectal cancer patients who received fluorouracil-based chemotherapy","volume":"27","author":"Zhou","year":"2021","journal-title":"Med. Sci. Monit."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"1095","DOI":"10.1002\/cpt.1304","article-title":"Clinical pharmacogenetics implementation consortium guideline for thiopurine dosing based on TPMT and NUDT15 genotypes: 2018 update","volume":"105","author":"Relling","year":"2019","journal-title":"Clin. Pharmacol. Ther."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"1990","DOI":"10.1002\/sim.6097","article-title":"Phase I\/II adaptive design for drug combination oncology trials","volume":"33","author":"Wages","year":"2014","journal-title":"Stat. Med."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1002\/cpt.3356","article-title":"Model-informed reinforcement learning for enabling precision dosing via adaptive dosing","volume":"116","author":"Tosca","year":"2024","journal-title":"Clin. Pharmacol. Ther."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1039\/D3SD00304C","article-title":"Democratizing nucleic acid-based molecular diagnostic tests for infectious diseases at resource-limited settings\u2014From point of care to extreme point of care","volume":"3","author":"Chakraborty","year":"2024","journal-title":"Sens. Diagn."},{"key":"ref_101","doi-asserted-by":"crossref","unstructured":"Ahmed, L., Constantinidou, A., and Chatzittofis, A. (2023). Patients\u2019 perspectives related to ethical issues and risks in precision medicine: A systematic review. Front. Med., 10.","DOI":"10.3389\/fmed.2023.1215663"},{"key":"ref_102","doi-asserted-by":"crossref","unstructured":"Calvino, G., Farro, J., Zampatti, S., Peconi, C., Megalizzi, D., Trastulli, G., Andreucci, S., Cascella, R., Strafella, C., and Caltagirone, C. (2025). From genomics to AI: Revolutionizing precision medicine in oncology. Appl. Sci., 15.","DOI":"10.3390\/app15126578"},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1057\/s41292-023-00323-w","article-title":"Challenges in public policy for the implementation of pharmacogenetic tests in Europe","volume":"20","author":"Meli","year":"2024","journal-title":"BioSocieties"},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"114225","DOI":"10.1016\/j.ejca.2024.114225","article-title":"Empowering effective biomarker-driven precision oncology: A call to action","volume":"209","author":"Lawler","year":"2024","journal-title":"Eur. J. Cancer"},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"Ferrero, J.M., Bouriga, R., Gal, J., and Milano, G. (2025). De-escalating anticancer treatment: Watch your step. Cancers, 17.","DOI":"10.3390\/cancers17152474"}],"container-title":["Journal of Personalized Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-4426\/15\/11\/516\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T17:48:36Z","timestamp":1762192116000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-4426\/15\/11\/516"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,31]]},"references-count":105,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2025,11]]}},"alternative-id":["jpm15110516"],"URL":"https:\/\/doi.org\/10.3390\/jpm15110516","relation":{},"ISSN":["2075-4426"],"issn-type":[{"value":"2075-4426","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,31]]}}}