Commentary on Pharmacometrics for Immunotherapy
Open accessAbstract
This commentary provides an overview of recent examples of pharmacometrics applied during the clinical development of two antagonists of the programmed death-1 (PD-1) cell surface receptor, pembrolizumab and nivolumab. Despite the remarkable achievements obtained in predicting the correct dosing schedule from different quantitative approaches, data indicated a great degree of heterogeneity in tumor response. To achieve therapeutic goals the search for predictive biomarkers associated with a lack of response and mechanism-based combination studies are warranted.
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The majority of novel checkpoint inhibitors in cancer immunotherapy exhibit heterogeneous tumor responses and lack predictive biomarkers.
“since the majority of these therapeutics exhibit heterogeneous tumor responses and lack predictive biomarkers.81”
From Tutorial on monoclonal antibody pharmacokinetics and its considerations in early development (2018) · cites this paper as [81]
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Cites
Oncology meets immunology: the cancer-immunity cycle.
Chen, D. S., & Mellman, I. (2013) · Immunity · doi:10.1016/j.immuni.2013.07.012 · Cited by 6,929 · see citing works
Immune Checkpoint Blockade: A Common Denominator Approach to Cancer Therapy
Topalian, S. L., Drake, C. G., & Pardoll, D. M. (2015) · Cancer Cell · doi:10.1016/j.ccell.2015.03.001 · Cited by 4,229 · see citing works
Sunshine, J. C., & Taube, J. M. (2015) · Current Opinion in Pharmacology · doi:10.1016/j.coph.2015.05.011 · Cited by 562 · see citing works
Model-Based Population Pharmacokinetic Analysis of Nivolumab in Patients With Solid Tumors
Bajaj, G., Wang, X., Agrawal, S., Gupta, M., Roy, A., & Feng, Y. (2016) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12143 · Cited by 265 · see citing works
Ahamadi, M., Freshwater, T., Prohn, M., Li, C. H., de Alwis, D., de Greef, R., Elassaiss‐Schaap, J., Kondic, A. G., & Stone, J. (2016) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12139 · Cited by 159 · see citing works
Elassaiss‐Schaap, J., Rossenu, S., Lindauer, A., Kang, S., de Greef, R., Sachs, J., & de Alwis, D. (2016) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12132 · Cited by 121 · see citing works
Lindauer, A., Valiathan, C., Mehta, K., Sriram, V, de Greef, R., Elassaiss-Schaap, J., & de Alwis, D. (2017) · CPT: Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12130 · Cited by 120 · see citing works
Wang, X., Feng, Y.-Y., Bajaj, G., Gupta, M., Agrawal, S., Yang, A., Park, J.-S., Lestini, B. J., & Roy, A. K. (2016) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12133 · Cited by 91 · see citing works
Chatterjee, M., Elassaiss‐Schaap, J., Lindauer, A., Turner, D., Sostelly, A., Freshwater, T., Mayawala, K., Ahamadi, M., Stone, J., de Greef, R., et al. (2016) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12140 · Cited by 85 · see citing works
de Greef, R., Elassaiss‐Schaap, J., Chatterjee, M. S., Turner, D., Ahamadi, M., Forman, M. S., Cutler, D. L., de Alwis, D., Kondic, A. G., & Stone, J. A. (2016) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12131 · Cited by 26 · see citing works
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Tutorial on monoclonal antibody pharmacokinetics and its considerations in early development
Ovacik, M., & Lin, K. (2018) · Clinical and Translational Science · doi:10.1111/cts.12567 · Cited by 299 · see citing works
Helmlinger, G., Sokolov, V. V., Peskov, K. V., Hallow, K. M., Kosinsky, Y., Voronova, V., Chu, L., Yakovleva, T. A., Azarov, I., Kaschek, D., et al. (2019) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12426 · Cited by 74 · see citing works
Predicting response to pembrolizumab in metastatic melanoma by a new personalization algorithm
Tsur, N., Kogan, Y., Avizov-Khodak, E., Vaeth, D., Vogler, N., Utikal, J. S., Lotem, M., & Agur, Z. (2019) · Journal of Translational Medicine · doi:10.1186/s12967-019-2081-2 · Cited by 17 · see citing works
Dosage of anti-PD-1 monoclonal antibodies: a cardinal open question
Sureda, M., Calvo, E., Mata, J. J., Escudero-Ortíz, V., Martinez-Navarro, E., Catalán-Latorre, A., & Rebollo, J. (2021) · Clinical & Translational Oncology · doi:10.1007/s12094-021-02563-3 · Cited by 7 · see citing works
Zalba, S., Belsúe, V., Topp, B. G., de Alwis, D. P., Álvarez, M., Trocóniz, I. F., Berraondo, P., & Garrido, M. J. (2021) · British Journal of Cancer · doi:10.1038/s41416-020-01239-z · Cited by 6 · see citing works
Self-citationIMPORTANCIA DE LA FARMACOMETRÍA EN EL DESARROLLO DE PRODUCTOS BIOLÓGICOS
Saborío, K. B., Avilés, R. M., Salazar, V., Rocha-Romero, A., Pérez, A. V., & Ramírez, J. M. F. (2023) · Revista Médica de la Universidad de Costa Rica · doi:10.15517/rmucr.v17i1.55336
- Authors
- Garrido, M., Berraondo, P., & Trocóniz, I.
- Affiliations
- Pharmacometrics & Systems Pharmacology, Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy; University of Navarra; Pamplona Spain
- Navarre Institute of Health Research (ES)
- ORCID
- Berraondo, P
- Venue
- CPT: Pharmacometrics & Systems Pharmacology
- Publisher
- Wiley
- Published
- 2017-01
- Volume
- 6
- Issue
- 1
- Pages
- 8-10
- ISSN
- 2163-8306 (ISSN-L)
- PMC
- PMC5270298
- OpenAlex
- W2579778311
- Cited by
- 6
- References
- 10
- Citations by year
- 2023: 1 · 2021: 2 · 2019: 2 · 2018: 1
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- CPT Pharmacometrics & Systems Pharmacology (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
- Keywords
- pharmacometrics, immunotherapy, pembrolizumab, nivolumab, predictive biomarkers, treatment response prediction, combination therapy
- MeSH terms
- Antibodies, Monoclonal, Antineoplastic Agents, Humans, Immunotherapy, Melanoma, Neoplasms, Biomarkers, Tumor, Biomarkers, B7-H1 Antigen, Programmed Cell Death 1 Receptor
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