REFERENCES:
1. Minchella K, Xu H, Al-Huniti N. Exposure-response methods and dose approval of new oncology drugs by FDA from 2005 to 2015. J. of Clin. Oncol. 2016; 34: 2530-30.
2. Yang J, Zhao H, Garnett C, et al. The combination of exposure-response and case-control analyses in regulatory decision making. J Clin Pharmacol. 2013; 53: 160-6.
3. Shah MA, Xu RH, Bang YJ, et al. HELOISE: Phase IIIb Randomized Multicenter Study Comparing Standard-of-Care and Higher-Dose Trastuzumab Regimens Combined With Chemotherapy as First-Line Therapy in Patients With Human Epidermal Growth Factor Receptor 2-Positive Metastatic Gastric or Gastroesophageal Junction Adenocarcinoma. J Clin Oncol. 2017; 35: 2558-67.
4. Li J, Levi M, Charoin J-E, et al. Rituximab Exhibits a Long Half-Life Based on a Population Pharmacokinetic Analysis in Non-Hodgkin’s Lymphoma (NHL) Patients. Blood 2007; 100.
5. Li J, Zhi J, Wenger M, et al. Population pharmacokinetics of rituximab in patients with chronic lymphocytic leukemia. J Clin Pharmacol. 2012; 52: 1918-26.
6. Rozman S, Grabnar I, Novakovic S, Mrhar A, Jezersek Novakovic B. Population pharmacokinetics of rituximab in patients with diffuse large B-cell lymphoma and association with clinical outcome. Br J Clin Pharmacol. 2017; 83: 1782-90.
7. Bajaj G, Wang X, Agrawal S, Gupta M, Roy A, Feng Y. Model-Based Population Pharmacokinetic Analysis of Nivolumab in Patients With Solid Tumors. CPT Pharmacometrics Syst Pharmacol. 2017; 6: 58-66.
8. Baverel PG, Dubois VFS, Jin CY, et al. Population Pharmacokinetics of Durvalumab in Cancer Patients and Association With Longitudinal Biomarkers of Disease Status. Clin Pharmacol Ther. 2018; 103: 631-42.
9. Li H, Yu J, Liu C, et al. Time dependent pharmacokinetics of pembrolizumab in patients with solid tumor and its correlation with best overall response. J Pharmacokinet Pharmacodyn. 2017; 44: 403-14.
10. Wilkins JJ, Brockhaus B, Dai H, et al. Time-Varying Clearance and Impact of Disease State on the Pharmacokinetics of Avelumab in Merkel Cell Carcinoma and Urothelial Carcinoma. CPT Pharmacometrics Syst Pharmacol. 2019; 8: 415-27.
11. Ryman JT, Meibohm B. Pharmacokinetics of Monoclonal Antibodies.CPT Pharmacometrics Syst Pharmacol. 2017; 6: 576-88.
12. Liu C, Yu J, Li H, et al. Association of time-varying clearance of nivolumab with disease dynamics and its implications on exposure response analysis. Clin Pharmacol Ther . 2017; 101: 657-66.
13. EMA. Assessment Report. OPDIVO. International non-proprietary name: Nivolumab. https://www.ema.europa.eu/en/documents/variation-report/opdivo-h-c-3985-ii-0008-epar-scientific-discussion-variation_en.pdf. In, 2016.
14. Wang Y, Booth B, Rahman A, Kim G, Huang SM, Zineh I. Toward greater insights on pharmacokinetics and exposure-response relationships for therapeutic biologics in oncology drug development. Clin Pharmacol Ther. 2017; 101: 582-84.
15. Li C, Wang B, Chen SC, et al. Exposure-response analyses of trastuzumab emtansine in patients with HER2-positive advanced breast cancer previously treated with trastuzumab and a taxane. Cancer Chemother Pharmacol. 2017; 80: 1079-90.
16. Imamura CK. Therapeutic drug monitoring of monoclonal antibodies: Applicability based on their pharmacokinetic properties. Drug Metab Pharmacokinet. 2019; 34: 14-18.
17. Lee JW, Kelley M, King LE, et al. Bioanalytical approaches to quantify ”total” and ”free” therapeutic antibodies and their targets: technical challenges and PK/PD applications over the course of drug development. AAPS J 2011; 13: 99-110.
18. Gorovits B, Alley SC, Bilic S, et al. Bioanalysis of antibody-drug conjugates: American Association of Pharmaceutical Scientists Antibody-Drug Conjugate Working Group position paper. Bioanalysis2013; 5: 997-1006.
19. Kraynov E, Kamath AV, Walles M, et al. Current Approaches for Absorption, Distribution, Metabolism, and Excretion Characterization of Antibody-Drug Conjugates: An Industry White Paper. Drug Metab Dispos. 2016; 44: 617-23.
20. Wang J, Song P, Schrieber S, et al. Exposure-response relationship of T-DM1: insight into dose optimization for patients with HER2-positive metastatic breast cancer. Clin Pharmacol Ther. 2014; 95: 558-64.
21. Iacus SM, King G, Porro G. Multivariate Matching Methods That are Monotonic Imbalance Bounding. J. Am. Stat. Assoc. 2011; 106: 345-61.
22. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika 1983; 70: 41-55.
23. Rubin DB. Inference and missing data. Biometrika 1976; 63: 581-92.
24. Han K, Chanu P, Jonsson F, et al. Exposure-Response and Tumor Growth Inhibition Analyses of the Monovalent Anti-c-MET Antibody Onartuzumab (MetMAb) in the Second- and Third-Line Non-Small Cell Lung Cancer.AAPS J. 2017; 19: 527-33.
25. Morrissey KM, Marchand M, Patel H, et al. Alternative dosing regimens for atezolizumab: an example of model-informed drug development in the postmarketing setting. Cancer Chemother Pharmacol. 2019; 84: 1257-67.
26. Quartino AL, Claret L, Li J, et al. Evaluation of tumor size metrics to predict survival in advanced gastric cancer. PAGE 2013; 22: Abstr 2812.
27. Stein WD, Figg WD, Dahut W, et al. Tumor growth rates derived from data for patients in a clinical trial correlate strongly with patient survival: a novel strategy for evaluation of clinical trial data.Oncologist 2008; 13: 1046-54.
28. Bruno R, Claret L, Jin YJ, Girish S. FDA-ISoP public workshop: model informed drug development (MIDD) for oncology products. Silver Spring,MD: FDA. 2018 Feb 1; Available from: https://www.fda.gov/drugs/news-events-human-drugs/fda-isop-public-workshop-model-informed-drug-development-midd-oncology-products. In, 2018.
29. Bruno R, Claret L, Wu B, et al. A tumor growth rate/overall survival model for atezolizumab as an early predictor of OS in patients with first or second line metastatic urothelial carcinoma. J. Clin. Oncol. 2018; 36: 62-62.
30. Chigutsa E, Long AJ, Wallin JE. Exposure-Response Analysis of Necitumumab Efficacy in Squamous Non-Small Cell Lung Cancer Patients.CPT Pharmacometrics Syst Pharmacol. 2017; 6: 560-68.
31. Claret L, Gupta M, Han K, et al. Evaluation of tumor-size response metrics to predict overall survival in Western and Chinese patients with first-line metastatic colorectal cancer. J Clin Oncol. 2013; 31: 2110-4.
32. Claret L, Jin JY, Ferte C, et al. A Model of Overall Survival Predicts Treatment Outcomes with Atezolizumab versus Chemotherapy in Non-Small Cell Lung Cancer Based on Early Tumor Kinetics. Clin Cancer Res. 2018; 24: 3292-98.
33. Claret L, Lu JF, Bruno R, Hsu CP, Hei YJ, Sun YN. Simulations using a drug-disease modeling framework and phase II data predict phase III survival outcome in first-line non-small-cell lung cancer. Clin Pharmacol Ther. 2012; 92: 631-4.
34. Feng Y, Wang X, Suryawanshi S, Bello A, Roy A. Linking Tumor Growth Dynamics to Survival in Ipilimumab-Treated Patients With Advanced Melanoma Using Mixture Tumor Growth Dynamic Modeling. CPT Pharmacometrics Syst Pharmacol. 2019; 8: 825-34.
35. Tardivon C, Desmee S, Kerioui M, et al. Association Between Tumor Size Kinetics and Survival in Patients With Urothelial Carcinoma Treated With Atezolizumab: Implication for Patient Follow-Up. Clin Pharmacol Ther. 2019; 106: 810-20.
36. Wang Y, Sung C, Dartois C, et al. Elucidation of relationship between tumor size and survival in non-small-cell lung cancer patients can aid early decision making in clinical drug development. Clin Pharmacol Ther. 2009; 86: 167-74.
37. Zheng Y, Narwal R, Jin C, et al. Population Modeling of Tumor Kinetics and Overall Survival to Identify Prognostic and Predictive Biomarkers of Efficacy for Durvalumab in Patients With Urothelial Carcinoma. Clin Pharmacol Ther. 2018; 103: 643-52.
38. Bruno R, Bottino D, de Alwis DP, et al. Progress and Opportunities to Advance Clinical Cancer Therapeutics Using Tumor Dynamic Models.Clin Cancer Res. 2020; 26: 1787-95.
39. Zecchin C, Gueorguieva I, Enas NH, Friberg LE. Models for change in tumour size, appearance of new lesions and survival probability in patients with advanced epithelial ovarian cancer. Br J Clin Pharmacol. 2016; 82: 717-27.
40. Turner DC, Kondic AG, Anderson KM, et al. Pembrolizumab Exposure-Response Assessments Challenged by Association of Cancer Cachexia and Catabolic Clearance. Clin Cancer Res. 2018; 24: 5841-49.
41. Bornkamp B, Bretz F, Dmitrienko A, et al. Innovative approaches for designing and analyzing adaptive dose-ranging trials. J Biopharm Stat. 2007; 17: 965-95.
42. Hay M, Thomas DW, Craighead JL, Economides C, Rosenthal J. Clinical development success rates for investigational drugs. Nat Biotechnol. 2014; 32: 40-51.
43. Lyauk YK, Jonker DM, Lund TM. Dose Finding in the Clinical Development of 60 US Food and Drug Administration-Approved Drugs Compared With Learning vs. Confirming Recommendations. Clin Transl Sci. 2019; 12: 481-89.
44. Wolchok JD, Neyns B, Linette G, et al. Ipilimumab monotherapy in patients with pretreated advanced melanoma: a randomised, double-blind, multicentre, phase 2, dose-ranging study. Lancet Oncol. 2010; 11: 155-64.
45. Feng Y, Roy A, Masson E, Chen TT, Humphrey R, Weber JS. Exposure-response relationships of the efficacy and safety of ipilimumab in patients with advanced melanoma. Clin Cancer Res. 2013; 19: 3977-86.
46. Ascierto PA, Del Vecchio M, Robert C, et al. Ipilimumab 10 mg/kg versus ipilimumab 3 mg/kg in patients with unresectable or metastatic melanoma: a randomised, double-blind, multicentre, phase 3 trial.Lancet Oncol. 2017; 18: 611-22.
47. Gripp S, Moeller S, Bolke E, et al. Survival prediction in terminally ill cancer patients by clinical estimates, laboratory tests, and self-rated anxiety and depression. J Clin Oncol. 2007; 25: 3313-20.
48. Maltoni M, Caraceni A, Brunelli C, et al. Prognostic factors in advanced cancer patients: evidence-based clinical recommendations–a study by the Steering Committee of the European Association for Palliative Care. J Clin Oncol. 2005; 23: 6240-8.
49. Dai HI, Vugmeyster Y, Mangal N. Characterizing Exposure-Response Relationship for Therapeutic Monoclonal Antibodies in Immuno-Oncology and Beyond: Challenges, Perspectives, and Prospects. Clin Pharmacol Ther. 2020.
50. McMillan DC. An inflammation-based prognostic score and its role in the nutrition-based management of patients with cancer. Proc Nutr Soc. 2008; 67: 257-62.
51. Trobec K, Kerec Kos M, von Haehling S, Springer J, Anker SD, Lainscak M. Pharmacokinetics of drugs in cachectic patients: a systematic review. PLoS One 2013; 8: e79603.
52. Hamuro L, Statkevich P, Bello A, Roy A, Bajaj G. Nivolumab Clearance Is Stationary in Patients With Resected Melanoma on Adjuvant Therapy: Implications of Disease Status on Time-Varying Clearance. Clin Pharmacol Ther. 2019; 106: 1018-27.
53. Chatterjee M, Turner DC, Felip E, et al. Systematic evaluation of pembrolizumab dosing in patients with advanced non-small-cell lung cancer. Ann Oncol. 2016; 27: 1291-8.
54. FDA. Clinical pharmacology and biopharmaceutics review: durvalumab. https://www.accessdata.fda.gov/drugsatfda_docs/nda/2017/761069Orig1s000TOC.cfm. In, 2017.
55. Jin C, Zheng Y, Jin X, et al. Exposure-efficacy and safety analysis of durvalumab in patients with urothelial carcinoma (UC) and other solid tumors. J. of Clin. Oncol. 2017; 35: 2568-68.
56. Jin J, Wang B, Gao Y, et al. Exposure–safety relationship of trastuzumab emtansine (T-DM1) in patients with HER2-positive locally advanced or metastatic breast cancer (MBC). J. of Clin. Oncol.2013; 31: 646-46.
57. Kang SP, Chatterjee M, Ahamadi M, et al. 3344 Relationship between pembrolizumab exposure and efficacy/safety in 1016 patients (pts) with advanced or metastatic melanoma. Eur J of Cancer. 2015; 51: S682.
58. Wang X, Feng Y, Bajaj G, et al. Quantitative Characterization of the Exposure-Response Relationship for Cancer Immunotherapy: A Case Study of Nivolumab in Patients With Advanced Melanoma. CPT Pharmacometrics Syst Pharmacol. 2017; 6: 40-48.
59. FDA. Guidance Document. Exposure-Response Relationships — Study Design, Data Analysis, and Regulatory Applications May 2003. http://www.fda.gov/downloads/drugs guidancecomplianceregulatoryinformation/guidances/ucm072109.pdf. In, 2018.