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.