Pharmacodynamic biomarkers in model-based drug development in oncology

Current Clinical Pharmacology

Volumn 6, Issue 1, 2011, Pages 30-40

  Keizer, Ron J ^a,b   Schellens, Jan H M ^b,c   Beijnen, Jos H ^a,b,c   Huitema, Alwin D R ^a,b  

^a SLOTERVAART HOSPITAL   (Netherlands)

^b NETHERLANDS CANCER INSTITUTE   (Netherlands)

^c UTRECHT UNIVERSITY   (Netherlands)

Author keywords

Biomarker; Model based drug development; Modeling and simulation; Pharmacodynamic; Pharmacometrics

Indexed keywords

2 [4 (1 HYDROXYIMINO 5 INDANYL) 3 (4 PYRIDINYL) 1H PYRAZOL 1 YL]ETHANOL; 3 [1 (2,6 DICHLORO 3 FLUOROPHENYL)ETHOXY] 5 [1 (4 PIPERIDINYL) 1H PYRAZOL 4 YL] 2 PYRIDINYLAMINE; ANTINEOPLASTIC AGENT; CAPECITABINE; CETUXIMAB; DASATINIB; E 7820; EVEROLIMUS; FLUOROURACIL; GEFITINIB; LY 2157299; PHARMACOLOGICAL BIOMARKER; RITUXIMAB; SILTUXIMAB; SUNITINIB; UNCLASSIFIED DRUG; VADIMEZAN;

COLORECTAL CANCER; DOSAGE SCHEDULE COMPARISON; DRUG BLOOD LEVEL; DRUG DESIGN; DRUG DOSE ESCALATION; DRUG DOSE REGIMEN; GLIOMA; HEAD AND NECK CANCER; HODGKIN DISEASE; HUMAN; MODEL BASED DRUG DEVELOPMENT; MOLECULAR MODEL; NONHUMAN; PHARMACODYNAMICS; PHASE 1 CLINICAL TRIAL (TOPIC); PHASE 2 CLINICAL TRIAL (TOPIC); PHASE 3 CLINICAL TRIAL (TOPIC); PRIORITY JOURNAL; REVIEW; RHEUMATOID ARTHRITIS; SIMULATION; TUMOR GROWTH;

ANIMALS; ANTINEOPLASTIC AGENTS; BIOMARKERS, PHARMACOLOGICAL; CLINICAL TRIALS AS TOPIC; COMPUTER SIMULATION; DRUG DELIVERY SYSTEMS; DRUG DESIGN; DRUG EVALUATION, PRECLINICAL; HUMANS; MODELS, BIOLOGICAL; NEOPLASMS;

EID: 79953066756     PISSN: 15748847     EISSN: None     Source Type: Journal    
DOI: 10.2174/157488411794941368     Document Type: Review

References (86)

1. Kola I, Landis J. Can the pharmaceutical industry reduce attrition rates? Nat Rev Drug Discov 2004; 3: 711-6.
2. Ferlay J, Parkin DM, Steliarova-Foucher E. Estimates of cancer incidence and mortality in Europe in 2008. Eur J Cancer (Oxford, England: 1990) 2010; 46: 765-81.
3. Gutierrez ME, Kummar S, Giaccone G. Next generation oncology drug development: opportunities and challenges. Nat Rev Clin Oncol 2009; 6: 259-65.
4. FDA - Office of the commissioner, challenges and opportunities report - March 2004; http://www.fda.gov/ScienceResearch/SpecialTopics/CriticalPathInitiative/CriticalPathOpportunitiesReports/ucm077262.htm.
5. Lalonde RL, Kowalski KG, Hutmacher MM, et al. Model-based drug development. Clin Pharmacol Ther 2007; 82: 21-32.
6. Grasela TH, Dement CW, Kolterman OG, et al. Pharmacometrics and the Transition to Model-Based Development. Clin Pharmacol Ther 2007; 82: 137-42.
7. Hu C, Sale M. Population modeling approach in bioequivalence assessment, Pharmacometrics: The Science of Quantitative Pharmacology, Wiley-Interscience, 2007.
8. Bhattaram VA, Bonapace C, Chilukuri DM, et al. Impact of pharmacometric reviews on new drug approval and labeling decisions- a survey of 31 new drug applications submitted between 2005 and 2006. Clin Pharmacol Ther 2007; 81: 213-21.
9. Zandvliet AS, Schellens JHM, Beijnen JH, Huitema ADR. Population pharmacokinetics and pharmacodynamics for treatment optimization in clinical oncology. Clin Pharmacokinet 2008; 47: 487-13.
10. Friberg LE, Henningsson A, Maas H, Nguyen L, Karlsson MO. Model of chemotherapy-induced myelosuppression with parameter consistency across drugs. J Clin Oncol 2002; 20: 4713-21.
11. Zandvliet AS, Karlsson MO, Schellens JH, Copalu W, Beijnen JH, Huitema AD. Two-stage model-based clinical trial design to optimize phase I development of novel anticancer agents. Investigational New Drugs 2010; 28(1): 61-75.
12. Karlsson MO, Anehall T, Friberg LE, et al. Pharmacokinetic/ pharmacodynamic modelling in oncological drug development. Basic Clin Pharmacol Toxicol 2005; 96: 206-11.
13. Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework. Clin Pharmacol Ther 2001: 69: 89-95.
14. Kuhlmann J, Wensing G. The applications of biomarkers in early clinical drug development to improve decision-making processes. Curr Clin Pharmacol 2006; 1: 185-91.
15. Gobburu JVS. Biomarkers in clinical drug development. Clin Pharmacol Ther 2009; 86: 26-7.
16. Colburn WA, Lee JW. Biomarkers, validation and pharmacokinetic- pharmacodynamic modelling. Clin Pharmacokinet 2003; 42: 997-1022.
17. Danhof M, Alvan G, Dahl SG, Kuhlmann J, Paintaud G. Mechanism- based pharmacokinetic-pharmacodynamic modeling-a new classification of biomarkers. Pharm Res 2005; 22: 1432-7.
18. Callies S, Andre V, Patel B, et al. Integration of preclinical data to support the design of the first in-man study of LY2181308, a second generation antisense oligonucleotide. Page 19 (2010) Abstr 1759 [www.page-meeting.org/?abstract=1759].
19. Cronier D, Gelbert L, Wishart G, De Dios A. A fully integrated PK/IVTI/IVE model in mouse to help design the FHD trial for a cell cycle inhibitor X. Page 18 (2009) Abstr 1611 [www.pagemeeting.org/?abstract=1611], 2009.
20. Wong H, Belvin M, Herter S, et al. Pharmacodynamics of 2-[4-[(1E)-1-(hydroxyimino)-2,3-dihydro-1H-inden-5-yl]-3-(pyridine-4- yl)-1H-pyrazol-1-yl]ethan-1-ol (GDC-0879), a potent and selective B-Raf kinase inhibitor: understanding relationships between systemic concentrations, phosphorylated mitogen-activated protein kinase kinase 1 inhibition, and efficacy. J Pharmacol Exp Ther 2009; 329: 360-7.
21. Yamazaki S, Skaptason J, Romero D, et al. Pharmacokineticpharmacodynamic modeling of biomarker response and tumor growth inhibition to an orally available cMet kinase inhibitor in human tumor xenograft mouse models. Drug Metab Dispos 2008; 36: 1267-74.
22. Kwak EL, Bang Y, Camidge DR, et al. Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. N Engl J Med 2010; 363, 1693-703.
23. Hallberg B, Palmer RH. Crizotinib-latest champion in the cancer wars?. N Engl J Med 2010; 363: 1760-2.
24. Bueno L, de Alwis DP, Pitou C, et al. Semi-mechanistic modelling of the tumour growth inhibitory effects of LY2157299, a new type I receptor TGF-beta kinase antagonist, in mice. Eur J Cancer 2008; 44: 142-50.
25. Simeoni M, Magni P, Cammia C, et al. Predictive pharmacokinetic- pharmacodynamic modeling of tumor growth kinetics in xenograft models after administration of anticancer agents. Cancer Res 2004; 64: 1094-101.
26. Workman P. Auditing the pharmacological accounts for Hsp90 molecular chaperone inhibitors: unfolding the relationship between pharmacokinetics and pharmacodynamics. Mol Cancer Ther 2003; 2: 131-8.
27. Tanaka C, O'Reilly T, Kovarik JM, et al. Identifying optimal biologic doses of everolimus (RAD001) in patients with cancer based on the modeling of preclinical and clinical pharmacokinetic and pharmacodynamic data. J Clin Oncol 2008; 26: 1596-602.
28. O'Donnell A, Faivre S, Burris HA, et al. Phase I pharmacokinetic and pharmacodynamic study of the oral mammalian target of rapamycin inhibitor everolimus in patients with advanced solid tumors. J Clin Oncol 2008; 26: 1588-95.
29. Tabernero J, Rojo F, Calvo E, et al. Dose- and schedule-dependent inhibition of the mammalian target of rapamycin pathway with everolimus: a phase I tumor pharmacodynamic study in patients with advanced solid tumors. J Clin Oncol 2008; 26: 1603-10.
30. Eisen HJ, Tuzcu EM, Dorent R, et al. Everolimus for the Prevention of Allograft Rejection and Vasculopathy in Cardiac-Transplant Recipients. N Engl J Med 2003; 349: 847-58.
31. Faivre S, Kroemer G, Raymond E. Current development of mTOR inhibitors as anticancer agents. Nat Rev Drug Discov 2006; 5: 671-88.
32. Hay N, Sonenberg N. Upstream and downstream of mTOR. Genes Dev 2004; 18: 1926-45.
33. Boulay A, Rudloff J, Ye J, et al. Dual inhibition of mTOR and estrogen receptor signaling in vitro induces cell death in models of breast cancer. Clin Cancer Res 2005; 11: 5319-28.
34. Laplanche R, Meno-Tetang GML, Kawai R. Physiologically based pharmacokinetic (PBPK) modeling of everolimus (RAD001) in rats involving non-linear tissue uptake. J Pharmacokinet Pharmacodyn 2007; 34: 373-400.
35. Wang S, Zhou Q, Gallo JM. Demonstration of the equivalent pharmacokinetic/pharmacodynamic dosing strategy in a multipledose study of gefitinib. Mol Cancer Ther 2009; 8: 1438-47.
36. Wang S. Guo P, Wang X, Zhou Q, Gallo JM. Preclinical pharmacokinetic/ pharmacodynamic models of gefitinib and the design of equivalent dosing regimens in EGFR wild-type and mutant tumor models. Mol Cancer Ther 2008; 7: 407-17.
37. Uhm JH, Ballman KV, Wu W, et al. Phase II evaluation of gefitinib in patients with newly diagnosed grade 4 astrocytoma: Mayo/North central cancer treatment group study N0074. Int J Radiat Oncol Biol Phys 2010. [Epub ahead of print]
38. Agarwal S, Sane R, Gallardo JL, Ohlfest JR, Elmquist WF. Distribution of gefitinib to the brain is limited by P-glycoprotein (ABCB1) and breast cancer resistance protein (ABCG2)-mediated active efflux. J Pharmacol Exp Ther 2010; 334: 147-55.
39. Keizer R, Funahashi Y, Semba T, et al. Evaluation of clinical dosing of E7820 from preclinical and clinical data using a biomarker. PAGE 19 (2010) Abstr 1690 [www.page-meeting.org/?abstract=1690], 2010.
40. Semba T, Funahashi Y, Ono N, et al. An angiogenesis inhibitor E7820 shows broad-spectrum tumor growth inhibition in a xenograft model: possible value of integrin alpha2 on platelets as a biological marker. Clin Cancer Res 2004; 10: 1430-8.
41. Luo FR, Yang Z, Camuso A, et al. Dasatinib (BMS-354825) pharmacokinetics and pharmacodynamic biomarkers in animal models predict optimal clinical exposure. Clin Cancer Res 2006; 12: 7180-6.
42. Freireich EJ, Gehan EA, Rall DP, Schmidt LH, Skipper HE. Quantitative comparison of toxicity of anticancer agents in mouse, rat, hamster, dog, monkey, and man. Cancer Chemother Rep Part 1 1966; 50: 219-44.
43. Li J, Jameson MB, Baguley BC, Pili R, Baker SD. Population pharmacokinetic-pharmacodynamic model of the vasculardisrupting agent 5,6-dimethylxanthenone-4-acetic acid in cancer patients. Clin Cancer Res 2008; 14: 2102-10.
44. Baguley BC, Zhuang L, Kestell P. Increased plasma serotonin following treatment with flavone-8-acetic acid, 5,6-dimethylxanthenone-4- acetic acid, vinblastine, and colchicine: relation to vascular effects. Oncol Res 1997; 9: 55-60.
45. Puchalski T, Prabhakar U, Jiao Q, Berns B, Davis HM. Pharmacokinetic and pharmacodynamic modeling of an anti-interleukin-6 chimeric monoclonal antibody (siltuximab) in patients with metastatic renal cell carcinoma. Clin Cancer Res 2010; 16: 1652-61.
46. van Zaanen HC, Lokhorst HM, Aarden LA, et al. Chimaeric antiinterleukin 6 monoclonal antibodies in the treatment of advanced multiple myeloma: a phase I dose-escalating study. Br J Haematol 1998; 102: 783-90.
47. Duda DG, Ancukiewicz M, Jain RK. Biomarkers of Antiangiogenic Therapy: How Do We Move From Candidate Biomarkers to Valid Biomarkers?. J Clin Oncol 2010; 28(2): 183-5.
48. Jain RK. Normalization of tumor vasculature: an emerging concept in antiangiogenic therapy. Science 2005; 307: 58-62.
49. Kabbinavar FF, Hambleton J, Mass RD, Hurwitz HI, Bergsland E, Sarkar S. Combined analysis of efficacy: the addition of bevacizumab to fluorouracil/leucovorin improves survival for patients with metastatic colorectal cancer. J Clin Oncol 2005; 23: 3706-12.
50. Jain RK, Duda DG, Willett CG, et al. Biomarkers of response and resistance to antiangiogenic therapy. Nat Rev Clin Oncol 2009; 6: 327-38.
51. Jubb AM, Oates AJ, Holden S, Koeppen H. Predicting benefit from anti-angiogenic agents in malignancy. Nat Rev Cancer 2006; 6: 626-35.
52. De Primo SE, Bello C. Surrogate biomarkers in evaluating response to anti-angiogenic agents: focus on sunitinib. Ann Oncol Official J Eur Soc Med Oncol/ESMO 2007; 18 (Suppl 10): x11-19.
53. Hansson E, Houk B, Amantea M, Milligan P, Karlsson M, Friberg L. Pharmacokinetic-pharmacodynamic modeling of the angiogenic factors VEGF, sVEGFR-2, sVEGFR-3 and sKIT following sunitinib treatment in GIST. PAGE 18 (2009) Abstr 1521, 2009.
54. Ma G, Hansson E, Amantea M, Milligan P, Friberg L, Karlsson M. Correlations Between Fatigue, Hand-foot syndrome and the Angiogenic Factors VEGF, sVEGFR-2, sVEGFR-3 and sKIT in Patients Receiving Sunitinib. Am Conf Pharma 2009.
55. Lindauer A, Di Gion P, Kanefendt F, et al. Pharmacokinetic/ Pharmacodynamic modeling of biomarker response to sunitinib in healthy volunteers. Clin Pharmacol Ther 2010; 87: 601-8.
56. 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.
57. Bruno R, Claret L. On the use of change in tumor size to predict survival in clinical oncology studies: Toward a new paradigm to design and evaluate phase II studies. Clin Pharmacol Ther 2009; 86: 136-8.
58. Claret L, Girard P, Hoff PM, et al. Model-based prediction of phase III overall survival in colorectal cancer on the basis of phase II tumor dynamics. J Clin Oncol 2009; 27: 4103-8.
59. Sandler A, Gray R, Perry MC, et al. Paclitaxel-carboplatin alone or with bevacizumab for non-small-cell lung cancer. The New Eng J Med 2006; 355: 2542-50.
60. Shepherd FA, Rodrigues Pereira J, Ciuleanu T, et al. Erlotinib in previously treated non-small-cell lung cancer. The New Eng J Med 2005; 353: 123-32.
61. Bruno R, Lu J, Sun Y, Claret L. Simulation of survival with firstand second-line non-small cell lung cancer (NSCLC) therapy using a public domain drug-disease modeling framework. J Clin Oncol 2009; 27: 15s, (suppl; abstr 8087).
62. Hoff PM, Ansari R, Batist G, et al. Comparison of oral capecitabine versus intravenous fluorouracil plus leucovorin as first-line treatment in 605 patients with metastatic colorectal cancer: results of a randomized phase III study. J Clin Oncol Official J Am Soci Clin Oncol 2001; 19: 2282-92.
63. Claret L, Girard P, Zuideveld K, Jorga K, Fagerberg J, Bruno R. A longitudinal model for tumor size measurements in clinical oncology studies. PAGE 15 (2006) Abstr 1004 [www.pagemeeting.org/?abstract=1004], 15: 2006.
64. Lindbom L, Claret L, Andre V, Cleverly A, de Alwish D, Bruno R. A drug independent tumor size reduction-survival model in advanced ovarian cancer to support early clinical development decisions. American Conference of Pharmacometric 2009.
65. Claret L, Lu J, Sun Y, Stepan D, Bruno R. A modeling framework to simulate motesanib efficacy in thyroid cancer. J Clin Oncol 2009; 27: (suppl; abstr e14553).
66. Baselga J, Mendelsohn J. Receptor blockade with monoclonal antibodies as anti-cancer therapy. Pharmacol Ther 1994; 64: 127-54.
67. Baselga J, Pfister D, Cooper MR, et al. Phase I studies of antiepidermal growth factor receptor chimeric antibody C225 alone and in combination with cisplatin. J Clin Oncol 2000; 18, 904-14.
68. Luo FR, Yang Z, Dong H, et al. Prediction of active drug plasma concentrations achieved in cancer patients by pharmacodynamic biomarkers identified from the geo human colon carcinoma xenograft model. Clinl Cancer Res 2005; 11: 5558-65.
69. Daydé D, Ternant D, Ohresser M, et al. Tumor burden influences exposure and response to rituximab: pharmacokinetic-pharmacodynamic modeling using a syngeneic bioluminescent murine model expressing human CD20. Blood 2009; 113: 3765-72.
70. Berinstein NL, Grillo-López AJ, White CA, et al. Association of serum Rituximab (IDEC-C2B8) concentration and anti-tumor response in the treatment of recurrent low-grade or follicular non-Hodgkin's lymphoma. Ann Oncol 1998; 9: 995-1001.
71. LN Gordan, Grow WB, Pusateri A, Douglas V, Mendenhall NP, Lynch JW. Phase II trial of individualized rituximab dosing for patients with CD20-positive lymphoproliferative disorders. J Clin Oncol 2005; 23: 1096-102.
72. Sheiner LB, Steimer JL. Pharmacokinetic/pharmacodynamic modeling in drug development. Ann Rev Pharmacol Toxicol 2000; 40: 67-95.
73. Pillai GC, Mentré F, Steimer J. Non-linear mixed effects modeling- from methodology and software development to driving implementation in drug development science. J Pharmacokinet Pharmacodynamics 2005; 32: 161-83.
74. Orloff J, Douglas F, Pinheiro J, et al. The future of drug development: advancing clinical trial design. Nat Rev Drug Discov 2009; 8: 949-57.
75. Tan DSW, Thomas GV, Garrett MD, et al. Biomarker-driven early clinical trials in oncology: a paradigm shift in drug development. Cancer J 2009; 15: 406-20.
76. Takimoto CH. Pharmacokinetics and pharmacodynamic biomarkers in early oncology drug development. Eur J Cancer 2009; 45 (Suppl 1): 436-8.
77. Ibrahim JG, Chu H, Chen LM. Basic concepts and methods for joint models of longitudinal and survival data. J Clin Oncol 2010; 28: 2796-801.
78. Treiber G, Wex T, Schleyer E, Troeger U, Hosius C, Malfertheiner P. Imatinib for hepatocellular cancer-focus on pharmacokinetic/ pharmacodynamic modelling and liver function. Cancer Lett 2008; 260: 146-54.
79. Peng B, Hayes M, Resta D, et al. Pharmacokinetics and pharmacodynamics of imatinib in a phase I trial with chronic myeloid leukemia patients. J Clin Oncol 2004; 22: 935-42.
80. Koup JR, Liu J, Loi C, et al. PK/PD modeling of biomarker (p-ERK) response and tumor growth to PD 0325901 in a human tumor xenograft mouse model. AACR Meeting Abstracts, Maart 2004; 1248-b.
81. Lee L, Niu H, Rueger R, et al. The safety, tolerability, pharmacokinetics, and pharmacodynamics of single oral doses of CH4987655 in healthy volunteers: target suppression using a biomarker. Clin Cancer Res 2009; 15: 7368-74.
82. Ribba B, Watkin E, Tod M, et al. Combined analysis of tumor size data and histological biomarkers drives the development of a semimechanistic model of the effect of the antiangiogenic drug Sunitinib in mice. Abstr Ann Meeting Popul Appr Group Eur 2010; 19: 1801.
83. Wang X, Anak O, Saro J, et al. Population PK modeling and simulation to select a dosing schedule in Phase II trials for a novel TKI agent with time-dependent and nonlinear PK. PAGE 18 (2009) Abstr 1583 [www.page-meeting.org/?abstract=1583], 2009.
84. Beal SL, Sheiner L. NONMEM Users Guides, Ellicott City, Maryland, USA: Icon Development Solutions, 1989.
85. You B, Fronton L, Boyle H, et al. Predictive value of modeled AUC(AFP-hCG), a dynamic kinetic parameter characterizing serum tumor marker decline in patients with nonseminomatous germ cell tumor. Urology 2010; 76(2): 423-9.e.2.
86. Jonsson F, Claret L, Knight R, et al. A longitudinal tumor growth inhibition model based on serum m-protein levels in patients with multiple myeloma treated by dexamethasone. PAGE 19 (2010) Abstr 1705 [www.page-meeting.org/?abstract=1705], 2010.