Advertisement

How to Design Phase I Trials in Oncology

  • Louise Carter
  • Ciara O’Brien
  • Emma Dean
  • Natalie Cook
Chapter

Abstract

Phase 1 trials allow the assessment of the safety, tolerability and proof of mechanism of an investigational medical product (IMP), in monotherapy and in combination, in human trial participants. To achieve these objectives, preclinical data, trial design methodology and dose selection should be carefully considered and assimilated. In the following chapter the fundamental principles of phase 1 trial design will be outlined.

Keywords

Phase I Experimental medicine Oncology Trial design 

References

  1. 1.
    US FDA (Editor). Guidance for industry estimating the maximum safe starting dose in initial clinical trials for therapeutics in adult healthy volunteers. Silver Spring, MD: US FDA; 2005.Google Scholar
  2. 2.
    Janne PA, et al. AZD9291 in EGFR inhibitor-resistant non-small-cell lung cancer. N Engl J Med. 2015;372(18):1689–99.CrossRefPubMedGoogle Scholar
  3. 3.
    Storer BE. Design and analysis of phase I clinical trials. Biometrics. 1989;45(3):925–37.CrossRefPubMedGoogle Scholar
  4. 4.
    Ji Y, et al. A modified toxicity probability interval method for dose-finding trials. Clin Trials. 2010;7(6):653–63.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Babb J, Rogatko A, Zacks S. Cancer phase I clinical trials: efficient dose escalation with overdose control. Stat Med. 1998;17(10):1103–20.CrossRefPubMedGoogle Scholar
  6. 6.
    Adaptive Designs Working Group of the MRC Network of Hubs For Trials Methodology Research “a quick guide why not to use A+B designs”. http://www.methodologyhubs.mrc.ac.uk/files/6814/6253/2385/A_quick_guide_why_not_to_use_AB_designs.pdf.
  7. 7.
    Tighiouart, M. and A. Rogatko, Dose finding with escalation with overdose control (EWOC) in cancer clinical trials. Stat Sci. 2010;(2):217–226.CrossRefGoogle Scholar
  8. 8.
    Ji Y, Wang SJ. Modified toxicity probability interval design: a safer and more reliable method than the 3 + 3 design for practical phase I trials. J Clin Oncol. 2013;31(14):1785–91.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Yin G, Zheng S, Xu J. Fractional dose-finding methods with late-onset toxicity in phase I clinical trials. J Biopharm Stat. 2013;23(4):856–70.CrossRefPubMedGoogle Scholar
  10. 10.
    EMEA (Editor). Guideline on strategies to identify and mitigate risks for first-in-human and early clinical trials with investigational medicinal products. London: EMEA; 2016.Google Scholar
  11. 11.
    US FDA (Editor). Guidance for industry S9 nonclinical evaluation for anticancer pharmaceuticals. Silver Spring, MD: US FDA; 2010.Google Scholar
  12. 12.
    Le Tourneau C, et al. Choice of starting dose for molecularly targeted agents evaluated in first-in-human phase I cancer clinical trials. J Clin Oncol. 2010;28(8):1401–7.CrossRefPubMedGoogle Scholar
  13. 13.
    Hansen AR, et al. Choice of starting dose for biopharmaceuticals in first-in-human phase I cancer clinical trials. Oncologist. 2015;20(6):653–9.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Wong KM, Capasso A, Eckhardt SG. The changing landscape of phase I trials in oncology. Nat Rev Clin Oncol. 2016;13(2):106–17.CrossRefPubMedGoogle Scholar
  15. 15.
    Elisei R, et al. Cabozantinib in progressive medullary thyroid cancer. J Clin Oncol. 2013;31(29):3639–46.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Sachs JR, et al. Optimal dosing for targeted therapies in oncology: drug development cases leading by example. Clin Cancer Res. 2016;22(6):1318–24.CrossRefPubMedGoogle Scholar
  17. 17.
    Hughes A, et al. Development and evaluation of a new technological way of engaging patients and enhancing understanding of drug tolerability in early clinical development: PROACT. Adv Ther. 2016;33(6):1012–24.CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Landers D. Technology – making trials simpler. Early phase workshop delivery of early phase oncology trials: how can we excel? London: CRUK Center for Drug Development; 2017.Google Scholar
  19. 19.
    Yeo WL, et al. Erlotinib at a dose of 25 mg daily for non-small cell lung cancers with EGFR mutations. J Thorac Oncol. 2010;5(7):1048–53.CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Binder D, et al. Erlotinib in patients with advanced non-small-cell lung cancer: impact of dose reductions and a novel surrogate marker. Med Oncol. 2012;29(1):193–8.CrossRefPubMedGoogle Scholar
  21. 21.
    Tol J, et al. Chemotherapy, bevacizumab, and cetuximab in metastatic colorectal cancer. N Engl J Med. 2009;360(6):563–72.CrossRefPubMedGoogle Scholar
  22. 22.
    Sandler A, et al. Paclitaxel-carboplatin alone or with bevacizumab for non-small-cell lung cancer. N Engl J Med. 2006;355(24):2542–50.CrossRefPubMedGoogle Scholar
  23. 23.
    Gianni L, et al. AVEREL: a randomized phase III Trial evaluating bevacizumab in combination with docetaxel and trastuzumab as first-line therapy for HER2-positive locally recurrent/metastatic breast cancer. J Clin Oncol. 2013;31(14):1719–25.CrossRefPubMedGoogle Scholar
  24. 24.
    Rini BI, et al. Phase III trial of bevacizumab plus interferon alfa versus interferon alfa monotherapy in patients with metastatic renal cell carcinoma: final results of CALGB 90206. J Clin Oncol. 2010;28(13):2137–43.CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Ang JE, Kaye S, Banerji U. Tissue-based approaches to study pharmacodynamic endpoints in early phase oncology clinical trials. Curr Drug Targets. 2012;13(12):1525–34.CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Gerlinger M, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med. 2012;366(10):883–92.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Cook N, et al. Early phase clinical trials to identify optimal dosing and safety. Mol Oncol. 2015;9(5):997–1007.CrossRefPubMedGoogle Scholar
  28. 28.
    Hunsberger S, et al. Dose escalation trial designs based on a molecularly targeted endpoint. Stat Med. 2005;24(14):2171–81.CrossRefPubMedGoogle Scholar
  29. 29.
    Mandrekar SJ, Cui Y, Sargent DJ. An adaptive phase I design for identifying a biologically optimal dose for dual agent drug combinations. Stat Med. 2007;26(11):2317–30.CrossRefPubMedGoogle Scholar
  30. 30.
    Polley MY, Cheung YK. Two-stage designs for dose-finding trials with a biologic endpoint using stepwise tests. Biometrics. 2008;64(1):232–41.CrossRefPubMedGoogle Scholar
  31. 31.
    Goulart BH, et al. Trends in the use and role of biomarkers in phase I oncology trials. Clin Cancer Res. 2007;13(22 Pt 1):6719–26.CrossRefPubMedGoogle Scholar
  32. 32.
    Jardim DL, et al. Predictive value of phase I trials for safety in later trials and final approved dose: analysis of 61 approved cancer drugs. Clin Cancer Res. 2014;20(2):281–8.CrossRefPubMedGoogle Scholar
  33. 33.
    Mok TS, et al. Osimertinib or platinum-pemetrexed in EGFR T790M-positive lung cancer. N Engl J Med. 2017;376(7):629–40.CrossRefPubMedGoogle Scholar
  34. 34.
    Von Hoff DD, et al. Pilot study using molecular profiling of patients' tumors to find potential targets and select treatments for their refractory cancers. J Clin Oncol. 2010;28(33):4877–83.CrossRefGoogle Scholar
  35. 35.
    Manji A, et al. Evolution of clinical trial design in early drug development: systematic review of expansion cohort use in single-agent phase I cancer trials. J Clin Oncol. 2013;31(33):4260–7.CrossRefPubMedGoogle Scholar
  36. 36.
    Sherman RE, et al. Expediting drug development—the FDA's new “breakthrough therapy” designation. N Engl J Med. 2013;369(20):1877–80.CrossRefPubMedGoogle Scholar
  37. 37.
    Kramer DB, Kesselheim AS. User fees and beyond—the FDA Safety and Innovation Act of 2012. N Engl J Med. 2012;367(14):1277–9.CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Kesselheim AS, Darrow JJ. FDA designations for therapeutics and their impact on drug development and regulatory review outcomes. Clin Pharmacol Ther. 2015;97(1):29–36.CrossRefPubMedGoogle Scholar
  39. 39.
    Hamid O, et al. Safety and tumor responses with lambrolizumab (anti-PD-1) in melanoma. N Engl J Med. 2013;369(2):134–44.CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Trippa L, Alexander BM. Bayesian Baskets: a novel design for biomarker-based clinical trials. J Clin Oncol. 2017;35:PMID: 28045624.CrossRefGoogle Scholar
  41. 41.
    Sleijfer S, Bogaerts J, Siu LL. Designing transformative clinical trials in the cancer genome era. J Clin Oncol. 2013;31(15):1834–41.CrossRefPubMedGoogle Scholar
  42. 42.
    Project GENIE goes public. Cancer Discov. 2017;7(2):118.Google Scholar
  43. 43.
    Hyman DM, et al. Vemurafenib in multiple nonmelanoma cancers with BRAF V600 mutations. N Engl J Med. 2015;373(8):726–36.CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    McNeil C. NCI-MATCH launch highlights new trial design in precision-medicine era. J Natl Cancer Inst. 2015;107(7):pii: djv193.CrossRefGoogle Scholar
  45. 45.
    Herbst RS, et al. Lung master protocol (lung-MAP)–a biomarker-driven protocol for accelerating development of therapies for squamous cell lung cancer: SWOG S1400. Clin Cancer Res. 2015;21(7):1514–24.CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Chabner BA, Roberts TG Jr. Timeline: chemotherapy and the war on cancer. Nat Rev Cancer. 2005;5(1):65–72.CrossRefPubMedGoogle Scholar
  47. 47.
    Audeh MW, et al. Oral poly(ADP-ribose) polymerase inhibitor olaparib in patients with BRCA1 or BRCA2 mutations and recurrent ovarian cancer: a proof-of-concept trial. Lancet. 2010;376(9737):245–51.CrossRefPubMedGoogle Scholar
  48. 48.
    Gao S, et al. Applications of RNA interference high-throughput screening technology in cancer biology and virology. Protein Cell. 2014;5(11):805–15.CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    Day D, Siu LL. Approaches to modernize the combination drug development paradigm. Genome Med. 2016;8(1):115.CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Gao H, et al. High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response. Nat Med. 2015;21(11):1318–25.CrossRefPubMedGoogle Scholar
  51. 51.
    Mathews Griner LA, et al. High-throughput combinatorial screening identifies drugs that cooperate with ibrutinib to kill activated B-cell-like diffuse large B-cell lymphoma cells. Proc Natl Acad Sci U S A. 2014;111(6):2349–54.CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Iorns E, et al. Utilizing RNA interference to enhance cancer drug discovery. Nat Rev Drug Discov. 2007;6(7):556–68.CrossRefPubMedGoogle Scholar
  53. 53.
    Keith CT, Borisy AA, Stockwell BR. Multicomponent therapeutics for networked systems. Nat Rev Drug Discov. 2005;4(1):71–8.CrossRefPubMedGoogle Scholar
  54. 54.
    Paller CJ, et al. Design of phase I combination trials: recommendations of the Clinical Trial Design Task Force of the NCI Investigational Drug Steering Committee. Clin Cancer Res. 2014;20(16):4210–7.CrossRefPubMedPubMedCentralGoogle Scholar
  55. 55.
    Thall PF, et al. Dose-finding with two agents in phase I oncology trials. Biometrics. 2003;59(3):487–96.CrossRefPubMedGoogle Scholar
  56. 56.
    Huang X, et al. A parallel phase I/II clinical trial design for combination therapies. Biometrics. 2007;63(2):429–36.CrossRefPubMedGoogle Scholar
  57. 57.
    Yuan Y, Yin G. Sequential continual reassessment method for two-dimensional dose finding. Stat Med. 2008;27(27):5664–78.CrossRefPubMedGoogle Scholar
  58. 58.
    Yin G, Li Y, Ji Y. Bayesian dose-finding in phase I/II clinical trials using toxicity and efficacy odds ratios. Biometrics. 2006;62(3):777–84.CrossRefPubMedGoogle Scholar
  59. 59.
    Polley MY. Practical modifications to the time-to-event continual reassessment method for phase I cancer trials with fast patient accrual and late-onset toxicities. Stat Med. 2011;30(17):2130–43.CrossRefPubMedPubMedCentralGoogle Scholar
  60. 60.
    Riviere MK, et al. Designs of drug-combination phase I trials in oncology: a systematic review of the literature. Ann Oncol. 2015;26(4):669–74.CrossRefPubMedGoogle Scholar
  61. 61.
    Osborne CK, Kitten L, Arteaga CL. Antagonism of chemotherapy-induced cytotoxicity for human breast cancer cells by antiestrogens. J Clin Oncol. 1989;7(6):710–7.CrossRefPubMedGoogle Scholar
  62. 62.
    Yap TA, Omlin A, de Bono JS. Development of therapeutic combinations targeting major cancer signaling pathways. J Clin Oncol. 2013;31(12):1592–605.CrossRefPubMedGoogle Scholar
  63. 63.
    Al-Lazikani B, Banerji U, Workman P. Combinatorial drug therapy for cancer in the post-genomic era. Nat Biotechnol. 2012;30(7):679–92.CrossRefPubMedGoogle Scholar
  64. 64.
    Blomme EA, Will Y. Toxicology strategies for drug discovery: present and future. Chem Res Toxicol. 2016;29(4):473–504.CrossRefPubMedGoogle Scholar
  65. 65.
    Bedard PL, et al. A phase Ib dose-escalation study of the oral pan-PI3K inhibitor buparlisib (BKM120) in combination with the oral MEK1/2 inhibitor trametinib (GSK1120212) in patients with selected advanced solid tumors. Clin Cancer Res. 2015;21(4):730–8.CrossRefPubMedGoogle Scholar
  66. 66.
    Postel-Vinay S, et al. Challenges of phase 1 clinical trials evaluating immune checkpoint-targeted antibodies. Ann Oncol. 2016;27(2):214–24.CrossRefPubMedGoogle Scholar
  67. 67.
    de Jonge MJ, et al. Phase I and pharmacokinetic study of pazopanib and lapatinib combination therapy in patients with advanced solid tumors. Investig New Drugs. 2013;31(3):751–9.CrossRefGoogle Scholar
  68. 68.
    Reardon DA, et al. A phase I/II trial of pazopanib in combination with lapatinib in adult patients with relapsed malignant glioma. Clin Cancer Res. 2013;19(4):900–8.CrossRefPubMedGoogle Scholar
  69. 69.
    Larkin J, et al. Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N Engl J Med. 2015;373(1):23–34.CrossRefPubMedPubMedCentralGoogle Scholar
  70. 70.
    Rodon J, et al. Challenges in initiating and conducting personalized cancer therapy trials: perspectives from WINTHER, a Worldwide Innovative Network (WIN) Consortium trial. Ann Oncol. 2015;26(8):1791–8.CrossRefPubMedPubMedCentralGoogle Scholar
  71. 71.
    Schilsky RL. Implementing personalized cancer care. Nat Rev Clin Oncol. 2014;11(7):432–8.CrossRefPubMedGoogle Scholar
  72. 72.
    Hay M, et al. Clinical development success rates for investigational drugs. Nat Biotechnol. 2014;32(1):40–51.CrossRefPubMedGoogle Scholar
  73. 73.
    DiMasi JA, Grabowski HG. Economics of new oncology drug development. J Clin Oncol. 2007;25(2):209–16.CrossRefPubMedGoogle Scholar
  74. 74.
    Le Tourneau C, et al. Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer (SHIVA): a multicentre, open-label, proof-of-concept, randomised, controlled phase 2 trial. Lancet Oncol. 2015;16(13):1324–34.CrossRefPubMedGoogle Scholar
  75. 75.
    Kim ES, et al. The BATTLE trial: personalizing therapy for lung cancer. Cancer Discov. 2011;1(1):44–53.CrossRefPubMedPubMedCentralGoogle Scholar
  76. 76.
    Middleton G, et al. The National Lung Matrix Trial: translating the biology of stratification in advanced non-small-cell lung cancer. Ann Oncol. 2015;26(12):2464–9.PubMedPubMedCentralGoogle Scholar
  77. 77.
    Topalian SL, et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 2012;366(26):2443–54.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Louise Carter
    • 1
    • 2
  • Ciara O’Brien
    • 1
  • Emma Dean
    • 1
    • 2
    • 3
  • Natalie Cook
    • 1
    • 2
  1. 1.The Christie NHS Foundation TrustManchesterUK
  2. 2.Division of Cancer Sciences, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
  3. 3.Early Clinical Development, Oncology Translational Medicine UnitAstra ZenecaMelbournUK

Personalised recommendations