A Quantitative Process for Enhancing End of Phase 2 Decisions

被引:20
作者
Sabin, Tony [1 ,2 ]
Matcham, James [3 ]
Bray, Sarah [1 ]
Copas, Andrew [2 ]
Parmar, Mahesh K. B. [2 ]
机构
[1] Amgen Ltd, Cambridge, England
[2] UCL, MRC, Clin Trials Unit, London, England
[3] AstraZeneca Ltd, Macclesfield, Cheshire, England
来源
STATISTICS IN BIOPHARMACEUTICAL RESEARCH | 2014年 / 6卷 / 01期
关键词
Decision making; Pancreatic cancer; Probability of success; CLINICAL-TRIAL; DRUG DEVELOPMENT; SURVIVAL;
D O I
10.1080/19466315.2013.852617
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The objectives of the phase 2 stage in a drug development program are to evaluate the safety and tolerability of different doses, select a promising dose range, and look for early signs of activity. At the end of phase 2, a decision to initiate phase 3 studies is made that involves the commitment of considerable resources. This multifactorial decision, generally made by balancing the current condition of a development organization's portfolio, the future cost of development, the competitive landscape, and the expected safety and efficacy benefits of a new therapy, needs to be a good one. In this article, we present a practical quantitative process that has been implemented for drugs entering phase 2 at Amgen Ltd. to ensure a consistent and explicit evidence-based approach is used to contribute to decisions for new drug candidates. Broadly following this process will also help statisticians increase their strategic influence in drug development programs. The process is illustrated using an example from the pancreatic cancer indication. Embedded within the process is a predominantly Bayesian approach to predicting the probability of efficacy success in a future (frequentist) phase 3 program.
引用
收藏
页码:67 / 77
页数:11
相关论文
共 20 条
  • [1] Phase II failures: 2008-2010
    Arrowsmith, John
    [J]. NATURE REVIEWS DRUG DISCOVERY, 2011, 10 (05) : 1 - 1
  • [2] TRIAL WATCH Phase III and submission failures: 2007-2010
    Arrowsmith, John
    [J]. NATURE REVIEWS DRUG DISCOVERY, 2011, 10 (02) : 1 - 1
  • [3] DiMasi J. A., 2012, CLIN PHARMACOL THER, V87, P272
  • [4] Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves
    Guyot, Patricia
    Ades, A. E.
    Ouwens, Mario J. N. M.
    Welton, Nicky J.
    [J]. BMC MEDICAL RESEARCH METHODOLOGY, 2012, 12
  • [5] Higgins J, 2011, COCHRANE HDB SYSTEMA, DOI DOI 10.1002/9780470712184
  • [6] Predictive power to assist phase 3 go/no go decision based on phase 2 data on a different endpoint
    Hong, Shengyan
    Shi, Li
    [J]. STATISTICS IN MEDICINE, 2012, 31 (09) : 831 - 843
  • [7] Discounting phase 2 results when planning phase 3 clinical trials
    Kirby, S.
    Burke, J.
    Chuang-Stein, C.
    Sin, C.
    [J]. PHARMACEUTICAL STATISTICS, 2012, 11 (05) : 373 - 385
  • [8] Can the pharmaceutical industry reduce attrition rates?
    Kola, I
    Landis, J
    [J]. NATURE REVIEWS DRUG DISCOVERY, 2004, 3 (08) : 711 - 715
  • [9] How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS
    Lambert, PC
    Sutton, AJ
    Burton, PR
    Abrams, KR
    Jones, DR
    [J]. STATISTICS IN MEDICINE, 2005, 24 (15) : 2401 - 2428
  • [10] Moher D, 2009, ANN INTERN MED, V151, P264, DOI [10.7326/0003-4819-151-4-200908180-00135, 10.1136/bmj.b2700, 10.1371/journal.pmed.1000097, 10.1136/bmj.i4086, 10.1016/j.ijsu.2010.02.007, 10.1016/j.ijsu.2010.07.299, 10.1136/bmj.b2535, 10.1186/2046-4053-4-1]