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SUMMARY:Biomarker-based Bayesian Adaptive Designs for Targeted Agent Devel
 opment - Implementation and Lessons Learned from the BATTLE Trial - Lee\, 
 J (MD Anderson Cancer Center)
DTSTART:20110815T130000Z
DTEND:20110815T134500Z
UID:TALK32346@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Advances in biomedicine have fueled the development of targete
 d agents in cancer therapy. Targeted therapies have shown to be more effic
 acious and less toxic than the conventional chemotherapies. Targeted thera
 pies\, however\, do not work for all patients. One major challenge is to i
 dentify markers for predicting treatment efficacy. We have developed bioma
 rker-based Bayesian adaptive designs to (1) identify prognostic and predic
 tive markers for targeted agents\, (2) test treatment efficacy\, and (3) p
 rovide better treatments for patients enrolled in the trial. In contrast t
 o the frequentist equal randomization designs\, Bayesian adaptive randomiz
 ation designs allow treating more patients with effective treatments\, mon
 itoring the trial more frequently to stop ineffective treatments early\, a
 nd increasing efficiency while controlling type I and type II errors. Baye
 sian adaptive design can be more efficient\, more ethical\, and more flexi
 ble in the study conduct than standard design s. We have recently complete
 d a biopsy-required\, biomarker-driven lung cancer trial\, BATTLE\, for ev
 aluating four targeted treatments. Lessons learned from the design\, condu
 ct\, and analysis of this Bayesian adaptive design will be given. \n
LOCATION:Seminar Room 2\, Newton Institute Gatehouse
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