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Devidas, Meenakshi

RC_20140825_UF_Biostats_Faculty_0027Research Professor

Office:  6011 NW 1st Place
Phone:  352-273-0551
Fax:  352-392-8162
Email:  mdevidas@cog.ufl.edu

Department of Biostatistics
Children’s Oncology Group
Department of Biostatistics
6011 NW 1st Place
Gainesville, FL 32607-2025

Education:

  • PhD, University of Memphis, Memphis, TN (Major: Applied Statistics, Minor: Computer Science)
  • MS, University of Memphis, Memphis, TN (Major: Applied Statistics)
  • MBA, Bangalore University, Bangalore, India (Major: Marketing Management)
  • BS, Bangalore University, Bangalore, India (Majors: Mathematics, Physics, and Chemistry)

Curriculum Vitae

Professional Biography

Meenakshi Devidas is the PI of the grant for the branch of the Children’s Oncology Group Statistics and Data Center located at the University of Florida. She is the Lead Statistician for the disease area of Acute Lymphoblastic Leukemia (ALL) and resource statistician for Bone tumors (Ewing Sarcoma and Osteosarcoma). In this role, she is responsible for reviewing concept proposals, trial design, sample size calculations, and developing / implementing safety and efficacy monitoring rules for new clinical trials in these disease areas. She is co-investigator on several NIH grants looking at prognostic significance of minimal residual disease and the biology of ALL in children. Her methodological research has focused on statistical issues related to the design and conduct of clinical trials, and the modeling of dose-response curves. Designing randomized comparative trials in disease areas with very low annual accruals is problematic. Dr. Devidas developed methodology for sample size estimations in Phase II and pilot trials where data from a completed or ongoing study (historical controls) may be effectively used in the design and analysis of a new comparative study. She proposed a method that allows an optimal proportion of the new sample also, to be allocated to the control group, while the rest are assigned to the experimental group. This method results in a substantially smaller total sample size than is required for a two-arm completely randomized study. The outcome of interest in the trials could be response rates or survival rates. Current research includes efficient two-stage designs for Phase II trials which need to be monitored for insufficient activity (low response rates) and/or excessive early disease progression rates.

Expertise

  • Clinical Trials Design
  • Statistical Applications to Clinical Trials
  • Survival Analysis
  • Group Sequential Methods
  • Generalized Linear Models
  • Dose-Response Modeling