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*Statistical methods for clinical trials to support Personalized Medicine:*

*Application to Heterogeneity in patient population*


 *Sandrine Katsahian*


 *Department of Biostatistics and Clinical Research*

*Mondor Hospital*


 *Engr 4201 (CS conference room)*

*4400 University Drive, Fairfax, VA 22030*

*Time: **11**:**0**0 **A**.M. - **12**:**0**0 **P**.M.*

*Date: **Friday**, **Mar 21**, 201**4*



*Abstract*

Personalized medicine allows the extensive use of information about a
person's genes, proteins, and environment to prevent, diagnose, and treat
disease. The objectives of personalized medicine include:

*    Predict individual susceptibility to disease based on genetic and
other factors;

*    Provide more useful and individualized approaches for preventing
disease, based on knowledge of individual susceptibility;

*    Detect the onset of disease at the earliest moments, based on
identified biomarkers that arise from changes at the molecular level;

*    Pre-empt the progression of disease, as a result of early detection;
and

*    Select and optimize medicines and dosages more precisely and safely to
each patient.



In this context, heterogeneity in patient population with respect to
clinical and histological characteristics, patient context, and genes that
are over or under-expressed, must be taken into account. The most common
hereditary cancers include breast cancer, ovarian cancer, prostate cancer
and colorectal cancer. For example, BRCA1 and BRCA2 are human genes that
belong to a class of genes known as tumor suppressors. Mutation of these
genes has been linked to hereditary breast and ovarian cancer.



To address heterogeneity among patients, we need better annotation of
phenotype data, shared representation of patient characteristics, as well
as precise and formal description of patient information stored in clinical
data-warehouse along with sophisticated methods to validate biomarkers to
be used in clinical trial design and take the whole spectrum of data
characteristics in study design and patient care.

Statistical methods for clinical trials will be applied to the Clinical
Data Warehouse in Hôpital Européen Georges Pompidou (HEGP), Paris.



Dr. Katsahian is currently a visiting associate professor at the Department
of Statistics, George Mason University.


-- 
Yunpeng Zhao, PhD

Assistant Professor
Department of Statistics
Volgenau School of Engineering <[log in to unmask]>
George Mason University
Engineering Building, Room 1719, MS 4A7
4400 University Drive
Fairfax, VA 22030-4444

Phone: 703-993-1674
Email: [log in to unmask]