Degree: Ph.D., Chemical Engineering
Advisor: Christos Georgakis
Research Project: Developing Patient Specific Pharmacokinetic Models: Deterministic and Stochastic Approaches in Population Pharmacokinetics

Project Description:
Prior population pharmacokinetic (PPK) modeling approaches have found  limited success in developing dynamic models that accurately describe  the variability that is observed in pharmacokinetic (PK) behavior  among a target population. Many patient specific characteristics, for example, age, weight, or gender, are thought to be the significant factors that cause such variability between the individuals of the population. It is likely that such factors may be found to have significant contribution to the variability of PK behavior that is observed in a single patient over time. The overall goal of this research is to formulate a semi-empirically based PK modeling methodology that will enable one to appropriately account for such types of PK variability that is observed in PK data sets.

The success of such research presents several major benefits to the field of pharmaceutical therapy:
1) the ability to optimize the administration of therapeutic drugs for patients on an individual basis, 2) acceleration and advancement of the ability to predict the PK properties of drug candidates undergoing clinical trials with a high level of certainty, and 3) gaining insight that will advance the knowledge of the physiological processes that govern PK behavior in hopes of leading to further innovation in the field of pharmaceutical therapy.

In order to develop such a methodology, an in depth knowledge of the relevant PK analysis techniques (deterministic & stochastic modeling techniques, parameter estimation, statistical inference) and understanding of the physiological processes relevant to drug adsorption, distribution, metabolism, and excretion (ADME) kinetics is required to deduce which patient characteristics are significant and how to appropriately incorporate such parameters into the development of novel PK models.

Education & Experience:
B.S. (cum laude) in Chemical Engineering, 2006 University of Massachusetts, Amherst

B.S. (cum laude) in Biochemistry and Molecular Biology, 2006 University of Massachusetts, Amherst

Funding:
Tufts University

Graduate Students:

Fernando Lima
Foteini Makrydaki
Praveen Prasanna
Lisa Schupmann
Sze Wing Wong