BCIG SPEAKER EVENT:
“Application of Control Theory and Machine Learning to Drug Dose Determination”
Clinical
Center (Building 10) Medical Board Room (Room 2C116)
- view the seminar archive
ABSTRACT: Effective pharmacologic management of chronic illnesses
poses a challenge to physicians due to variable drug response within patient
population. Individualized, patient-specific strategies for drug dose
determination are one of the keys to achieving better treatment outcomes. In
this talk, we address the problem of drug dosing individualization from a
control theoretic and machine learning point of view. We present the application
of model-based (Model Predictive Control) and model-free (Reinforcement
Learning) techniques to treatment of chronic illness, using anemia of End Stage
Renal Disease as an example. We demonstrate both methods using simulation
examples and results from recent clinical trials.
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3:00 - 5:00 pm March 13, 2008
Adam E. Gaweda, Ph.D.
Adam E. Gaweda received the M.Eng. degree in Electrical Engineering from
Czestochowa University of Technology, Poland, and the Ph.D. degree in Computer
Science and Engineering from University of Louisville, Louisville, KY, in 1997
and 2002, respectively. In 2002 he joined the Department of Medicine, Division
of Nephrology, University of Louisville, where he currently holds the position
of Assistant Professor. Currently, he is working toward Master's degree in
Clinical Investigative Sciences. His research interests focus on application of
computational intelligence and adaptive control to pharmacokinetic/pharmacodynamic
modeling, treatment planning and delivery.
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