Discovering a Better Way to Determine What Drug Dose is Right for You

Principal Investigators: John VanMeter, PhD, Christopher Albanese, PhD, and Valeriy Korostyshevskiy, PhD

One goal of personalized medical care is matching each patient with the optimal dose of a prescription drug to maximize therapeutic response while minimizing unintended consequences. This project will combine the power of magnetic resonance imaging (MRI) with computer models of how the body processes medications in order to determine the effectiveness of a drug on an individualized basis. Radical transformation of the current trial-and-error method of determining the dose of a medication given each individual patient is the goal. Based on personalized information about how the individual patient’s body is responding to medication by using sophisticated imaging technologies to measure changes, this project aims at saving lives and enhancing public health by creating safer ways to dose medicine,

A novel technology will be developed to provide not only faster assessment of treatment outcome but, even more important, provide information about how the drug functions in the individual patient. Recently, we have shown that a type of MRI called MR Spectroscopy (MRS) can be used to measure drug efficacy through changes in various chemicals, which cannot be measured from the blood. However, challenges remain in imaging drug action related to the limitations of MRS to measure all of the chemicals related to the drug.

Our technology will combine the unique ability of MRS to measure chemicals internally with known information about how the body processes chemicals using computer models. We hypothesize that we can use this technology to quantify not only the changes in key chemicals that can be measured but also those that cannot be measured but still are important markers of drug sensitivity. Using this technology, we can quantify efficacy, mechanism of action, and changes in the patient – all factors that lead to a better understanding of the disease and the effectiveness of drugs to treat the disease.

Two tests will demonstrate the power of this technology. First, we will measure the effectiveness of prozac or similar drugs in newly diagnosed patients, comparing our results with treatment outcomes. Second, we will use a mouse model of pediatric cancer to measure the effectiveness of a novel cancer drug. Together these tests will show the capabilities of this technology to measure the dosage effectiveness of a well-known drug and the way a new drug treatment works.