Improving Drug Repurposing Success by Predicting Correct Dosage

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Researchers from Penn State have developed a model that can predict the effective dosage of repurposed drugs, potentially improving the success rate of drug repurposing efforts. Repurposing already-approved drugs for new therapeutic uses can save time and money compared to developing novel drugs from scratch. However, the researchers found that the success rate of repurposing drugs is about the same as that of developing new drugs in clinical trials.

The researchers, led by corresponding author Justin R. Pritchard, Associate Professor of Biomedical Engineering at Penn State, published their findings in Cell Reports Medicine. Pritchard stated that the advantage of repurposing drugs is that they have already been proven safe for use in patients. However, upon analyzing the data, the researchers found that the success rate of repurposing drugs is not significantly higher than that of developing new drugs.

One of the main reasons for the low success rate of repurposing drugs, according to co-author Scott M. Leighow, a doctoral researcher in biomedical engineering at Penn State, is the difficulty in determining the appropriate dosage during preliminary testing. Researchers often test drugs on isolated cells in a dish and administer a higher concentration than would be feasible for a patient. Additionally, cells in a dish may behave differently than cells in a patient’s body, surrounded by proteins and tissues.

To address this issue, the Penn State researchers developed a computer model using existing data on the performance of a leukemia drug in real patients. They then incorporated their own experimental data on drug-disease interactions at different concentrations in isolated cells and cells immersed in a solution of sticky proteins, similar to those found in blood. By comparing the percentage of the drug that reached the target cancer cells in tests with and without sticky proteins, they calculated a serum shift factor. This factor could be multiplied by the concentration of the drug in a patient’s blood sample to obtain a corrected concentration.

The researchers found that this corrected concentration, which they referred to as effective drug exposure in a patient, is a good predictor of how well the drug performs in a specific disease context. They established a threshold based on this number, which distinguishes whether a drug is clinically efficacious or not. Interestingly, the same threshold performed well in predicting drug efficacy in different diseases such as lung cancer and gastrointestinal stromal tumors.

According to Leighow, the model could be used not only for determining effective doses of repurposed drugs but also for designing new drugs in a similar class. The researchers believe that considering this broader biological context during drug development could lead to more accurate predictions of drug efficacy.

Overall, predicting the correct dosage for repurposed drugs could significantly improve the success rate of drug repurposing efforts and streamline the process of finding new therapeutic options for various diseases. The Penn State researchers’ model provides a valuable tool for researchers and pharmaceutical companies seeking to repurpose drugs or develop new drugs more efficiently.

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1. Source: Coherent Market Insights, Public sources, Desk research
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