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New Computational Equation To Better Predict Drug-Drug Interactions

A joint research team of mathematicians and pharmacological scientists has identified the major causes of inaccuracies in the Food and Drug Administration’s (FDA) equation for predicting drug-drug interactions and presented solutions.

They found that the FDA’s equation, based on the 110-year-old Michaelis-Menten (MM) model, was only accurate 38% of the time. The MM model is only accurate when the concentration of the enzyme that metabolizes the drug is much lower than its MM constant (Km). Furthermore, the MM equation is expected to be highly inaccurate when enzyme concentration is increased by drug-drug interaction.

The conventional equation recommended by the FDA guidance (upper) and the newly derived equation (lower) for predicting drug-drug interaction. Credit: Institute for Basic Science

To re-calculate gut bioavailability (Fg), the research team used an “estimated Fa” value based on factors such as the drug’s transit time, intestine radius, and permeability values. Unlike the MM equation, they also used an alternative model that can more accurately predict the drug metabolism rate regardless of the enzyme concentration. Combining these changes, the modified equation with re-calculated Fg dramatically increased accuracy by about 80%.

Citations: Vu, N.-A.T., Song, Y.M., Tran, Q.T., Yun, H.-y., Kim, S.K., Chae, J.-w. and Kim, J.K. (2023), Beyond the Michaelis–Menten: Accurate Prediction of Drug Interactions through Cytochrome P450 3A4 Induction. Clin Pharmacol Ther.

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