7.27
Noncompartmental Analysis: Mean Residence Time
According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean…
According to statistical moment theory, mean residence time is the expected mean of a probability density function distribution. It can also be viewed from the perspective of drug disposition in the body.
After an intravenous bolus administration, drug molecules are distributed and reside in the body for different periods.
Mean residence time describes the average time the drug molecules stay in the body.
It can be calculated from the area under the moment-versus-time curve, AUMC, and the area under the concentration-versus-time curve, AUC, from zero to infinity.
AUMC can be extrapolated to infinity from a given point, assuming a log-linear terminal phase.
However, AUMC can only be calculated after a single-dose administration and not at steady-state conditions.
As a result, mean residence time can be readily computed after a single drug dose using the noncompartmental approach
View the full transcript and gain access to JoVE Core videos
Q1: What is mean residence time in pharmacokinetics?
Mean residence time (MRT) is the expected mean of a probability density function distribution that describes the average time drug molecules stay in the body after administration. According to statistical moment theory, MRT provides valuable insights into drug disposition by quantifying how long a drug remains present in the system following an intravenous bolus injection.
Q2: How is mean residence time calculated from pharmacokinetic data?
Mean residence time is calculated using the ratio of the area under the moment-versus-time curve (AUMC) to the area under the concentration-versus-time curve (AUC), both integrated from zero to infinity. Since infinite measurement is impossible, a log-linear terminal phase assumption extrapolates AUMC to infinity from a given point, enabling accurate MRT computation.
Q3: Why can mean residence time only be calculated after single-dose administration?
Mean residence time calculation is limited to single-dose administration because the mathematical relationship between AUMC and AUC reflects the average residence time for one drug dose. At steady-state conditions with repeated dosing, this relationship breaks down, making MRT values unreliable for continuous or repeated dosing schedules.
Q4: What does the area under the moment-versus-time curve represent?
The area under the moment-versus-time curve (AUMC) provides information about the distribution and residence of drug molecules in the body over time. When combined with the area under the concentration-versus-time curve, AUMC enables calculation of mean residence time through the noncompartmental approach.
Q5: How does mean residence time relate to drug disposition in the body?
After intravenous bolus administration, drug molecules distribute throughout the body and reside there for varying periods. Mean residence time quantifies this disposition by representing the average duration these molecules remain in the system, offering clinicians insight into how quickly a drug is eliminated and how long therapeutic effects persist.
Q6: What is the noncompartmental approach in mean residence time analysis?
The noncompartmental approach is a model-independent methodology that calculates mean residence time using available data from single-dose administration without assuming specific compartment structures. This approach employs equations and algorithms to estimate MRT accurately by analyzing the relationship between AUMC and AUC values.
Q7: Why is the log-linear terminal phase assumption necessary for mean residence time calculation?
The log-linear terminal phase assumption allows extrapolation of the area under the moment-versus-time curve to infinity from a measured point, since it is impossible to obtain drug concentration measurements infinitely. This assumption enables practical calculation of mean residence time by providing a mathematical framework to estimate the tail of the AUMC curve.