The calculation gives each interval a width multiplied by the mean of its two endpoint measurements: (t2−t1)(C1+C2)/2. Summing these interval areas produces the overall estimate. This formulation allows investigators to use observations collected at different time points while preserving the contribution of each interval according to its actual duration.
Sampling frequency affects how faithfully the estimate follows the underlying time course. Closely spaced observations provide more intervals and can better capture changes between measurements, whereas sparse sampling may overlook variation. Consequently, accuracy depends not only on the calculation itself but also on whether the recorded points represent the important changes in the curve.
The method uses measured values from adjacent observations, so researchers do not need to specify a continuous equation for the entire curve. This makes it suitable when clinical data consist of discrete measurements. However, the estimate remains tied to what was actually sampled, meaning the sampling design influences how well the calculated area reflects the measured time course.
Researchers first arrange the observations in time order and identify each pair of adjacent measurements. For every interval, they determine the time width, average the two endpoint values, and multiply those quantities to obtain the interval area. Adding the interval areas yields the overall estimate, which can then support interpretation of the time-dependent clinical measurement.
In pharmacokinetic research, the method estimates the area under a concentration-time curve from sampled drug concentrations. The resulting area summarizes drug exposure across the observed period and can support comparisons among treatments. Its usefulness depends on whether the concentration measurements are frequent enough to represent relevant changes over time.
Beyond drug concentration profiles, the method can summarize other clinical measurements that change over time when values are available at discrete observations. The calculated area provides a single summary of the measured time course, but interpretation still requires attention to sampling frequency and whether the observations capture meaningful changes between recorded points.