Internal Standard Curve in Sample

This is a question for the Empower 3 software.  I have a method that requires an internal standard curve to be generated from the samples where the first sample is endogenous but the next 3 injections are the sample spiked at a 20%, 50% then 100% of the standard concentration and I was trying to figure out how to have a curve be generated off those levels so a line of best fit is generated and determine the relative concentration in the endogenous sample.  Has anyone here had a similar method to work without the need to have a custom field?

• Go to the "Standards and unknowns" view of component editor and enter concentration of the internal standard next to the relevant standards and samples. For example, if you are quantifying these 3 samples off a bracketing standard, then enter the concentrations of the active and internal standard in your standard, followed by whatever concentration of your internal standard at 20% 50% etc spiking comes to in your samples. That way, your samples should be correctly quantified by the bracketing standard, assuming the internal standard peak and other peaks live in the same channel.
• These samples aren't being quantitated off a bracketing standard.  In the endogenous and spiked sample preparations we are developing the curve from the standard spiked in the sample injections which we haven't been able to figure out how to treat the sample as both the standard curve and to quantitate the sample.
• edited November 2018

You are using a standard additions approach. You need to plot your signal (peak area) vs. the amount of standard added. Your sample with no standard added will be plotted on the y-axis.

You then extrapolate to the point at which this line crosses the x-axis. The absolute value of the x-intercept will be the original concentration in the sample.

As far as I am aware, Empower will not be able to provide this result to you by default. You will need to calculate external to Empower or add a custom field.

Simply stated, the y-intercept divided by the slope gives you the x-intercept. In Empower variables, I believe that is B (y-intercept) divided by A (slope) for a linear regression type line.