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AMV - Assay Linearity Calculator

AMV Assay Linearity Calculator (USP/ICH) | PharmCal Professional

AMV - Assay Linearity Calculator

Advanced Regression Analysis & Plotting for Method Validation (USP/ICH)

1. Standard Solution Preparation
2. System Suitability

Enter area response for replicate injections. Stats update in real-time.

# Injection Name Area Response
Mean: 0.00 SD: 0.00 % RSD: 0.00%
3. Stock Solution Preparation (For Linearity)
*This Stock Concentration is used to calculate the Linearity levels below.
4. Linearity Solution Preparation & Data

Enter the Volume of Stock Taken and Final Dilution Volume to auto-calculate concentration. Then enter area for 3 injections.

Level Stock Vol (mL) Final Vol (mL) Calc. Conc (ppm) Inj-1 Area Inj-2 Area Inj-3 Area Avg Area
Regression Statistics
Slope (m) 0.000
Intercept (c) 0.000
Correlation (r) 0.000
R-Squared (R²) 0.000
Res. Sum Sq 0.000
Y-Intercept Bias 0.00%
Line Equation: y = mx + c
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About Assay Linearity in Method Validation

Linearity is a fundamental parameter in Analytical Method Validation (AMV) as described in ICH Q2(R1) and USP <1225>. It demonstrates that the analytical procedure obtains test results that are directly proportional to the concentration (amount) of analyte in the sample within a given range.

Key Parameters Explained

  • Range: The interval between the upper and lower concentration of analyte in the sample for which it has been demonstrated that the analytical procedure has a suitable level of precision, accuracy, and linearity. For Assay, the typical range is 80% to 120% of the test concentration.
  • Correlation Coefficient (r): Indicates the strength of the linear relationship. Acceptance criteria is typically r ≥ 0.999.
  • Coefficient of Determination ($R^2$): Indicates the proportion of the variance in the dependent variable (Area) that is predictable from the independent variable (Concentration). Typically $R^2$ ≥ 0.9998.
  • Y-Intercept Bias: The intercept value at zero concentration. Ideally, this should be close to zero. A high intercept bias indicates systematic error.
  • Residual Sum of Squares (RSS): A measure of the discrepancy between the data and the estimation model. Lower values indicate a better fit.

Step-by-Step Guide

1 Prepare Standards: Prepare your Working Standard and perform 5 replicate injections to establish System Suitability (SST). The % RSD should be ≤ 2.0%.
2 Prepare Stock: Create a high-concentration Stock Solution. Enter the weight, dilutions, and potency to calculate the exact Stock PPM.
3 Prepare Levels: From the Stock, prepare at least 5 linearity levels (e.g., 80%, 90%, 100%, 110%, 120%). Enter the volume taken and final volume for each level to auto-calculate the concentration.
4 Inject & Analyze: Inject each level in triplicate. Enter the Area Response for each injection. The tool will calculate the Average Area.
5 Generate Report: Click "Calculate". The tool performs regression analysis using the Least Squares Method and plots the Linearity Curve. Print the report for your validation file.

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