Methods testing parallelism can be divided into two categories depending on how the parallelism hypothesis is tested: response comparison tests and parameter comparison tests.1 This application note explains both methods and outlines how to use them in SoftMax® Pro GxP and Standard Software to test for parallelism. The relative potency is set to one for the reference curve (red circle) and the scaling factor used to transform the reference curve into the test curve (blue diamond) is the relative potency of the unknown agent.
Parallel line model for linear regression. However with non-linear regression curve fits, such as the 4-parameter and 5-parameter logistics, the sigmoidal dose-response curve has a variable slope over the entire concentration range (Figure 1).įigure 2. This methodology works well for linear regression curve fits where the slope is unchanged across the concentration range (Figure 2).
1 The relative potency is generally set to one for the reference curve (known agent) and the scaling factor used to transform the reference curve into the test curve (unknown agent) is the relative potency of the unknown agent. Two curves are defined to be parallel when one function is obtained from the other by a scaling factor either to the right or to the left on the x-axis, ƒ(x) = ƒ(rx), where x is the dose and r is the scaling factor, or relative potency. Parallel line analysis of dose response data sets with a constrained global 4-parameter curve fit. Testing for parallelism is a prerequisite to calculate the relative potency of a compound and plays an important role in many pharmaceutical drug development applications such as drug comparison, analyte confirmation, crossreactivity, interfering substances, matrix compensation, concentration estimation, and inhibitory studies.įigure 1. Parallelism methods allow the user to establish if the biological response to two substances is similar or if two biological environments give similar dose-response curves to the same substances. PLA is commonly used to compare dose-response curves where there is no direct measurement of a product, but rather an effect is measured (Figure 1). In laboratories operating under GMP (good manufacturing practice) and GLP (good laboratory practice) regulations, biological assays are frequently analyzed with the help of parallel line analysis (PLA). High-Content Screening with AgileOptix Technology.PROTEIN DETECTION, QUANTITATION, ANALYSIS.NUCLEIC ACID (DNA/RNA) DETECTION & ANALYSIS.SpectraTest Validation Plates and Recertification.GXP SOFTWARE INSTALLATION AND VALIDATION.HIGH-THROUGHPUT, HIGH CONTENT SCREENING.
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