In this small blog article, we would like to explain the parameter “Linearity” for an analytical method validation, its importance, and how it is calculated.

Mathematically speaking, linearity is a function of values that can be graphically represented as a straight line. Similarly, as per the method validation ICH Q2(R1) guideline, the linearity of an analytical method can be explained as its capability to show “results that are directly proportional to the concentration of the analyte in the sample”.

Introduction and background

Monoclonal antibodies (mABs) are monovalent immunoglobulin molecules that bind only to the same epitope. These antibodies have a wide range of applications such as in diagnostics, analytics, and as drugs in the treatment of cancer and other autoimmune diseases. The emerging market of mAB biosimilars demands proper characterization after previously performed isolation of these molecules. Isolating these antibodies however is quite a challenge and was first done by Georges Köhler and César Milstein, for which they were awarded the Nobel prize in medicine and physiology in the year 1984.

In this small blog article, we would like to explain two terms often mixed up during analytical method validation. It’s about specificity and selectivity.

Specificity

According to the official guideline to be applied for method validation ICH Q2(R1), specificity is defined as:

“Specificity is the ability to assess unequivocally the analyte in the presence of components which may be expected to be present.”

Introduction and background

Recombinant human tissue Plasminogen Activator (rt-PA), the synthetic version of Tissue plasminogen activator (tPA), is a serine protease involved in degradation of blood clots. As a drug it is used for the treatment of stroke. It functions by converting plasminogen into plasmin, which in turn degrades insoluble fibrin into soluble by-products. This process of converting fibrin into soluble by-products is called fibrinolysis.