Why do we need a validated analytical method for pharmaceuticals?

Analytical method development and validation are essential in the discovery, development, optimization and manufacture of pharmaceuticals.  

The development of an analytical method is based on many considerations, such as: chemical properties of the analyte and its concentration in the sample matrix, the speed and cost of the analysis, type of measurements i.e. quantitative or qualitative and the number of samples.  

A qualitative method yields information on the chemical identity of the analyte(s) in the sample. A quantitative method provides numerical information regarding the relative amounts of each of the analytes in the sample. 

Validation is a series of experiments designed to ensure and prove with multiple statistically useful experiments that the method employed gives a true value for the concentration within a desired range of error. These include: specificity (the method only detects that analyte), linearity, accuracy (the method gives a true value), precision (different injections give the same result), range (the analyte satisfies all the validation criteria over the whole range of expected concentrations), detection and quantitation limits (the analyte can still be detected well below any expected analyte concentration and quantified accurately below any expected concentration), and stability and robustness (small changes to experimental parameters don’t affect the result, and the samples are acceptably stable for longer than any expected analytical waiting times and temperatures). A well-developed analytical method should be easy to validate, with the goal to rapidly test pre-formulation samples, formulation prototypes, production and commercial samples, and clinical trial samples.

The most widely used method for quantitative testing of the active pharmaceutical ingredient (API) and associated synthesis impurities, degradants and biological metabolites is the high performance liquid chromatography (HPLC). 

HPLC with ultraviolet or diode-array detection (UV or DAD) and HPLC with mass spectrometric detection (MS) techniques take advantage of chromatography as a separation method and UV or DAD or MS as detection, identification and quantification methods. The HPLC equipment consists of a high-pressure multiple solvent delivery system, a sample auto-injector, a separation column, a detector (UV or DAD) and a computer to control the system and display results. 

Ultra-high performance liquid chromatography (UPLC, or UHPLC) is a more recent technique in liquid chromatography using much smaller column packing particle sizes and much higher pressures of operation, which enables significant reductions in separation time, solvent consumption and analysis time as compared to conventional HPLC. 

Sample preparation plays an important role in the developed method. It should be an aliquot relatively free of interferences that is compatible with the HPLC method and that will not damage the column. The most desirable sample preparation is simple dilution in a solvent, since the process of validation is greatly simplified. For more difficult matrices, including biological matrices during clinical trials, more complex sample treatment is needed, and the validation protocols may become more involved. The main sample preparation techniques are liquid-liquid extraction (LLE) and solid-phase extraction (SPE). In these methods the analyte of interest is separated from sample matrix, so that as few potentially interfering species as possible are carried through to the analytical separation stage. 

 In summary, the analytical method development measures the concentration of an API in a specific compounded dosage form, which allows simplified procedures to be employed to verify that it will deliver accurately and consistently a reliable measurement of an active ingredient in a compounded dosage. 

Analytical method validation is essential to ensure that the developed analytical method is tested extensively for specificity, linearity, accuracy, precision, range, detection limit, quantitation limit, stability and robustness. This ensures that the method will give the correct result every time. 

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