HPLC Method Development and Validation for Pharmaceutical Analysis



The wide variety of equipment, columns, eluent and operational parameters involved makes high performance liquid chromatography (HPLC) method development seem complex. The process is influenced by the nature of the analytes and generally follows the following steps:

  • step 1 – selection of the HPLC method and initial system
  • step 2 – selection of initial conditions
  • step 3 – selectivity optimization
  • step 4 – system optimization
  • step 5 – method validation.

Figure 1: A flow diagram of an HPLC system.

Depending on the overall requirements and nature of the sample and analytes, some of these steps will not be necessary during HPLC analysis. For example, a satisfactory separation may be found during step 2, thus steps 3 and 4 may not be required. The extent to which method validation (step 5) is investigated will depend on the use of the end analysis; for example, a method required for quality control will require more validation than one developed for a one-off analysis. The following must be considered when developing an HPLC method:


  • keep it simple
  • try the most common columns and stationary phases first
  • thoroughly investigate binary mobile phases before going on to ternary
  • think of the factors that are likely to be significant in achieving the desired resolution.

Mobile phase composition, for example, is the most powerful way of optimizing selectivity whereas temperature has a minor effect and would only achieve small selectivity changes. pH will only significantly affect the retention of weak acids and bases. A flow diagram of an HPLC system is illustrated in Figure 1.


Table I: HPLC detector comparison.

HPLC method development Step 1 – selection of the HPLC method and initial system. When developing an HPLC method, the first step is always to consult the literature to ascertain whether the separation has been previously performed and if so, under what conditions – this will save time doing unnecessary experimental work. When selecting an HPLC system, it must have a high probability of actually being able to analyse the sample; for example, if the sample includes polar analytes then reverse phase HPLC would offer both adequate retention and resolution, whereas normal phase HPLC would be much less feasible. Consideration must be given to the following:

Sample preparation. Does the sample require dissolution, filtration, extraction, preconcentration or clean up? Is chemical derivatization required to assist detection sensitivity or selectivity?

Types of chromatography. Reverse phase is the choice for the majority of samples, but if acidic or basic analytes are present then reverse phase ion suppression (for weak acids or bases) or reverse phase ion pairing (for strong acids or bases) should be used. The stationary phase should be C18bonded. For low/medium polarity analytes, normal phase HPLC is a potential candidate, particularly if the separation of isomers is required. Cyano-bonded phases are easier to work with than plain silica for normal phase separations. For inorganic anion/cation analysis, ion exchange chromatography is best. Size exclusion chromatography would normally be considered for analysing high molecular weight compounds (.2000).

Table II: The basic types of analytes used in HPLC.

Gradient HPLC. This is only a requirement for complex samples with a large number of components (.20–30) because the maximum number of peaks that can be resolved with a given resolution is much higher than in isocratic HPLC. This is a result of the constant peak width that is observed in gradient HPLC (in isocratic HPLC peak width increases in proportion to retention time). The method can also be used for samples containing analytes with a wide range of retentivities that would, under isocratic conditions, provide chromatograms with capacity factors outside of the normally acceptable range of 0.5–15.

Gradient HPLC will also give greater sensitivity, particularly for analytes with longer retention times, because of the more constant peak width (for a given peak area, peak height is inversely proportional to peak width). Reverse phase gradient HPLC is commonly used in peptide and small protein analysis using an acetonitrile–water mobile phase containing 1% trifluoroethanoic acid. Gradient HPLC is an excellent method for initial sample analysis.

Column dimensions. For most samples (unless they are very complex), short columns (10–15 cm) are recommended to reduce method development time. Such columns afford shorter retention and equilibration times. A flow rate of 1-1.5 mL/min should be used initially. Packing particle size should be 3 or 5 μm.

Detectors. Consideration must be given to the following:

  • Do the analytes have chromophores to enable UV detection?
  • Is more selective/sensitive detection required (Table I)?
  • What detection limits are necessary?
  • Will the sample require chemical derivatization to enhance detectability and/or improve the chromatography?

Fluorescence or electrochemical detectors should be used for trace analysis. For preparative HPLC, refractive index is preferred because it can handle high concentrations without overloading the detector.

UV wavelength. For the greatest sensitivity λmax should be used, which detects all sample components that contain chromophores. UV wavelengths below 200 nm should be avoided because detector noise increases in this region. Higher wavelengths give greater selectivity.

Fluorescence wavelength. The excitation wavelength locates the excitation maximum; that is, the wavelength that gives the maximum emission intensity. The excitation is set to the maximum value then the emission is scanned to locate the emission intensity. Selection of the initial system could, therefore, be based on assessment of the nature of sample and analytes together with literature data, experience, expert system software and empirical approaches.

Step 2 – selection of initial conditions. This step determines the optimum conditions to adequately retain all analytes; that is, ensures no analyte has a capacity factor of less than 0.5 (poor retention could result in peak overlapping) and no analyte has a capacity factor greater than 10–15 (excessive retention leads to long analysis time and broad peaks with poor detectability). Selection of the following is then required.

Mobile phase solvent strength. The solvent strength is a measure of its ability to pull analytes from the column. It is generally controlled by the concentration of the solvent with the highest strength; for example, in reverse phase HPLC with aqueous mobile phases, the strong solvent would be the organic modifier; in normal phase HPLC, it would be the most polar one. The aim is to find the correct concentration of the strong solvent. With many samples, there will be a range of solvent strengths that can be used within the aforementioned capacity limits. Other factors (such as pH and the presence of ion pairing reagents) may also affect the overall retention of analytes.

Gradient HPLC. With samples containing a large number of analytes (.20–30) or with a wide range of analyte retentivities, gradient elution will be necessary to avoid excessive retention.

Determination of initial conditions. The recommended method involves performing two gradient runs differing only in the run time. A binary system based on either acetonitrile/water (or aqueous buffer) or methanol/water (or aqueous buffer) should be used.

Figure 2: The chemical structure of progesterone and Figure 3: Amount injected versus peak area of progesterone standard to demonstrate linearity.

Step 3 – selectivity optimization. The aim of this step is to achieve adequate selectivity (peak spacing). The mobile phase and stationary phase compositions need to be taken into account. To minimize the number of trial chromatograms involved, only the parameters that are likely to have a significant effect on selectivity in the optimization must be examined. To select these, the nature of the analytes must be considered. For this, it is useful to categorize analytes into a few basic types (Table II).

Once the analyte types are identified, the relevant optimization parameters may be selected (Table III). Note that the optimization of mobile phase parameters is always considered first as this is much easier and convenient than stationary phase optimization.

Selectivity optimization in gradient HPLC. Initially, gradient conditions should be optimized using a binary system based on either acetonitrile/water (or aqueous buffer) or methanol/water (or aqueous buffer). If there is a serious lack of selectivity, a different organic modifier should be considered.

Step 4 – system parameter optimization. This is used to find the desired balance between resolution and analysis time after satisfactory selectivity has been achieved. The parameters involved include column dimensions, column-packing particle size and flow rate. These parameters may be changed without affecting capacity factors or selectivity.

Table IV: Accuracy/recovery of progesterone from samples of known concentration.

Step 5 – method validation. Proper validation of analytical methods is important for pharmaceutical analysis when ensurance of the continuing efficacy and safety of each batch manufactured relies solely on the determination of quality. The ability to control this quality is dependent upon the ability of the analytical methods, as applied under well-defined conditions and at an established level of sensitivity, to give a reliable demonstration of all deviation from target criteria.

Analytical method validation is now required by regulatory authorities for marketing authorizations and guidelines have been published. It is important to isolate analytical method validation from the selection and development of the method. Method selection is the first step in establishing an analytical method and consideration must be given to what is to be measured, and with what accuracy and precision.

Method development and validation can be simultaneous, but they are two different processes, both downstream of method selection. Analytical methods used in quality control should ensure an acceptable degree of confidence that results of the analyses of raw materials, excipients, intermediates, bulk products or finished products are viable. Before a test procedure is validated, the criteria to be used must be determined.

Analytical methods should be used within good manufacturing practice (GMP) and good laboratory practice (GLP) environments, and must be developed using the protocols set out in the International Conference on Harmonization (ICH) guidelines (Q2A and Q2B).1,2 The US Food and Drug Administration (FDA)3,4 and US Pharmacopoeia (USP)5 both refer to ICH guidelines. The most widely applied validation characteristics are accuracy, precision (repeatability and intermediate precision), specificity, detection limit, quantitation limit, linearity, range, robustness and stability of analytical solutions. Method validation must have a written and approved protocol prior to use.6

Equation 1 and Figure 4: HPLC chromatograms of (a) progesterone reference standard; (b) separation of progesterone gel sample; (c) placebo formulation.

This article reviews and demonstrates practical approaches to analytical method validation with reference to an HPLC assay of progesterone (Figure 2) in a gel formulation. Progesterone is widely used for dysfunctional uterine bleeding or amenorrhoea,7,8 for contraception (either alone or with, for example, oestradiol or mestranol in oral contraceptives) and in combination with oestrogens for hormone replacement therapy in postmenopausal women.9,10

Experimental Chemicals and reagents All chemicals and reagents were of the highest purity. HPLC-grade methanol was obtained from Merck (Darmstadt, Germany). Progesterone reference standard was purchased from Sigma Chemicals (St Louis, Missouri, USA). Deionized distilled water was used throughout the experiments.

HPLC instrumentation The HPLC systems used for the validation studies consisted of Series 200 UV/Visible Detector, Series 200 LC Pump, Series 200 Autosampler and Series 200 Peltier LC Column Oven (all Perkin Elmer, Boston, Massachusetts, USA). The data were acquired via TotalChrom Workstation (Version 6.2.0) data acquisition software (Perkin Elmer), using Nelson Series 600 LINK interfaces (Perkin Elmer).

All chromatographic experiments were performed in the isocratic mode. The mobile phase was a methanol/water solution (75:25 v/v). The flow rate was 1.5 mL/min and the oven temperature was 40 ºC. The injection volume was 20 μL and the detection wavelength was set at 254 nm. The chromatographic separation was on a 25034.6 mm ID, 10 μm C18 μ-Bondapak column (Waters, Milford, Massachusetts, USA).

Table V: Demonstration of the repeatability of the HPLC assay for progesterone.

Results and discussionLinearity and range The linearity of a test procedure is its ability (within a given range) to produce results that are directly proportional to the concentration of analyte in the sample. The range is the interval between the upper and lower levels of the analyte that have been determined with precision, accuracy and linearity using the method as written. ICH guidelines specify a minimum of five concentration levels, along with certain minimum specified ranges. For assay, the minimum specified range is 80–120% of the theoretical content of active. Acceptability of linearity data is often judged by examining the correlation coefficient and y-intercept of the linear regression line for the response versus concentration plot. The regression coefficient (r2) is .0.998 and is generally considered as evidence of acceptable fit of the data (Figure 3) to the regression line. The per cent relative standard deviation (RSD), intercept and slope should be calculated.

In the present study, linearity was studied in the concentration range 0.025–0.15 mg/mL (25–150% of the theoretical concentration in the test preparation, n=3) and the following regression equation was found by plotting the peak area (y) versus the progesterone concentration (x) expressed in mg/mL: y53007.2×14250.1 (r251.000). The demonstration coefficient (r2) obtained for the regression line demonstrates the excellent relationship between peak area and concentration of progesterone. The analyte response is linear across 80-120% of the target progesterone concentration.

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