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Author(s): Suman Shrivastava, Pooja Deshpande, S. J. Daharwal*


Address: University Institute of Pharmacy, Pt. Ravishankar Shukla University, Raipur-492010, Chhattisgarh, India. *Corresponding Author:

Published In:   Volume - 31,      Issue - 1,     Year - 2018

Cite this article:
shrivastava et al. (2018). Key Aspects of Analytical Method Development and Validation. Journal of Ravishankar University (Part-B: Science). 31 (1), pp. 32-39.

Journal of Ravishankar University–B, 31 (1), 32-39 (2018)

 Key Aspects of Analytical Method Development and Validation

Suman Shrivastava, Pooja Deshpande, S. J. Daharwal*

University Institute of Pharmacy, Pt. Ravishankar Shukla University, Raipur-492010, Chhattisgarh, India.

*Corresponding Author:

[Received: 20 February 2018; Revised version: 08 April 2018; Accepted: 13 April 2018]

Abstract: Development of a method is crucial for discovery, development, and analysis of medicines in the pharmaceutical formulation. Method validation could also be thought to be one in all the foremost well-known areas in analytical chemistry as is reproduced within the substantial variety of articles submitted and presented in peer review journals every year. Validation of an analytical procedure is to demonstrate that it's appropriate for its intended purpose. Results from method validation are often wont to decide the quality, reliability and consistency of analytical results. Analytical methods need to be validated or revalidated. This review describes general approach towards validation process and validation parameters to be considered during validation of an analytical method. It also refers to various regulatory requirements like WHO, USFDA, EMEA, ICH, ISO/IEC. The parameters described here are according to ICH guidelines which include accuracy, precision, specificity, limit of detection, limit of quantification, linearity range and robustness.

 Keywords: Method development; Validation; Analytical method; ICH guidelines; Accuracy and precision.


Analysis is vital in any product or service, and it is also important in drug because it involves life (Hema and Reddy, 2017). Analytical chemistry is the analysis of separation, quantification and chemical additives identification of herbal and synthetic materials constituted with one or more compounds or factors. Analytical chemistry is separated into two predominant classes, a qualitative evaluation that is to say the identification with regard to the chemical additives exists in the sample, whereas quantitative evaluation estimates the amount of positive detail or compound within the substance, i.e. the sample (Ravisankar et al., 2015). The consistency of an analytical finding could be a matter of great importance to drive the formulation scientist in the developing stage and impurity profile in stability study and dissolution data of the stability study yet as routine analysis. The importance of validation is producing reliable and repeatable results for routine analysis and stability analysis. This is often very true within the context of quality management and certification, that became matters of increasing importance in analytical in dissolution and impurity profile within the recent years. Therefore, this subject ought to extensively be mentioned on an international level to achieve a harmony on the extent of validation experiments and on acceptance criteria for validation parameters of analytical methods (Thompson et al., 2012).

In pharmaceutical industry, Validation is an important part of quality control and quality assurance. Various regulatory authorities offer special importance on the validation of all the processes used in the industry. Validation may be formal and systematic way to demonstrate suitability of the method to provide helpful information to confirm that the method or the method gives satisfactory and consistent results among the scope of the method. The analytical methods refer to the manner of performing the analysis. “Validation is that the method by that it is established by laboratory studies, that the performance characteristics of the method meet the requirements for the intended application” (Chan, 2010; Huber, 2007). All the analytical methods that are meant for analyzing any sample got to be valid. The current good manufacturing practices suggest that quality should be built into the product, and testing alone cannot be relied on to ensure product quality. Pharmaceutical products got to maintain prime quality so as to supply safe and effective usage. From the analytical purpose of interpretation, analytical methods used to test these products should have quality attributes built into them. Validation ensures these quality attributes are built into the method. Validation of analytical methods is a vital but time-consuming activity for most analytical laboratories. But it results inexpensive, eliminates frustrating repetitions and leads to better time management in the end. The analytical methods need to be validated or revalidated before initial use of the method in routine analysis, when transferred from one laboratory to another, whenever the conditions or method parameters that technique has been valid amendment and alter is outside the initial scope of the method (Paithankar, 2013).

Method validation is that the method used to ensure that the analytical procedure utilized for a selected check is appropriate for its meant use. Results from method validation may be able to decide the quality, reliability, and consistency of analytical results; it is an essential part of any good analytical practice.

Analytical methods need to be validated or revalidated.

  i.     Before their introduction into routine use

ii.     Whenever the conditions change for which the method has been validated (e.g., an instrument with different characteristics or samples with a different matrix); and

iii.     Whenever the method is changed, and the change is outside the original scope of the method (Patil et al., 2017).

Method validation has received significant attention within the literature and from industrial committees and regulatory agencies.

ICH Q14 guidelines on Analytical Procedure development: The new guideline is proposed for harmonising the scientific approaches of Analytical Procedure Development, and providing the principles relating to the description of Analytical Procedure Development process. Applying this guideline can improve regulatory communication between industry and regulators and facilitate additional economical, sound scientific and risk-based approval further as post-approval modification management of analytical procedures (ICH Q14, 2018).

WHO guidelines on Analytical Method Validation: This presents some information on the characteristics that should be considered during validation of analytical methods. Approaches other than those specified may be followed and may be acceptable. Manufacturers should choose the validation protocol and procedures most suitable for testing of their product. The manufacturer should demonstrate that the analytical procedure is suitable for its intended purpose. Analytical methods, whether or not they indicate stability, should be validated. The analytical method should be validated by research and development before being transferred to the quality control unit when appropriate. The recommendations as provided for in good laboratory practices and guidelines for transfer of technology should be considered, where applicable, when analytical method validation is organized and planned (Guidelines on validation, 2016).

ICH Q2R1 and EMEA guidelines on Validation of Analytical Procedures: This document presents a discussion of the characteristics for consideration during the validation of the analytical procedures included as part of registration applications submitted within the EC, Japan and USA. This document does not necessarily seek to cover the testing that may be required for registration in, or export to, other areas of the world. Furthermore, this text presentation serves as a collection of terms, and their definitions, and is not intended to provide direction on how to accomplish validation. These terms and definitions are meant to bridge the differences that often exist between various compendia and regulators of the EC, Japan and USA. The objective of validation of an analytical procedure is to demonstrate that it is suitable for its intended purpose. A tabular summation of the characteristics applicable to identification, control of impurities and assay procedures is included. Other analytical procedures may be considered in future additions to this document (ICH Q2R1, 2005; EMEA, 1996).

ISO/IEC 17025 includes a chapter on the validation of methods with a list of nine validation parameters. The International Conference on Harmonization (ICH) has developed a consensus text on the validation of analytical procedures. The document includes definitions for 8 validation characteristics. ICH also developed a guidance with the detailed methodology (ISO, 2005). The US EPA prepared guidance for method’s development and validation for the Resource Conservation and Recovery Act (USEPA, 1995). The FDA has also published guidance for the validation of bioanalytical methods (USFDA, 2001).

Analytical method development: When there are no definitive techniques are present, new methodologies are being progressed for evaluation of the novel product. To investigate the presence of either pharmacopoeial or non-pharmacopoeial product novel techniques are developed to reduce the value besides time for higher precision and strength. These methodologies are optimized and valid through preliminary runs. Alternate ways are planned and place into practice to exchange the present procedure within the comparative laboratory information with all accessible merits and demerits (Chauhan et al., 2015).

Necessity of method development: Drug evaluation exhibits the identity characterization and resolution of the drugs in combination like dosage forms and organic fluids. At some point of producing technique and development of drug the principal purpose of analytical strategies is to generate data regarding efficiency (which might be directly connected with the need of a identified dose), impurity (related to safety of the medication), bioavailability (consists of key drug traits like crystal kind, uniformity of drug and release of drug), stability(that shows the degradation product), and effect of manufacturing parameters to verify that the production of drug product is steady (Sharma et al., 2018).

The reasons for the development of novel methods of drug analysis are:

         i.            When there is no official drug or drug combination available in the pharmacopoeias.

        ii.            When there is no decorous analytical process for the existing drug in the literature due to patent regulations.

      iii.            When there are no analytical methods for the formulation of the drug due to the interference caused by the formulation excipients.

      iv.            Analytical methods for the quantitation of the analyte in biological fluids are found to be unavailable.

       v.            The existing analytical procedures may need costly reagents and solvents. It may also involve burdensome extraction and separation procedures.

Steps for the development of the method: Development procedure follows with the proper documentation. All data relating to these studies must be recorded either in laboratory notebook or in an electronic database (Ravisankar et al., 2015).

Analyte standard characterization

a) All known important information about the analyte and its structure that is to say physico-chemical properties like solubility, optical isomerism etc., is collected.

b) The standard analyte (≈100 % purity) is obtained. Necessary arrangement is to be made for the perfect storage (refrigerator, desiccators, and freezer).

c)  In the sample matrix when multiple components are to be analyzed, the number of components is noted duly presenting the data and the accessibility of standards is estimated.

d)  Methods like spectroscopic, HPLC, GC, MS etc., are considered when matched with the sample stability (Ravisankar et al., 2015).

Method requirements: The requirements of the analytical method need to develop the analytical figures of merit such as linearity, selectivity, range, accuracy, precision, detection limits etc., shall be defined (Ravisankar et al., 2015).

Literature search and prior methodology: All the information of literature connected with the drug is reviewed for physico-chemical properties, synthesis, solubility and appropriate analytical methods with reference to relevant books, journals, USP/NF, AOAC and ASTM publications and it is highly convenient to search Chemical Abstracts Service automated computerized literature (Ravisankar et al., 2015).

Choosing a method:

a) Duly utilizing the information available from the literature, methodology is evolved since the methods are changed wherever required. Occasionally it is imperative to get additional instrumentation to develop, modify or reproduce and validate existing procedures for analytes and samples.

b) If there are no past suitable methods available to analyze the analyte to be examined (Ravisankar et al., 2015).

Instrumental setup and initial studies: Installation, operational and performance qualification of instrumentation with reference to laboratory standard operating procedures is verified by setting up appropriate instrumentation (Ravisankar et al., 2015).

Optimization: While performing optimization, one parameter is changed at a time and a set of conditions are isolated, before utilizing trial and error approach. The said work need to be accomplished basing on a systematic methodical plan duly observing all steps and documented with regard to dead ends (Ravisankar et al., 2015).

Documentation of analytical figures of merit: The actual decided analytical figures of merit like Limit of quantitation, Limit of detection, linearity, time taken for analysis, cost, preparation of samples etc. are also documented (Ravisankar et al., 2015).

Evaluation of development method with real samples: The sample solution should lead to unequivocal, total identification of the peak interest of the drug apart from all other matrix components (Ravisankar et al., 2015).

Estimation of percent recovery of real samples and demonstration of quantitative sample analysis: Percent recovery of spiked, genuine standard drug into a sample matrix which contains no analyte is estimated. Optimization to reproducibility of recovery (average ± standard deviation) from sample to sample has to be showed. It is not necessary to get 100% recovery so far as the results are reproducible to recognize with a high degree of certainty (Ravisankar et al., 2015).

Analytical method validation: Validation of an analytical approach is established through laboratory research, that the execution attributes of the procedure meet the requirements for the proposed scientific application. Validation is required for any new or altered procedure to verify that it is fit for giving predictable and dependable outcomes, once used by various administrators by usage of comparable instrumentation inside the similar or absolutely distinct laboratories (Bhardwaj et al., 2015).

The process of validation of analytical method is adopted to confirm that the employed analytical procedure for a specific test meet the intended requirements. Guidelines from the USP, ICH, FDA etc., can provide a framework for validations of pharmaceutical methods. Results from the method validation can be considered to judge its quality, reliability as well consistency pertaining to analytical results. In the realm of pharmaceutical industry, the prominent reasons for validating assay are the first crucial one is validation of assay which is the integral part of the quality-control system and secondly regulation of genuine manufacturing practices inevitably needs assay validation (USP, 2000; USFDA).

Importance of validation (Nandhakumar et al., 2011; Bansal et al., 2004; Jenke, 1996)

            i.         Assurance of quality

           ii.         Time bound

         iii.         Process optimization

         iv.         Reduction of quality cost.

          v.         Nominal mix-ups, and bottle necks

         vi.         Minimal batch failures, improved efficiently and productivity.

       vii.         Reduction in rejections.

      viii.         Increased output.

         ix.         Avoidance of capital expenditures

          x.         Fewer complaints about process related failures.

         xi.         Reduced testing in process and in finished goods.

       xii.         More rapid and reliable start-up of new equipment

      xiii.         Easier scale-up form development work.

     xiv.         Easier maintenance of equipment.

       xv.         Improved employee awareness of processes.

     xvi.         More rapid automation.

    xvii.         Government regulation (Compliance with validation requirements is necessary for obtaining approval to manufacture and to introduce new products)

Strategy for the validation of methods: The validity of a specific method should be demonstrated in laboratory experiments using samples or standards that are similar to unknown samples analyzed routinely. The preparation and execution should follow a validation protocol, preferably written in a step-by-step instruction format. This proposed procedure assumes that the instrument has been selected, and the method has been developed. It meets criteria such as ease of use; ability to be automated and to be controlled by computer systems; costs per analysis; sample throughput; turnaround time; and environmental, health, and safety requirements (Patil et al., 2017).

Steps in Method Validation: (CITAC/EURACHEM, 2002)

         i.            Develop a validation protocol, an operating procedure or a validation master plan for the validation

        ii.            For a specific validation, project defines owners and responsibilities

      iii.            Develop a validation project plan

      iv.            Define the application, purpose, and scope of the method

       v.            Define the performance parameters and acceptance criteria

      vi.            Define validation experiments

    vii.            Verify relevant performance characteristics of equipment

   viii.            Qualify materials, for example, standards and reagents for purity, accurate amounts, and sufficient stability

      ix.            Perform pre-validation experiments

       x.            Adjust method parameters or/and acceptance criteria if necessary

      xi.            Perform full internal (and external) validation experiments

    xii.            Develop SOPs for executing the method in the routine

   xiii.            Define criteria for revalidation

  xiv.            Define type and frequency of system suitability tests and/or analytical quality control checks for the routine

    xv.            Document validation experiments and results in the validation report.

Types of analytical procedures to be validated:

The discussion of the validation of analytical procedures is directed to the four most common types of analytical procedures:

         i.            Identification tests;

        ii.            Quantitative tests for impurities' content;

      iii.            Limit tests for the control of impurities;

      iv.            Quantitative tests of the active moiety in samples of drug substance or drug

       v.            Product or other selected component(s) in the drug product.

Identification tests are intended to ensure the identity of an analyte in the sample. This normally achieved by comparison of a property of the sample (e.g., spectrum, chromatographic behaviour, chemical reactivity, etc) to that of a reference standard. Testing for impurities can be either a quantitative test or a limit test for the impurity in a sample. Either test is intended to accurately reflect the purity characteristics of the sample. Different validation characteristics are required for a quantitative test than for a limit test. Assay procedures are intended to measure the analyte present in a given sample. In the perspective of this document the assay presents a quantitative measurement of the major components in the drug substances.

For the drug products similar characteristics also apply when assaying for the active or other selected components. The same validation characteristics also apply to assay associated with other analytical procedures (Lavanya et al., 2013).

Analytical method validation parameters

 The parameters for validation as per ICH guidelines (ICH, 2005) need to be selected as per the regulatory requirements. The parameters considered in chromatographic method validation are discussed below.

Figure 1. Validation parameters


Specificity is the ability to assess the analyte for the presence of various components that may be present. It can be established by a number of approaches, depending on the intended purpose of the method. The ability of the method to assess the analyte of interest in a drug product is determined by a check for interference by placebo. Specificity can be assessed by measurement of the API in samples that are spiked with impurities or degradants.

If API-related compounds are not available, drug can be stressed or force-degraded in order to produce degradation products. In chromatographic separations, apparent separation of degradants may be confirmed by peak purity determinations by photodiode array, mass purity determinations by mass spectroscopy (MS) or by confirming separation efficiency using alternate column chemistry. Lack of specificity of an individual analytical procedure may be compensated by other supporting analytical procedures (ICH, 2005).


The term selectivity is sometimes used interchangeably with specificity. Technically, however, there is a difference. Selectivity is defined as the ability of the method to separate the analyte from other components that may be present in sample, including impurities. Selectivity is separate and shows every component in the sample. Therefore, one could have a method that is specific, yet it may not be selective (Shrivastava and Gupta, 2012).


A linear relationship should be evaluated across the range (see section 3) of the analytical procedure. It may be demonstrated directly on the drug substance (by dilution of a standard stock solution) and/or separate weighing of synthetic mixtures of the drug product components, using the proposed procedure. The latter aspect can be studied during investigation of the range. Linearity should be evaluated by visual inspection of a plot of signals as a function of analyte concentration or content. If there is a linear relationship, test results should be evaluated by appropriate statistical methods, for example, by calculation of a regression line by the method of least squares. For the establishment of linearity, a minimum of 5 concentrations is recommended (ICH, 2005; Araujo, 2009).


The accuracy of an analytical procedure expresses the closeness of agreement between the value which is accepted either as a conventional true value or an accepted reference value and the value found. This is sometimes termed trueness and several methods available of determining the accuracy. Accuracy should be established across the specified range of the analytical procedure. Accuracy should be assessed using a minimum of 9 determinations over a minimum of 3 concentration levels covering the specified range (e.g., 3concentrations/3 replicates each of the total analytical procedure). Accuracy should be reported as percent recovery by the assay of known added amount of analyte in the sample or as the difference between the mean and the accepted true value together with the confidence intervals (Srivastava and Kumar, 2017).


The precision of an analytical procedure expresses the closeness of agreement (degree of scatter) between a series of measurements obtained from multiple sampling of the same homogeneous sample under the prescribed conditions. It can be sub divided into repeatability, intermediate precision and reproducibility. Precision should be investigated using homogeneous, authentic samples. However, if it is not possible to obtain a homogeneous sample it may be investigated using artificially prepared samples or a sample solution. The standard deviation, relative standard deviation like coefficient of variation and confidence interval should be reported for each type of precision investigated.

Repeatability: Repeatability is also termed intra assay precision. Repeatability is the variation experienced by a single analyst on a single instrument. Repeatability does not distinguish between variation from the instrument or system alone and from the sample preparation process. During the validation, repeatability is performed by analyzing multiple replicates of an assay composite sample by using the analytical method. Repeatability should be assessed using a minimum of 9 determinations covering the specified range for the procedure by 3 replicates or 6 determinations at 100% of the test concentration (Daksh et al., 2015).

Intermediate precision: Intermediate precision expresses within-laboratories variations: different days, different analysts, different equipment, etc. Intermediate precision depends upon the circumstances under which the procedure is intended to be used. The applicant should establish the effects of random events on the precision of the analytical procedure. Typical variations to be studied include days, analysts, equipment, etc. It is not considered necessary to study these effects individually. The use of an experimental design (matrix) is encouraged. A statistical comparison is made to the first analyst’s results (Daksh et al., 2015).

Reproducibility: Reproducibility expresses the precision between laboratories (collaborative studies, usually applied to standardization of methodology). Reproducibility is assessed by means of an inter-laboratory trial (Tijare et al., 2016).

Limit of detection (LOD)

Lowest quantity of an analyte which may be detected by the chromatographical separation however it is not necessary that this quantity will quantify as a precise value. A blank resolution is injected and peak to peak quantitative noise relation we have to calculate from blank chromatograms. Then, calculate the concentration at the signal to quantitative noise relation is concerning 3:1.

LOD can be expressed as

LOD = 3.3 σ /S

Where, σ = Standard deviation of response, S = Slope of calibration curve (Pasbola and Chaudhary, 2017).

The slope S may be estimated from the calibration curve of the analyte. The estimate of σ may be carried out in a variety of ways, based on the standard deviation of the blank and the calibration curve.

Limit of Quantitation (LOQ)

The Quantitation limit of an individual analytical procedure is the lowest amount of analyte in a sample which can be quantitatively determined with suitable precision and accuracy. The quantitation limit is a parameter of quantitative assays for low levels of compounds in sample matrices, and is used particularly for the determination of impurities and/or degradation products. It can be determined visually, by signal to noise ratio, standard deviation of the response and the slope. Quantitation limit signal to noise approach can only be applied to analytical procedures which exhibit baseline noise. Comparing measured signals from samples with known concentrations of analyte with those of blank samples and establishing the minimum concentration at which the analyte can be reliably detected. A signal-to-noise ratio between 10 or 10:1 is generally considered acceptable for estimating the quantitation limit.

The quantitation limit may be expressed as

LOQ=10 σ/ S

Where, σ=Standard deviation of the response, S= Slope of the calibration curve.

The slope S may be estimated from the calibration curve of the analyte. The estimate of σ may be carried out in a variety of ways, based on the standard deviation of the blank and the calibration curve. The LOQ level is usually confirmed by injecting standards which have an acceptable percent relative standard deviation (% RSD) not more than 10% (ICH, 2005; Geetha et al., 2012).


The evaluation of robustness should be considered during the development phase and depends on the type of procedure under study. It should show the reliability of an analysis with respect to deliberate variations in method parameters. If measurements are susceptible to variations in analytical conditions, the analytical conditions should be suitably controlled or a precautionary statement should be included in the procedure. One consequence of the evaluation of robustness should be that a series of system suitability parameters (e.g., resolution test) is established to ensure that the validity of the analytical procedure is maintained whenever used (ICH, 2005; Ajay and Rohit, 2012).


Ruggedness is the degree or measure of reproducibility under different situations such as in different laboratories, different analyst, different machines, environmental conditions, operators etc (Boque et al., 2002).

System suitability parameters

System suitability test is used to check the sensitivity, resolution, and reproducibility of the chromatographic system are well for the analysis to be done. The factors mainly used in system suitability are tailing factor, a number of the theoretical plate, retention time, resolution, etc. (Gupta et al., 2012; Sanap et al., 2017).


This article gives an idea that what is validation, its types, why it is necessary, how to develop a method and how to carry out the validation procedure to demonstrate that the technique is able for its proposed reason. All validation parameters such as linearity, LOQ, LOD, Range, specificity, robustness, ruggedness and system suitability are defined.


The authors are grateful to Director, University Institute of Pharmacy, Raipur for providing encouragement and critical review on the manuscript.

Conflict of interests

There is no conflict of interest from the authors.


Ajay, S., Rohit, S. (2012). Validation of analytical procedures: a comparison of ICH VS Pharmacopoeia (USP) and FDA. International Research Journal of Pharmacy, 3:39-42.

Araujo, P. (2009). Key aspects of analytical method validation and linearity evaluation. Journal of chromatography B, 877:2224-34.

Bansal, S.K., Layloff, T., Bush, E.D., Hamilton, M., Hankinson, E.A., Landy, J.S., Lowes, S., Nasr, M.M., Jean, P.A. and Shah, V.P. (2004). Qualification of analytical instruments for use in the pharmaceutical industry: a scientific approach. American Association of Pharmaceutical Scientists, 5:151.

Bhardwaj, S.K., Dwivedi, K. and Agarwal, D.D. (2015). A review: HPLC method development and validation. International Journal of Analytical and Bioanalytical Chemistry, 5:76-81.

Boque, R., Maroto, A., Riu, J. and Rius, F.X. (2002). Validation of analytical methods. Grasas Aceites, 53:128-43.

Gupta, V., Jain, A.D., Gill, N.S. and Gupta, K. (2012). Development and validation of HPLC method-a review. International Journal of Pharmaceutical Research and Allied, 2:17-5.

Chauhan, A., Mittu, B. and Chauhan, P. (2015). Analytical method development and validation: a concise review. Journal of Analytical & Bioanalytical Techniques, 6:1.

Chan, C.C. (2010). Analytical method validation: principles and practices. Pharmaceutical Sciences Encyclopedia: Drug Discovery, Development, and Manufacturing.1-6.

CITAC/EURACHEM (2002). Working Group, International Guide to Quality in Analytical Chemistry: An Aid to Accreditation.

Daksh, S., Goyal, A. and Pandiya, C.K. (2015). Validation of analytical methods–strategy and significance. International Journal of Research and Development in Pharmacy & Life Sciences, 4:1489-97.

Draft guidance analytical procedures and method validation, US food and drug administration, Centre for drugs and biologics, Department of Health and Human Services.

EMEA guidelines. (June, 1995). ICH Topic Q2 (R1) Validation of Analytical Procedures: Text and Methodology.

Geetha, G., Raju, K.N., Kumar, B.V. and Raja, M.G. (2012). Analytical method validation: an updated review. International Journal of Pharmaceutical and Biological Science, 1:64-1.

Guidelines on Validation (June, 2016). Appendix 4 Analytical Method Validation.

Guideline, I. H. T. (2005, November. Validation of analytical procedures: text and methodology Q2 (R1). In International conference on harmonization, Geneva, Switzerland , 11-12.

Hema and Reddy, G.S. (2017). A review on new analytical method development and validation by RP-HPLC. International Research Journal of Pharmaceutical and Biosciences, 4:41-50.

Huber, L. (2007). Validation and qualification in analytical laboratories, CRC Press.

ICH Q14 (November, 2018). Analytical Procedure Development and Revision of Q2(R1) Analytical Validation.

ISO (2005). General Requirements for the Competence of Testing and Calibration Laboratories, ISO/IEC 17025. Geneva.

Jenke, D.R. (1996). Chromatographic method validation: a review of current practices and procedures, II guidelines for primary validation parameters. Journal of Liquid Chromatography and Related Technology, 19: 737-57.

Lavanya, G., Sunil, M., Eswarudu, M.M., Eswaraiah, M.C., Harisudha, K., Spandana, B.N. (2013). Analytical method validation: An updated review. International Journal of Pharma Sciences and Research, 4:1280-6.

Nandhakumar, L., Dharmamoorthy, G., Rameshkumar, S. and Chandrasekaran, S. (2011). An overview of pharmaceutical validation: Quality assurance view point. International Journal of Research in Pharmacy and Chemistry, 1:1003-4.

Paithankar, H.V. (2013). HPLC Method validation for pharmaceuticals: A Review.  International Journal of Universal Pharmacy and Bio Sciences, 2: 229-240.

Pasbola, K. and Chaudhary, M. (2017). Updated review on analytical method development and validation by HPLC. World Journal of Pharmacy and Pharmaceutical Sciences, 6:1612-30.

Patil, S.T., Ahirrao, R.A. and Pawar, S.P. (2017). A short review on method validation. Journal of Pharmaceutical and BioSciences, 5.

Ravisankar, P., Navya, C.N., Pravallika, D. and Sri, D.N. (2015). A review on step-by-step analytical method validation. IOSR Journal of Pharmacy, 5:7-19.

Sanap, G.S., Zarekar, N.S. and Pawar, S.S. (2017). Review on method development and validation. International Journal of Pharmaceutics and Drug Analysis, 5:177-84.

Sharma, S., Goyal, S. and Chauhan, K. (2018). A Review on Analytical Method Development and Validation. International Journal of Applied Pharmaceutics, 10: 8-15.

Shrivastava, A. and Gupta, V.B. (2012). HPLC: Isocratic or gradient elution and assessment of linearity in analytical methods. Journal of Advanced Scientific Research, 3(2):12-20.

Srivastava, R.K. and Kumar, S.S. (2017). An updated review: Analytical method validation. European Journal of Pharmaceutical and Medical Research, 4: 774-784.

Tijare, L.K., Rangari, N.T. and Mahajan, U.N. (2016). A review on bioanalytical method development and validation. Asian Journal of Pharmaceutical and Clinical Research, 9:6-10.

Thompson, M., Ellison, S.L. and Wood, R. (2002). Harmonized guidelines for single-laboratory validation of methods of analysis (IUPAC Technical Report). Pure and Applied Chemistry, 74:835-55.

U.S. EPA (1995). Guidance for Methods Development and Method Validation for the Resource Conservation and Recovery Act (RCRA) Program. Washington, DC.

U.S. FDA (2001). Guidance for Industry, Bioanalytical Method Validation.

United States Pharmacopoeia. 24, National Formulary 19, (November, 2000). Section <1225> “Validation of compendial methods”. US Pharmacopoeial convention, Rockville, Validation of analytical procedures text and methodology Q2 (R1): 2005.

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