INTRODUCTION:

Thedevelopment of bioanalytical method validation principles over the last two decades is an example of well-accepted regulations within an area of science and scientific research. The validation procedures, defined as guidance, are not written into general law, but nevertheless describe the view of the registration authorities [1].

Successful conduct of nonclinical and/or bio pharmaceutics and clinical pharmacology studies the Selective, sensitive, and validated analytical methods for the quantitative evaluation of drugs and their metabolites (analytes) and biomarkers are critical.

Validation of bioanalytical methods includes the performance of all of the procedures that demonstrate that a particular method used for quantitative measurement of analytes in a given biological matrix (e.g., blood, plasma, serum, or urine) is consistent and reproducible for the intended use. Fundamental parameters for this validation include the following:

· Accuracy

· Precision

· Selectivity

· Sensitivity

· Reproducibility

· Stability

· Robustness

· Ruggedness

Bioanalytical Validation involves documenting, through the use of particular laboratory investigations, that the performance characteristics of a method are suitable and consistent for the proposed analytical applications. The suitability of analytical data corresponds directly to the criteria used to validate the method. For fundamental studies that require regulatory action for approval or labeling, such as Bioequivalence or Pharmacokinetic studies, the bioanalytical methods must be fully validated. For tentativemethods used for the sponsor’s internal decision making, less validation may be sufficient [2].

A bioanalytical method is a set of various procedures involved in the collection, processing, storage, and analysis of a biological matrix of a chemical compound. Bioanalytical method validation (BMV) is the process used to establish that a quantitative analytical method is suitable for biomedical applications. Bioanalytical method validation employed for the quantitative determination of drugs and their metabolites in biological fluidswhich plays a significant role in the evaluation and interpretation of bioavailability, bioequivalence, pharmacokinetic, and toxicokinetic study data [3]. Bioanalytical method validation is vital not only in terms of regulatory submission but also for ensuring generation of high quality data during drug discovery and development. BMV assures that the quantification of analyte in biological fluids is reproducible, reliable and suitable for the application.

The increased number of biological agents used as therapeutics (in the form of recombinant proteins, monoclonal antibodies, vaccines, etc.) has prompted the pharmaceutical industry to review and redefine aspects of the development and validation of bioanalytical methods for the quantification of this therapeutics in biological matrices in support of preclinical and clinical studies [3,4].

Bioanalytical methods, based on a variety of physico-chemical and biological techniques such as chromatography, immunoassay and mass spectrometry, must be validated prior to and during use to give confidence in the results generated. It is the process used to establish that a quantitative analytical method is suitable for biomedicalapplications. Bioanalytical method validation includes all of the procedures that demonstrate that a particular methodused for quantitative measurement of analytes in a given biological matrix, such as blood, plasma, serum, or urine isreliable and reproducible for the intended use. [5,6]

The objective of validation of bioanalytical procedure is todemonstrate that it is suitable for its intended purpose. The mostwidely accepted guideline for method validation is the ICH guideline Q2 (R1), which is used both in pharmaceutical and medical science [4].

Need of Bioanalytical Method Validation:

1. It is essential to choose the well-characterized and fully validated bioanalytical methods to yield reliable results that can besatisfactorily interpreted.

2. It is recognized that bioanalytical methods and techniques are constantly undergoing changes and improvements; they are atthe cutting edge of the technology.

3. It is also important to highlight that each bioanalytical technique has its own characteristics, which will vary fromanalyte to analyte, specific validation criteria may need to be developed for each analyte [7].

4. The appropriateness of the technique also influenced by the ultimate objective of the analytical study. When sample analysis for a given study is conducted at over one site, it's necessary to validate the bio analytical method (s) at every site and provide applicable validation information for different sites to establish inter-laboratory reliability [7, 8].

TYPES OF BIOANALYTICAL METHOD VALIDATION:

Bioanalytical method validation most widely classified into three types

A. Full validation

B. Partial validation

C. Cross validation

A.FULL VALIDATION:

Full validation is important in expanding and executing a bioanalytical method for a new drug entity. If metabolites in new drug entity are added to an existing assay for quantification, then full validation of the revised assay is necessary for all analytes measured [9].

B. PARTIAL VALIDATION:

Partial validations are conducted to validatemitigation of previously fully validated bioanalytical methods. Partial validations can range from an intra or inter-assay precision and accuracy experiment to nearly same as a full validation. Partial validations are performed to check the validity of a change in method but not a change to the type of method usedwhere a full validation would be required [9].

Partial validation use in:

· Transfer of bioanalytical method between laboratories and analysts

· Modification in analytical methodology (e.g., change in detection systems)

· Modification in anticoagulant in harvesting biological fluid

· Change in matrix intervals species (e.g., human plasma to human urine)

· Modification in sample processing procedures

· Modification of species within matrix (e.g., rat plasma to mouse plasma)

· Modification in relevant concentration range

· Instruments and/or software platforms modification

· Limited sample volume (e.g., pediatric study)

· Rare matrices

· In the presence of concomitant medications the Selectivity demonstration of an analyte

· In the presence of specific metabolites the Selectivity demonstration of an analyte [10].

C. CROSS VALIDATION:

In cross validation process the comparison of validation parameters when two or more bio analytical methods are use to generate data within the same study or across different study [4,11]. Cross validation method is comparative. The comparison of method should be done in both ways. Cross-validation with spiked matrix and subject samples must be conducted at every site or laboratory to determine inter-laboratory reliability once sample analyses among one study are conducted at more than one site, or more than one laboratory, and should be considered once data generated using completely different analytical techniques [e.g., LC-MS (Liquid chromatography mass spectroscopy) vs. enzyme-linked immunosorbent assay (ELISA)] in several studies are enclosed in a regulatory submission [12].

Current Validation Practice on Bioanalytical Methods Validation:

In recent drug development environment, highly sensitive and selective methodology is required to quantify drugs in matrices such as blood, plasma, serum, or urine.

Chromatographic methods are the most commonly used technology for the bioanalysis of small molecules and the general terms presented below take in account to this type of analytical method. It is well accepted the FDA Guidance for Industry, Bioanalytical Methods Validation (2001) as a reference for current validation practice and a briefly description of it is given in the common terminology [4, 7].

Validation parameters:

The fundamental parameters involved in bioanalytical validation

1. Accuracy

2. Precision

3. Linearity

4. Selectivity and specificity

5. Limit of detection

6. Limit of quantitation

7. Standard curve (calibration curve)

8. Recovery

9. Stability

10. Robustness

11. Ruggedness

ACCURACY:

Accuracy is ‘Generally measured as relative error (% RE). It is an absolute measurement and an accurate method depends on several factors such as specificity and precision. Accuracy is sometimes referred as trueness [4,13]. Accuracy of an analytical method may be determined by the assay method used on highly pure substance like reference standards and compared it with the same material with a known and established method. In case of quantitative analysis of impurities, accuracy should be assessed on samples of drug substance or product by spiking with, known amounts of impurities.

The ICH recommends that the accuracy should be assessed using a minimum of nine determinations over a minimum of 3 concentrations levels, covering the specified range (i.e. 3 concentrations and 3 replicates of each concentrations) [2].

The mean value should be within 15% of the nominal value except at LLOQ, where it should not deviate by more than 20%. The deviation of the mean from the nominal value serves as the measure of accuracy. The two most commonly used ways to determine the accuracy or method bias of an analytical method are (I) analyzing control samples spiked with analyte and (II) by comparison of the analytical method with a reference method. Accuracy is best reported as percentage bias which is calculated from the expression:

Measured value - true value

Abso % Bias = ----------------------------------- 100

True value

Bias: According to ISO, bias is the difference between the expectation of test results and an accepted reference value. It may consist of more than one systematic error component. Bias can be measured as a percent deviation from the accepted reference value. The term trueness expresses the deviation of the mean value of a large series of measurements from the accepted reference value. It can be expressed in terms of bias. Due to the high workload of analyzing such large series, trueness is usually not determined during method validation, but rather from the results of a great number of quality control samples (QC samples) during routine application [12,14].

PRECISION:

Precision of an analytical method describes the closeness of individual measures of an analyte when the procedure is applied repeatedly to multiple aliquots of a single homogeneous volume of biological matrix [15].

There are various parts to precision, such as repeatability, intermediate precision, and reproducibility ruggedness). Intermediate precision refers to how the method performs, both qualitatively and quantitatively, within one lab, but now from instrument to-instrument and day to-day [10].

The precision of an analytical method is determined by assessing sufficient number of aliquots of a homogeneous sample to be able to calculate statistically valid estimates of standard deviation or relative standard deviation [2].

Measurement of scatter for the concentrations obtained for replicate samplings of a homogeneous sample. It is typically measured as coefficient of variation (% CV) or relative standard deviation (R.S.D.) of the replicate measurements [4,16].

Standard deviation

% CV = --------------------------- × 100

Mean

The ICH documents recommends that repeatability should be assessed using a nine determinations covering the specified range for the procedure. (i.e. 3 concentrations and 3 replicate of each concentrations or using minimum of 6 determinations at 100% of the test concentrations). The precision determined at each concentration level should not exceed 15% coefficient of variation (CV) except for the LOQ where it should not exceed 20% CV. Precision may be considered at three levels: Repeatability, Intermediate precision, and Reproducibility.

Repeatability:

Repeatability expresses the analytical variability under the same operating conditions over a short interval of time (within-assay, intra-assay) [4]. It reflects the closeness of agreement of a series of measurements under the same operating conditions over a short interval of time. For a chromatographic method, repeatability can be evaluated by performing a minimum of six replicate injections of a single sample solution prepared at the 100% test concentration [12]. Repeatability means how the method performs in one lab and on one instrument, within a given day. Precision measured under the best condition possible (short period, one analyst) [4,5,12].

Alternatively, repeatability can be determined by evaluating the precision from a minimum of nine determinations that encompass the specified range of the method. The nine determinations may be composed of triplicate determinations at each of three different concentrations levels, one of which would represent the 100% test concentration [12].

Intermediate precision:

Intermediate Precision expresses within the laboratories with variations: different days, analysts, equipment’s, etc. The ISO definition used the term “M- factor different immediate precision”, where the M-factor expresses the number of factors (operator, equipment, or time) that vary between consecutive determinations [12].

Intermediate precision refers to how the method performs, both qualitatively and quantitatively, within lab, but now from instrument-to-instrument and from day-to-day [4]. Intermediate precision testing can consist of two different analysts, each preparing a total of six sample preparation, as per the analytical method [12].

Reproducibility:

Reproducibility is the precision between laboratories (collaborative or interlaboratory studies), is not required for submission, but can be taken into account for standardization of analytical procedure [5]. Ability of the method to yield similar concentration. Reproducibility refers to hoe that method performs from lab-to-lab, day-to-day, analyst-to-analyst, and instrument-to-instrument, again in both qualitative and quantitative terms [4].

LINEARITY:

The ability of bioanalytical procedure to obtain test results that are directly proportional to the concentration of analyte in the sample within the range of the standard curve [4].The concentration range of calibration curve should at least span those concentrations expected to be measured in the study samples. If the total range cannot be described by a single calibration curve, two calibration ranges can be validated [4,10,15]. It should kept in mind that the accuracy and precision of the method will be negatively affected at the extremes of the range by extensively expanding the range beyond necessity. Correlation coefficients were most widely use to test linearity. Although the correlation coefficient is of benefit for demonstrating a high degree of relationship between-response data, it is of little value in establishing linearity. Therefore, by assessing an acceptable high correlation coefficient alone the linearity is not guaranteed and further tests on linearity are necessary, for ex. A lack-of-fit test [4,5,10,14].

The linear range of the method must be determined regardless of the phase or drug development. Table 1 indicates US Food and Drug administration (FDA) guidelines for bioanalytical method validation. ICH recommends evaluating a minimum of five concentrations to assess the linearity. The five concentration levels should bracket the upper and lower concentration levels evaluated during the accuracy study. ICH guidelines recommend the following concentration ranges be evaluated during method validation [12].

Table 1 : US FDA guidelines for Bioanalytical method validation

· Assay (finished product or drug substance): 80–120% of the sample concentration. This range must bracket that of the accuracy study, however. If accuracy samples are to be prepared at 80, 100, and 120% of nominal, then the linearity range should be expanded to a minimum of 75–125%.

· Content uniformity method: 70–130% of the sample concentration, unless a wider, more appropriate, range is justified based on the nature of the dosage form (e.g., metered dose inhalers).

· Dissolution method: This requires ±20% of the specified range. In cases where dissolution profiles are required, the range for the linearity evaluation should start below the typical amount recovered at the initial pull point to 120% of total drug content.

· Impurity method: Reporting level to 120% of the specification. Impurity and assay method combined: One hundred percent level standard is used for quantification; reporting level of impurity to 120% of assay specification

SELECTIVITY AND SPECIFICITY:

For every phase of product development, the analytical method must demonstrate specificity [12]. Selectivity is the ability of an analytical method to differentiate and quantify the analyte in the presence of other components in the sample, which may consist of degradants, excipients/sample matrix, and sample blank peaks. The sample blank peaks may be attributed to things such as reagents or filters used during the sample preparation [6, 12,17].

Analysis of blank samples of the appropriated biological matrix should be obtained from at least six sources. Each blank sample should be tested for interference and selectivity should be ensured at the lower limit of quantification (LLOQ). These interference may arise from the constituents of the biological matrix under study, be it an animal (age, sex, race, ethnicity etc.) or a plant (development stage, varity, nature of the soil, etc.) or they could also depend on environmental exposure (climatic conditions such as UV- light, temperature and relative humidity) [4,5].

The actual FDA guidance for bioanalytical method validation requires the use of at least six independent sources of matrix to demonstrate methods selectivity. The ICH documents state that, when chromatographic procedures are used, representative chromatogram should be represented to demonstrate the degree of specificity (selectivity) and peaks should be appropriately labeled. Peak purity tests may be useful to show that the analyte chromatographic peak is not attributable to more than one component.

LIMIT OF DETECTION:

The L.O.D. is generally expressed as the concentration of the analyte sample (e.g. percentage or parts per million, etc.) [2]. The calculations of LOD is open to misinterpretation as some bioanalytical laboratories just measure the lowest amount of a references solution that can be detected and others the lowest concentrations that can be detected in the biological samples [4, 5].There is an overall agreement that the LOD should represent the smallest detectable amount or concentration of the analyte of interest [5, 18].

The ICH documents describe a common approach, which is to compare measured signals from samples with known low concentrations of analytes with those of blank samples.

These detection limits should be subsequently validated by the analysis of a suitable number of samples of known to be near or prepared at the detection limit [17].

LIMIT OF QUANTITATION:

The L.O.Q. is generally expressed as the concentration of the analyte in the sample (e.g. percentage or parts per million, etc.).

The ICHdocuments describe a common approach, which is to compare measured signals from samples with known low concentration of analytes with those of blank samples.

These quantitation limits should be subsequently validated by the analysis of a suitable number of samples known to be near or prepared at the quantitation limit [17].

The FDA Bioanalytical Method Validation document defined the lower limit of quantification (LLOQ) and the upper limit of quantification (ULOQ) as following.

Lower Limit Of Quantification:

The lower limit of quantification is the lowest amount of analyte in a sample that can be detected but not necessarily quantitated under the stated experimental conditions with acceptable accuracy and precision (bias). There are different approaches to the determination of LLOQ [4, 6, 12, 16].

The lowest standard on the calibration curve should be accepted as LLOQ if the following criteria are met:

The analyte response should be at least five times the response. Analyte peak should be identifiable, discrete and reproducible with a precision of maximum 20% and accuracy of 80- 120% [15].

LLOQ based on precision and accuracy (bias) data: This is probably the most practical approach and defines the LLOQ as the lowest concentration of a sample that can still be quantified with acceptable precision and accuracy (bias). The advantage of this approach is the fact that the estimation of LLOQ is based on the same quantification procedure used for real samples [12].

LLOQ based on signal to noise ratio (S/N): This approach can only be applied if there is baseline noise, for example, to chromatographic methods. Signal and noise can then be, defined as the height of the analyte peak (signal) and the amplitude between the highest and lowest point of the baseline (noise) in a certain area around the analyte peak. For LLOQ, S/N is usually required to be equal to or greater than 10. The estimation of baseline noise can be quite difficult for bioanalytical methods, if matrix peaks elute close to the analyte peak [12].

Upper limit of quantification:

Theupper limit of quantification (ULOQ) is the maximum analyte concentration of a sample that can be quantified with acceptable precision and accuracy (bias). In general, the ULOQ is identical with the concentration of the highest calibration standard [5, 12, 16].

Quantification Range:

The range of concentration, including the LLOQ andULOQ that can be reliably and reproducibly quantified with suitable accuracy and precision through the use of a concentration response relationship [19].

STANDARD CURVE (CALIBRATION CURVE):

The standard curve for a bioanalytical procedure is the existing relationship, within a specified range; between the response (signal, e.g. area under curve, peak height, absorption) and the concentration (quantity) of the analyte in the sample i.e. calibration (standard) curve is the relationship between instrument response and known concentration of the analyte. It is also called as calibration curve [4]. A calibration curve should be designed by using the same biological matrix in which the intended study is to be done by spiking the matrix with known concentration of the analyte [15].

A calibration curve should consists of a blank sample (matrix sample processed without internal standard), a zero sample (matrix sample processed with internal standard), and six to eight non-zero samples covering the expected range, including LLOQ. The lowest standard on the calibration curve should be accepted as the limit of quantification if the analyte response is at least five times the response compared to the blank response and if the analyte response is identifiable, discrete and reproducible with a precision of 20% and accuracy of 80-120% [4, 5, 15, 16].

RECOVERY:

Recovery experiment should be performed at three concentrations (low, medium and high) with un-extracted standards that represent 100% recovery [20]. Recovery of the analyte need not be 100% but the extent of recovery of an analyte and an internal standard should be consistent, precise and reproducible. As already mentioned above, recovery is not among the validation parameters regarded as essentials conference reports. Most authors agree that the value for recovery is not important as long as the data for LLOQ, LOD, precision and accuracy (bias) are acceptable [12].

Response of analyte spiked into matrix (processed)

Absolute recovery = ----------------------------------- × 100

Response of analyte of pure standard (unprocessed)

Nevertheless, the guidelines of the journal of chromatography require the determination of the recovery for the analyte and the internal standard at high and low concentration. Recovery does not seem to be a big issue for forensic and clinical toxicologists as long as precision, accuracy (bias), LLOQ and especially LOD are satisfactory. However, during method development one should of course optimize recovery [10, 12].

STABILITY:

The definition according to Conference Report II was as follows: The chemical or physical stability of analyte in a given matrix under specific conditions for given time intervals. The aim of a stability test is to detect any degradation of the analyte of the interest during the entire period of sample collection, processing, storing, preparing, and analysis. The condition under which the stability is determined is largely dependent on the nature of the analyte, the biological matrix, and the anticipated time period of the storage (before analysis). [4, 5, 12]

The FDA guidelines on Bioanalytical method validation as well as the recent AAPS/FDA white paper require evaluating analyte stability at different stages and should be confirmed for every step of sample preparation of analysis, as well as the conditions used for long term storage.

i. Freeze Thaw Stability:

During freeze/thaw stability evaluations, the freezing and thawing of stability samples should mimic the intended sample handling conditions to be used during sample analysis. Stability should be assessed for a minimum of three freeze-thaw cycles [21].

ii. Bench-Top Stability:

Bench–Top stability experiments should be designed and conducted to over the laboratory handling conditions that are expected for study samples [21, 22].

iii. Stock solution stability:

The stability of stock solution must be evaluated at room temperature at least for 6 hours [23, 24].

iv. Long-Term Stability:

Long-term stability evaluations will be performed to demonstrate the stability of the analyte in the matrix for longer duration of time. The anticipated duration for the long terms stability should cover the duration of time form the first sample collection to the last sample analysis of the study [25].

v. Short-Term Stability:

The stability of the analyte in biological matrix at ambient temperature should be evaluated. Three aliquots of low and high concentration kept for at least 24 hrs and then analyzed [22, 23, 24].

ROBUSTNESS:

According to ICH guidelines. The robustness of an analytical procedure is the measure of an it’s capacity to remain unaffected by small, but deliberate variations in method parameters and provides an indication of its reliability during normal usage. Robustness can be described as the ability to reproduce the ( bioanalytical )method in different laboratories or under different circumstances without the occurrence of unexpected differences in the obtained result(s), and a robustness test as an experimental set-up to evaluate the robustness of a method [22, 23, 24].

RUGGEDNESS:

Ruggedness is a measure for the susceptibility of a method to small changes that might occur during routine analysis like small changes of pH values, mobile phase composition, temperature, etc. Full validation must not necessarily include ruggedness testing; it can, however, be very helpful during the method development / pre-validation phase, as problems that may occur during validation are often detected in advance. Ruggedness should be tested if a method is supported to be transferred to another laboratory [22, 23, 24].

SPECIFIC RECOMMENDATION FOR BIOANALYTICAL METHOD VALIDATION:

1. For validation of the bioanalytical method, accuracy and precision should be determined using a minimum of five determinations per concentration level (excluding blank samples). The mean value should be within 15% of the theoretical value. Other methods of assessing accuracy and precision that meet these limits may be equally acceptable.

2. The accuracy and precision with which known concentrations of analyte in biological matrix can be determined should be demonstrated. This can be accomplished by analysis of replicate sets of analyte samples of known concentrations QC samples from an equivalent biological matrix.

3. Reported method validation data and the determinations of accuracy and precision should include all outliers; however, calculations of accuracy and precision excluding values that are statistically determined as outliers can also be reported.

4. The stability of the analyte in biological matrix at intended storage temperature should be established.

5. The stability of an analyte in matrix at ambient temperature should be evaluated over a time period equal to the typical sample preparation, sample handling, and analytical run times.

6. Reinjection reproducibility should be evaluated to determine if an analytical run could be reanalyzed in the case of instrument failure.

7. The specificity of the assay methodology should be established using a minimum of 6 independent sources of the same matrix[12].

REFERENCES:

1. Jurgen Burhenne (2012), Bioanalytical method validation. Journal of analytical and bioanalytical techniques; 3(7).

2. U. S. Department of Health and Human Services Food and Drug Adinistration Center for Drug Evaluation and research (CDER) Center for Veterinary Medicine (CVM)(2013) Guidance for Industry, Bioanalytical Method validation.

3. Rozet E1, Dewé W, Morello R, Chiap P, Lecomte F, et al. (2008) Risk-based approach for the transfer of quantitative methods: bioanalytical applications. J Chromatogr A 1189: 32-41.

4. Lalit V. Sonawane, Bhagwat N. Poul, Sharad V. Usnale, Pradeepkumar V. Waghmare and Laxman H Surwase (2014), Bioanalytical Method Validation and Its Pharmaceutical Application- A Review. Pharmaceutica Analytica Acta; 5(3): 1-7.

5. A. Kirthi, R. Shanmugam, M. Shanti Prathyusha, D. Jamal Basha, (2014) A review on bioanalytical method development and validation by RP-HPLC. Journal of global trends in pharmaceutical sciences; 5(4): 2265-2271.

6. Priyanka Patel, Nilesh Patel, Ashok Patel, Ajay Patel, Amit Vyas (2016), Bioanalytical method development and validation: A review. International journal of applied pharmaceutical and biological research; 1(2); 191-196.

7. Yadav AK, Singh SK, Yashwant, Verma S (2012) Bioanalytical Method Validation- How much and Why: A Research prospective. Int J of Nat Prod Sci 1: 123.

8. Patil S, Pandurang ND, Kuchekar BS (2009) Bioanalytical Method Development and Validation: Guidelines Latest reviews. Pharmainfo.net 7: 1-8.

9. Vinod P. Shah (2007), the history of bioanalytical method validation and regulation: Evolution of a guidance document on bioanalytical methods validation. The AAPS Journal 9(1): E43-E47.

10. Komal Arora and H. V. Gangadharappa, (2016) An Approach to bioanalytical method development and validation: A review. International Journal Pharmaceutical science and Research; 7(6): 2291-2301.

11. Mary T, Gilbert T, Irina Barinov-Colligon and Joy R. Miksic (1995), Cross-validation of laboratories. Journal of pharmaceutical and biomedical analysis;13; 385-394.

12. Gaurv Tiwari and Ruchi Tiwari (2010), bioanalytical method validation: An updated review. Pharm methods; 25-38

13. Michael Swartz and Ira Krull Validation Viewpoint Editors, (2003), Validation of Bioanalytical Methods-Highlights of FDA’s Guidance LCGC NORTH AMERICA21 (1).

14. S. Braggio, R. J. Barnaby, P. Grossi, M. Cugola (1996), A strategy for validation of bioanalytical methods. Journal of pharmaceutical and biomedical analysis; 14; 375-388.

15. Pushpa Latha E. and Sailaja B. (2014) Bioanalytical method validation by HPLC: A review. Journal of medical and pharmaceutical innovation;1(6): 1-9.

16. E. Rozeta, R.D. Marinia, E. Ziemonsa, B. Boulangerb, Ph. Huber (2011), Advances in validation, risk and uncertainty assessment of bioanalytical methods. Journal of Pharmaceutical and Biomedical Analysis: 55:848–858.

17. M. A. Potdar

18. Mohammad Mahdi Moein, Aziza El Beqqali, Mohamed Abdel-Rehim (2016) Bioanalytical method development and validation: criticalconcepts and strategies; 1-37.

19. Marian Kelley and Binodh DeSilva (2007), Key Elements of Bioanalytical Method Validation for Macromolecules.The AAPS Journal; 9 (2) E156-163.

20. J.R. Lang and S. Bolton (1991), A comprehensive method validation strategy for bioanalytical applications in the pharmaceutical industry - 2. Statistical analyses. Journal of Pharmaceutical & Biomedical Analysis: 9:435-442.

21. Bhusnure O. G., Gandge N. V., Gholye S. B., Sugave B. K., Giram P. S. (2017), Review on bioanalytical method development and validation by chromatographic techniques. IJPPR; 10(1); 76-97.

22. R. Subramani1, M. Purushothaman (2016), Design, Development and Validation of Bioanalytical Methods for Pharmaceutical Formulations – Review. Journal of Pharmaceutical and Biological Research ; 4(2):99–105.

23. Rahul Naudiyal, Praveen Kumar, Preeti Kothiyal (2014), Bioanalytical method development and its validation. International Journal of universal pharmacy and bioscience; 3(4); 321-330.

24. Tijare LK, Rangari NT, Mahajan UN (2016), A Review on bioanalytical method development and validation. Asian journal of pharmaceutical and clinical research; 9(3); 6-10.

25. Rama Rao Kalakuntla , K.Santosh Kumar (2009), Bioanalytical Method Validation: A Quality Assurance Auditor View Point. J. Pharm. Sci. & Res.; 1(3), 1-10.

Received on 21.03.2018 Modified on 05.04.2018

Asian J. Res. Pharm. Sci. 2018; 8(2):107-114.

DOI: 10.5958/2231-5659.2018.00019.X