The analytical method validation for the estimation of Orlistat in the formulation and bulk drug was done as per ICH Q2 (R1) guidelines with respect to specificity, linearity, range, accuracy, precision, detection limit, quantitation limit, robustness, and system suitability [15].
Specificity
Specificity was the capability of the method to quantify the analyte in the presence of components which may be accepted to be present. Normally, these consist of impurities, degradants, matrix, etc. [16]. In order to determine specificity, the Orlistat capsules (prepared formulation and marketed formulation) and Orlistat powder were stressed under various conditions to perform forced degradation studies. For all the series, API 1 mg/ml and capsule contents equivalent to 120 mg of Orlistat were taken and prepared for analytical validation.
To 10 ml of prepared stock solution, 10 ml each of 0.1 N HCl and 0.1 N NaOH were added separately. These mixtures were refluxed for 8 h in the dark in order to keep out the probable degradative effect of light.

Preparation of hydrogen peroxide induced degradation product
To 10 ml of prepared stock solution, 10 ml of 3.0% hydrogen peroxide was added. The solution was heated in a boiling water bath for 10 min to completely eliminate the surplus of hydrogen peroxide and then refluxed for 8 h in the dark in order to keep out the possible degradative effect of light.

Preparation of wet heat induced degradation product
The stock solution was refluxed with water for 8 h for wet heat induced degradation. Refluxing was done in the dark in order to keep out the possible degradative effect of light.

Preparation of photochemical degradation product
The photochemical stability of the drug was studied by exposing the Orlistat formulation (prepared and marketed) powder and API powder to direct sunlight for 48 h in the open air.
A paired twotailed t test was done to evaluate the concentration signals obtained for the six standards at t = 0 h with those obtained at t = 8 h. To evaluate the stability of formulations containing Orlistat were analyzed instantaneously after preparation and after 8 h storage at stressed conditions and concentrations were estimated by comparing the relative error (Er), formula as Eq. (1), with injector repeatability relative standards deviation.
$$ \mathrm{Er}=\left({C}_8{C}_0\right)/{C}_0\times 100 $$
(1)
Where C_{8} was the concentration after 8 h storage and C_{0} was the concentration before storage [17].
Linearity and range
The linearity of a method was its capability to get the results which are straightway proportional to the concentration of analyte in the sample. For the estimation of linearity and range, solutions of different concentration of Orlistat containing 1.00, 2.00, 3.00, 4.00, 5.00, 6.00, 7.00, 8.00, 9.00, and 10.00 μg/ml were injected six times per concentration. Area under the curve for each concentration was observed and a graph of Orlistat concentration versus area under the curve was prepared [18].
Method of least squares
Procedure of developing a calibration graph preferably requires a linear relationship between the various responses and the least square method is ideally used for fitting the obtained data into a linear model.
The relationship between the concentration of drug (x, independent variable) and the absorbance of UV (y, dependent variable) can be represented by least square regression analysis as:
$$ Y=f\left(x,a,{b}_{\mathrm{i}}\dots \dots \dots .{b}_{\mathrm{n}}\right) $$
Where a, b_{i}……..b_{n} are the parameters of the function.
The data of unknown parameters must be evaluated in a way the linear regression model fit the experimental value points (X_{i} & Y_{i}) as nearly as possible.
If Y_{i} = α + βX_{i} + e_{i}
The e_{i} represents residuals and a,b are the values for intercept and the slope of the graph given by the Eqs. (2) and (3).
$$ b=\frac{n\sum \limits_{i=1}^n{x}_i{y}_i\sum \limits_{i=1}^n{x}_i\sum \limits_{i=1}^n{y}_i}{n\sum \limits_{i=1}^n{x}_i^2{\left[{\sum}_{i=1}^n{x}_i\right]}^2} $$
(2)
$$ a=\frac{\sum \limits_{i=1}^n{y}_i\sum \limits_{i=1}^n{x}_i^2\sum \limits_{i=1}^n{x}_i\sum \limits_{i=1}^n{x}_i{y}_i}{\sum \limits_{i=1}^n{x}_i^2{\left[\sum \limits_{i=1}^n{x}_i\right]}^2} $$
(3)
Evaluation of standard error (S
_{e})
It is the estimation of the difference between the obtained values and the calculated values of the dependent variable given by Eq. (4).
$$ S\mathrm{e}=\sqrt{\sum \limits_{i=1}^n\raisebox{1ex}{${\left({y}_i{y}_p\right)}^2$}\!\left/ \!\raisebox{1ex}{$\left(n2\right)$}\right.} $$
(4)
y_{i} and y_{p} are observed values and predicted values.
Standard deviation of slope (S_{b}) can be estimated by the formula as given by Eq. (5):
$$ S\mathrm{b}=\sqrt{\frac{\sum \limits_{i=1}^n{\left({y}_i{y}_p\right)}^2}{\left(n2\right)}}\ast \sqrt{\frac{1}{\sum \limits_{i=1}^n{\left({x}_i{x}_p\right)}^2}} $$
(5)
where x_{p} and y_{b} are the arithmetic mean value of x_{i} and y_{i}
Standard deviation of intercept (S_{a}) can be given Eq. (_{6})
$$ S\mathrm{a}=\sqrt{\frac{\sum \limits_{i=1}^n{\left({y}_i{y}_p\right)}^2}{\left(n2\right)}}\ast \sqrt{\frac{1}{\sum \limits_{i=1}^n{\left({x}_i{x}_p\right)}^2}}\ast \sqrt{\frac{\sum \limits_{i=1}^n{x_i}^2}{n}} $$
(6)
Correlation coefficient (r)
It is used to confirm the linear association between the absorbance and the concentration of the Orlistat. The value of ‘r’ can be obtained by applying the Eq. (7)
$$ r=\frac{\raisebox{1ex}{$\left[\sum \limits_{i=1}^n\left({x}_i{x}_p\right)\left({y}_i{y}_b\right)\right]$}\!\left/ \!\raisebox{1ex}{$\left(n1\right)$}\right.}{\raisebox{1ex}{$\left[\sum \limits_{i=1}^n{\left({x}_i{x}_p\right)}^2{\left({y}_i{y}_b\right)}^2\right]$}\!\left/ \!\raisebox{1ex}{${\left(n1\right)}^2$}\right.} $$
(7)
Ordinary least square (OLS) can give prompt factually mistaken outcomes for heteroscedastic information; both OLS and weighted least square (WLS) were tried for heteroscedasticity by F test. In light of the connection acquired among F_{critical} and F_{statistic} (F_{critical} > F_{statistic}), WLS relapse investigation was performed on various weights (w_{i}). Percent relative error (% Er) and complete percent relative error (Σ%Er) were resolved for each model of various weights and model with least Σ%Er was chosen [18]. Scope of created diagnostic technique was resolved dependent on plot got for top zone against concentration and reaction factor against focus for each alignment standard. Further, percent RSD of got reaction factor was resolved to set up proper range [19].
Accuracy
Analytical method accuracy represents the nearness of the values between the standard value and the obtained value. As confirmed by ICH, accuracy gives information regarding the distinction between the mean value and the true value. For the validation of analytical method, there are two practicable methods the estimation of the accuracy, first one was absolute method and the second one was comparative method [20].
Accuracy of the method was evaluated by carrying out the recovery studies at three different levels. The already estimated samples were spiked with additional 50, 100, and 150% of the standard Orlistat and the samples were reanalyzed by the developed method. The practical was performed in triplicate for finding the percent recovery of the Orlistat at different levels in the formulations [21].
Precision
The analytical procedure precision represent the proximity of agreement involving in a series of estimation obtained from manifold sampling of the identical sample under the approved conditions. It represents the ‘reproducibility’ of the method and the most familiar statistical terms used for the precision was standard deviation (SD) [21]. The equation for SD was given by Eq. (8):
$$ \upsigma =\sqrt{\frac{\sum \left({x}_i\mu \right)2}{N}} $$
(8)
σ =  Sample standard deviation 
N =  The size of the sample 
x =  Each value from the sample 
μ =  The sample mean 
The square of the standard deviation is known as Variance. RSD stands for relative standard deviation and also called coefficient of variance. Percent relative standard deviation is given by Eq. (9):
$$ \%\mathrm{RSD}=\left(\upsigma /\upmu \right)\ast 100 $$
(9)
Precision was considered at two level, i.e., intraday and interday precision. Method repeatability was estimated by six replicate injections and six fold estimation of 5.0 μg/ml concentration. The intra and interday variation for the estimation of Orlistat was performed at three different concentration levels of 2.5, 5.0, and 7.5 μg/ml, respectively [22].
Estimation of precision and accuracy
Student t test
Student t test was usually used to evaluate the means of two correlated samples estimated by standard and test methods. It also gives response to the rightness of the null hypothesis within a limit of confidence from 95 % to 99%.
$$ t=\frac{d_r}{\raisebox{1ex}{${S}_D$}\!\left/ \!\raisebox{1ex}{$\sqrt{n}$}\right.} $$
(10)
Where,
d_{r} = X_{r} (standard method) – X_{t}. (Test method)
S_{D} was standard deviation
F test
F test is usually used to test the importance of the difference in variances of standard and test methods. If one preformed n_{1} replicate observations by test methods and n2 replicate observations by means of standard method, then S_{T}^{2} and S_{R}^{2} will not differ extremely if null hypothesis is correct. The F ratio can obtain by Eq. (11) as:
$$ F={S_{\mathrm{T}}}^2/{S_{\mathrm{R}}}^2 $$
(11)
where S_{T}^{2} = variance of the test method
S_{R}^{2} = variance of reference method
If the value of F is less than unity, then procedures used are not significantly different in precision in a given confidence interval [23].
Limit of detection and limit of quantitation
The detection limit of an analytical procedure was the minimum quantity of drug in a sample which can be identified and the quantitation limit of an analytical methodology was the minimum quantity of drug present in a sample which can be quantitatively estimated with reasonable precision and accuracy [17].
The limit of detection (DL) can be calculated by Eq. (12) as:
$$ \mathrm{LOD}=3.3\ \upsigma /\mathrm{S} $$
(12)
where σ = standard deviation
S = slope of the standard curve
The limit of quantitation (LOQ) can be calculated by Eq. (13) as:
$$ \mathrm{LOQ}=10\ \upsigma /\mathrm{S} $$
(13)
The slope S was determined from the equation of the standard curve of the drug (Mohammadi et al. 2006).
Robustness
For any analytical experimentation, the robustness represents the proportion of its ability to stay unaffected by little changes in the system; however, conscious variations in technique parameters gives a sign of its unwavering quality during typical utilization. To evaluate the HPLC method robustness, a few parameters were deliberately varied. Thus, pH of the mobile phase, column temperature, and flow rate were varied. By introducing small changes in the established parameters, the effects on the results were examined [24].
System suitability
So as to confirm the appropriateness of chromatographic framework for planned investigation, system suitability test was performed by six duplicate injections of standard solutions of Orlistat [25]. The various parameters used for testing system suitability were as follows.

Number of theoretical plates (N)
According to sigma or tangential method column, efficiency can be evaluated by degree of peak dispersion as column characteristics. The formula for calculation N can be given by Eq. (14) as:
$$ N=16\ {\left(\mathrm{V}/\mathrm{T}\right)}^2 $$
(14)
where N = no. of theoretical plates
V = retention time
T = width of the peak
$$ \mathrm{HETP}=L/N $$
(15)
where L = length of column
N = plate number
$$ R\mathrm{s}=\left({t}_{\mathrm{R}2}{t}_{\mathrm{R}1}\right)/0.5\ \left({t}_{\mathrm{w}1}+{t}_{\mathrm{w}2}\right) $$
(16)
where t_{R1} and t_{R2} were the retention times of two peaks
t_{w1} and t_{w2} were the baselines lying between the tangents drawn to the sides of the peaks [21].
$$ {A}_{\mathrm{S}}=B/A $$
(17)
where B = distance from the midpoint to the trailing edge
A = distance from the leading edge to the midpoint
$$ \mathrm{RSD}=\left(\mathrm{SD}\ast 100\right)/X $$
(18)
Where SD = standard deviation
X = mean of the obtained data
Method applicability
The dissolution of Orlistat capsules was performed out by eightstation USP type II dissolution rate test apparatus with dissolution media of 3% sodium lauryl sulfate and 0.5% sodium chloride in water to which added 1–2 drops of noctanol, and adjusted with phosphoric acid to a pH of 6.0 at 37 ± 0.5 °C with paddle rotation speed of 75 rpm for 45 min [26]. Aliquots of 5 ml were removed at different time intervals (5, 10, 20, 30, and 45 min) and replaced with corresponding amount of fresh dissolution media. The obtained samples were then diluted further with phosphate buffer of pH 6 and were centrifuged at 2500 rpm for 15 min and filtered through 0.45 μm nylon filter. The obtained samples were appropriately analyzed by validated HPLC method [27].
Statistical data analysis
Statistical analysis of the obtained values was performed using student t test and all the observations were expresses as mean ± standard deviation recovered from three different experiments (n = 6).