Optimized Differential Derivative UV Spectrophotometric Assay For Enhanced Accuracy In Orlistat Quantification
Ch.Sakhinamma1*,
A.Sisindri2, B.Mourya Vardhan2,
K.Manasa2, K.Lakshmi Samyuktha2, M.Swapna2, Y.Prapurnachandra3
1Assistant Professor, Department of
Pharmaceutical Analysis, Ratnam Institute of Pharmacy, Pidathapolur(V),
Muthukur(M), SPSR Nellore Dt. 524346 A.P. India.
2 Department of Pharmaceutical
Analysis, Ratnam Institute of Pharmacy, Pidathapolur(V), Muthukur(M), SPSR
Nellore Dt. 524346 A.P. India.
3 Professor &
Principal, Department of Pharmacology, Ratnam Institute of Pharmacy, Pidathapolur(V),
Muthukur(M), SPSR Nellore Dt. 524346 A.P. India.
ABSTRACT
A novel and validated UV
spectrophotometric method using differential derivative techniques was
developed for the quantification of Orlistat in pharmaceutical formulations.
The method was assessed based on various analytical parameters, including
linearity, precision, accuracy, sensitivity, ruggedness, and robustness. The
assay results indicated a percentage recovery of 98.74%, confirming compliance
with Pharmacopeial standards. Linearity studies showed high correlation
coefficients (r² ? 0.999) for zero-order, first-order, and second-order
derivative methods, ensuring reliable quantification. Precision and
repeatability assessments demonstrated low relative standard deviation (%RSD) values,
indicating excellent reproducibility. Recovery studies revealed percentage
recoveries between 109.81% and 131.16%, highlighting the method's accuracy.
Sensitivity analysis, expressed through the limits of detection (LOD) and
quantification (LOQ), confirmed the method’s capability to detect low drug
concentrations. Ruggedness and robustness evaluations showed that minor
variations in experimental conditions did not significantly impact the method’s
performance. The validated UV spectrophotometric approach is simple, precise,
and cost-effective, making it suitable for routine quality control of Orlistat
formulations.
Keywords: Orlistat, UV Spectrophotometry, Derivative
Spectroscopy, Optimization, Validation.