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Most solvents are organic volatile chemicals that are used in the manufacture of APIs, excipients and pharmaceuticals. Therefore, there is no therapeutic use of such solvents and they also affect the quality and stability of not only drugs but also their product and should be eliminated to the extent possible to meet product specifications and other quality-based requirements. These residual solvents cannot be completely removed; therefore, they should be within acceptable limits according to regulatory guidelines such as ICH guidelines. GC-HS is the most commonly used technique used for the analysis of volatile solvents. The aim of this work is therefore to develop a simple, specific GC-HS method for the determination of residual solvents in Flurbiprofen. The method was developed accurately and validation parameters were explained. Chromatographic condition was RDS/AL/GC – 03 Parkin Elmer instrument and RDS/AL/GC – 05 by Agilent, column: GSBP- 624 (30m x 0.53 mm x 3.0 µm). The parameters like as Specificity, Precision, Accuracy, Linearity and Range, Limit of Detection (LOD) and Limit of Quantitation testing with Acetone, Benzene, Dichloromethane, Ethyl Acetate, Toluene, Isopropyl alcohol and Bromobenzene. All validation parameters are used in the routine and stability analysis.

Objective: To evaluate MRI\\\'s effectiveness in detecting malignant ovarian neoplasms and differentiating them from benign lesions, using histopathological findings as the gold standard. Methodology: A descriptive study with diagnostic test evaluation was conducted on 50 female patients referred for MRI evaluation of ovarian lesions at Govt. T. D. Medical College, Alappuzha. MRI findings were compared with histopathology. Ovarian neoplasms were categorized based on morphology. Various criteria for malignancy detection were assessed. Results: Using MRI, positivity for any 5 out of 6 general criteria showed: Sensitivity: 95%, Specificity: 83.33%, Positive Predictive Value: 79.17%, Negative Predictive Value: 96.15%, Accuracy: 88% For 6 out of 6 criteria, specificity and positive predictive value increased to 100%, with slight sensitivity reduction. Adding ancillary criteria had minimal impact. Subcategories showed: Cystic/multilocular cystic lesions: Sensitivity: 50%, Specificity: 91.67%, Accuracy: 85.71% Solid-cystic/predominantly solid lesions: Sensitivity: 88%, Specificity: 100%, Accuracy: 92.86% T1 hyperintense lesions: Sensitivity, Specificity, and Accuracy: 100% Conclusion: MRI combined criteria are highly sensitive and specific for detecting malignancy, especially in T1 hyperintense lesions, but less so in cystic ovarian neoplasms. Diffusion restriction and necrosis are strong individual predictors.