Y.Prapurnachandra

ABSTRACTCancer encompasses more than 277 distinct diseases, each influenced by multiple genetic mutations that drive abnormal cell proliferation. These mutations may arise due to hereditary or environmental factors, significantly contributing to uncontrolled cell growth. Traditional cancer treatments such as chemotherapy, radiotherapy, and surgery have long been the standard of care. However, the emergence of immunotherapy has dramatically transformed cancer treatment, offering improved survival rates and enhanced quality of life for many patients. Immunotherapy has now become a fundamental component of cancer care, spanning from metastatic settings to adjuvant and neoadjuvant therapies across various cancer types. This review explores the historical breakthroughs in cancer immunotherapy that have shaped modern treatment strategies. Additionally, it examines the limitations of current checkpoint inhibitor therapies and the ongoing research aimed at overcoming these challenges. Emerging approaches, including personalized cancer vaccines, modulation of the tumour microenvironment, microbiome-targeted therapies, and metabolomics, are being investigated to enhance treatment efficacy. Immunotherapies such as checkpoint inhibitors and adoptive cell therapies harness the body's immune system to identify and destroy cancer cells, showing remarkable potential in treating both solid tumours and blood cancers. Despite their effectiveness, these therapies present unique toxicities that differ from conventional cancer treatments, necessitating specialized management strategies. Proper diagnosis and treatment of immune-related adverse effects—often requiring corticosteroids and immune-modulating therapies—are critical for patient safety. This review focuses on the mechanisms, clinical impact, and management of side effects associated with checkpoint inhibitors and chimeric antigen receptor (CAR) T-cell therapies, offering insights into the evolving landscape of cancer immunothera

ABSTRACTA 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.