ISI Report

The efficacy of immunosuppressants is critical for patients undergoing organ transplants or suffering from autoimmune diseases. However, optimizing immunosuppressant dosages remains a complex challenge due to individual variability and the dynamic nature of immune responses. This article explores the application of second-order accuracy models in conjunction with vector autoregression (VAR) analysis to enhance the precision of immunosuppressant therapy. Second-order accuracy methods provide highly precise numerical solutions, while VAR enables robust multivariate time series analysis. This integrated approach aims to improve dosage prediction and patient outcomes. A comprehensive literature review is presented, followed by a detailed description of the research methodology, results from a case study, and concluding insights.