<![CDATA[Background: The integration of applied statistics in drug development and clinical trials is essential for ensuring the efficacy and safety of new pharmaceuticals. Statistical methods play a critical role in designing studies, analyzing data, and interpreting results, thereby influencing regulatory decisions and clinical practices. Objective: This study aims to examine the role of applied statistics in the drug development process, particularly within clinical trials. The focus is on identifying key statistical techniques and their impact on trial outcomes and decision-making. Methodology: A comprehensive review of literature was conducted, analyzing various statistical methods employed in clinical trials, including sample size determination, randomization techniques, and data analysis methods. Case studies were included to illustrate the application of these methods in real-world scenarios. Results: Findings indicate that robust statistical methodologies significantly improve the reliability of clinical trial results. Proper sample size calculations ensure adequate power to detect treatment effects, while randomization techniques minimize bias. Additionally, advanced data analysis methods enhance the interpretation of trial outcomes, leading to more informed regulatory approvals. Conclusion: This research highlights the indispensable role of applied statistics in drug development and clinical trials. Emphasizing the importance of sound statistical practices not only improves trial integrity but also contributes to the overall success of new drug therapies. Continued advancements in statistical methods will further enhance the efficiency and effectiveness of clinical research.]]>
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