Published Paper Details:

Biostatistical analysis has emerged as one of the most crucial applications for the clinical trial systems. The relevance of statistical analysis in the clinical trials cannot be overstated in advancement of the novel pharmaceuticals and therapeutics. Data volumes, including effectiveness and safety summaries, are produced throughout the process of the developing and approving novel medicines. Data standards developed by Clinical Data Interchange Standards Consortium (CDISC) are well-established, widely accepted, and widely utilized by pharmaceutical sector for submissions to the regulatory bodies. Biostatistical programs like PRM, ODM, CDASH, SDTM, ADaM, SAS, and ARDM have come to long way in the recent years, this article highlights those developments. The present study has made an effort to the report on typical difficulties encountered when using biostatistical methods, with every new discovery, there is always a potential pitfall. Even the main endpoint of experiment might be improperly analysed without adequate validation of the model assumptions. Biostatisticians must collaborate closely with the physicians to choose the most suitable statistical methods for data assessment; otherwise, results may be ambiguous or misleading. To guarantee that a clinical trial satisfies the requirements of the regulatory agencies in the drug approvals, future research should concentrate on the strategies that can enhance compliance and validation processes. Clinical trials play a pivotal role in the advancing medical research and improving patient outcomes. Biostatistics methodologies are essential for the designing robust clinical trials and analysing the resulting data effectively. This review explores recent advancements in the biostatistics methodologies, focusing on the innovative approaches that enhance the efficiency, reliability, and the ethical considerations of the clinical trials.