| Hongbo Li |
In the drug development industry, statistical programming plays an indispensable role for clinical trials or real world data analysis. No matter handling the raw data to submission format data and to analysis-ready data, or creating tables, figures and listings, those deliverables are usually generated by statistical programmers. The responsibilities and duties of statistical programmers also include developing data specifications and programming standards to comply with regulatory requirements and guidelines. Therefore, the good quality of statistical programming work will benefit the entire clinical trial or real world data processing and analysis.
How to become an expert in statistical programming? Based on the author's past more than 15 years industry experience, excellent coding/programming skill (using SAS, R or other software) is not enough at all. Statistical programmers work with biostatistician and data management very closely, and also collaborate with other functional teams like clinical operations, medical writing/clinical development, regulatory affairs, PV (pharmacovigilance), PK/PD (pharmacokinetics/pharmacodynamics) and Biomarker etc. Thus, a good statistical programmer should not only have programming technical, but also statistical knowledge (understanding SAP, mock shells, and statistical modelling etc.), clinical/medical knowledge (for example, knowledge on clinical trials), familiar with CDISC standards and regulatory requirements/compliance checks, having idea about EDC database (electronic data collection system) and performing UAT (user acceptance test) as well as external data collection/transfer process. Also, project management skills and collaborative abilities with cross-functional teams are the essentials to have too for a good statistical programmer. This paper aims to conduct a discussion on those key elements to become an expert in statistical programming area.
Currently, statistical programmers are in high demand due to the growing importance of new drug development in the pharmaceutical and health care industry. Although artificial intelligence technology develops rapidly, the role of statistical programmers is still crucial in the design, development, and execution of data collection, cleaning, manipulation, and statistical analysis. It makes a meaningful contribution to the scientific research for drug development. |