An Introduction To Biostatistics In Clinical Trials
A biostatistician is not just a number-crunching individual providing a p-value, making sense of data and identifying whether treatment A worked better than treatment B. Biostatisticians in clinical research are typically integral members of project teams providing advice throughout the entire compound development process, offering far more than a service just to be dipped in and out of whenever numbers crop up.
To leverage fullest benefit from our wide-ranging knowledge and skills, biostatisticians should be involved in the design of a trial as early on in the process as possible. At the idea stage of a new clinical trial, we can provide expertise in the experimental design, the size of the clinical trial, optimising the use of limited resources available. Bayesian frameworks, adaptive designs, interim analyses, randomisations, analysis methods, superiority vs non-inferiority vs equivalence and the all-important p-value are but a number of topics our statistical consultancy team shall cover over the coming blog posts.
Statistics is still a relatively new science and is continually evolving, in much the same way medicine is. Many avenues are there to be explored still, many are being researched already. The origins of Statistics can be traced to centuries ago with the collection of data and subsequent simple descriptive summaries – which is a retrospective look at data. We’ve come a long way since then, and are now able to help in experimental design, taking a prospective approach. The p-value (which basically summarises whether the observed data could have happened by chance), only came to exist a little over 80 years ago. Sir Ronald Fisher introduced the world to the concept of the p-value and since then Statistics has come on in leaps and bounds. Sir Ronald Fisher is often regarded as the Grandfather of modern day statistics.
Quanticate’s Statistical consultancy team has experience in biostatistics at the early stage of clinical trials in the field of Bayesian statistics.
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