If you have ever wondered whether this is someone else's problem, this is the answer.

So why, why do we need statistics in clinical trials? By and large, people are not big fans of statistics all the time and there, there can be antibodies to statistics.

So why do we have to put up with them in clinical trials? Clinical trials aim to establish for a new intervention or treatment safety, is the new treatment safe? Efficacy, does it actually work? Does it benefit? What's the benefit-risk balance? A lot of treatments may have side effects, so if they have a benefit, it, does that outweigh the side effect also? And also, especially in early phase clinical trials, we're trying to identify some sense of an optimal dosing level.

The role of statistics is to quantify uncertainty in any of those aspects above and support decision-making regarding treatment, so regulatory, clinical and ethics decision-making will be influenced by the, these statistical aspects and the quantification of uncertainty around our estimated treatment effects.

The application of statistics does rely on some sort of framework, conceptual framework for how we approach it.

So I will talk about that a little bit, but I don't want to get too bogged down by this notion of inferring something about treatment from observing a, a few participants in a trial.

One aspect is that our clinical trial will define a patient group of interest with inclusion/exclusion criteria So any inference we make from data that we collect in that trial should only be inferred for that patient group that those individuals represent.

What are the key challenges for biostatistics in such a program to maintain quality of decision-making?