"Cu6 had only 5 in a phase 2a trial"If 5 is the number you need...

Recruiting just a few patients (such as 11) is fine: This is a Phase 2 trial for a rare disease. This was by design, and was meant to achieve a certain goal. In this case, all they needed was to show that the drug works and its safe, (and IMO and more importantly) in a different indication from previously. At this stage, you just need to do enough to be confident of moving to more costly, larger late stage trials (safe, and efficacious = GO).

Also remember: the participants were their own controls so the data points are double (before versus after). In a Phase 3, they will have an activeversus control.

Furthermore: Why would you recruit 100 participants for an observational study, incurring higher costs on a study that returns limited use results (vs a Ph3), when you know you will still need to use the same pool to find potential Ph3 participants, when you can get all the information you need from 11?

Actually, it's not quite true that "smaller population = more difficult to achieve statistically significant outcomes...". This study achieved statistical significance with a small sample of just 11. There is more to the p-value level than just the sample size (e.g: treatment effect size, type of data, etc).

An exceptionally good treatment requires a small number to prove its superiority (versus baseline or control). In a clinical trial with a control group, you get stopped once interim analysis shows that your results are so superior that it pointless to continue and hence the controls are being disadvantaged.

https://doc-aids.com/a-lesson-on-sample-size/

"It’s not the number trialled. It’s the P Value that matters" (in response to: "Only 11 people tested... This is not a good number" by @TemptingTrade)

While the @TemptingTrade was wrong, the statement is (arguably) incorrect. The number actually matters and in fact, good science will chase numbers and let the p-values take care of themselves.

In theory, NEU executives only found out about the p-values in the last few days, yet the numbers were known already (it was part of the design). Even with p values of 6% (close to 5%), and as long as safety was confirmed, they could have chosen to proceed and that would have been fine: all you need is increase the number of participants (eg: make it 13 instead of 11), and you get back below the 5%. So, its the number that matters.

"... It's common sense that having only 11 patients in a phase 2 trial is TERRIBLE..."

Clearly, this commonly held belief (if that's what you mean by common sense, and if indeed it is common), is just a myth. Its WRONG!

Just stop for a minute, and imagine what the brains of the person who invented this treatment might be like! Clearly, very uncommon, I would say.

Then, after accepting that they are super smart individuals, ask yourself why on earth they would choose to design a study with a sample size of just 11! At this point, I hope you are beginning to realise that, our failure to understand them, does not in any way make us (in our common sense), superior. They know what they are doing.

And you might be right: its uncommon stuff! But then, isn't that the reason we are backing them with our hard earned dollars, instead of setting up shop in some corner, where we can cook our own smart therapies?

"Cu6 had only 5 in a phase 2a trial"

If 5 is the number you need to prove that a person drinking your potentially poisonous medicine won't drop dead immediately after swallowing it, thats what you go with. You then assess the results, then go out and experiment on others. So, 5 is fine for the stage and purpose of your study, especially with very powerful drugs.