RE:RE:RE:RE:Improving results yet
I've never really minded how they project the timeline for full FDA approval as that is the only way that the can do it and be honest. They would get in trouble to predict anything faster or to predict accellerated approval. I think they would be a very good candidate for AA.
By way of example, it seems like most drugs take 2-3 years from AA to get final approval. But the great thing about AA is that they can sell the drug in the meantime.
A recent example is interesting. Takeda had AA for Mobocertinib for NSCLC back in Sept 2021. They started selling and sales may have been quite good. However, once the full patient numbers were reported, it turned out that they didn't have the evidence that the drug was better. It was withdrawn in Oct 2023.
I see TLT as needing the full 18 m data set on 100 patients to get final FDA approval. But if you have good statistical support you can get AA much sooner showing that the data is looking good. For example, if they chase down the 18 m data and find that all 450 day CR's stayed CR then you could make a statistical case that you will soon have enough info for AA based on durable response part.
Better yet, I've said before that all 4 in a row CRs (green from 90 to 360) stay CR to 450 with no conversion to IR or NR, so it would be cool if that held true for the 18 m follow up. In which case, you could make a statistical case that 360 day follow up is enought to confirm durable CR. 360 become the new 540 :)
Again I'm talking the continous CR patients for the above example. The green all the way across ones.