Share Price, page-150

Hi mpec, I must admit I can't remember the exact numbers that were in the Phase 2 vs the Phase 3, and even with those numbers its would be hard to say as it would depend upon the statistical method being used and the data variance. However, I can say that from my understanding of the statistical analysis normally used in these types of trials (1) increasing the number of patients in the trial makes a BIG difference to being able to prove statistical significance - is probably one of the biggest factors and (2) the difficulty of proving statistical significance is partly down to the size of the difference, but is even more affected by the variance (e.g. the noise in the measurements) and when you have subjective measures as are being used in these trials then this noise tends to be quite high (rather than an objective measure like the level of some chemical in a blood test, which won't have many errors/noise), thus making it harder to achieve statistical significance with even a large change. Again, one of the best (in fact only) ways to address the noise in subjective measures is through increased 'power', which means having lots more subjects. So the fact the trial only needs to duplicate phase 2 results but has a far larger number of participants effectively sets a lower bar for the phase 3 trial to achieve success - put another way the phase 3 trial is statistically far more likely to be successful than the phase 2 trial (if there is in fact a real underlying benefit to be measured that is). The fact the trial was also run for significantly longer with phase 2 results suggesting improvements increased with time, is also likely to add to the ability of the phase 3 trial to achieve statistical significance.