SNT 25.7% 4.4¢ syntara limited

If you are not a drug development scientist and you were not...

  1. 72 Posts.
    If you are not a drug development scientist and you were not involved in the planning, conduct and analysis of these studies and if you are unfamiliar with the regulatory requirements of NDAs it is better to keep poorly informed opinions to yourself. Alan Robertson has done the hard yards..unlike any of you he has been successful at getting drugs to market; he does know what he is doing. Regulatory requirements are just that, they are not optional, you cannot do your own thing to manipulate the data. In addition to the clinical study report produced by PXS,the FDA will run its own analyses on the data. Analyses are presented on the intention to treat population (ITT) - that is All subjects who were randomised and received a single dose of drug, irrespective of how long they were in the study for. In addition a per protocol population (PP) is analysed - these are the subjects who received at least x months of treatment and who had no major protocol deviations. This is the cleanest population and gives the best data on how the drug works. However the data published in reports is based on the ITT population..this includes all the subjects who may have only taken a few days of drug. Ideally, the ITT and PP should be very similar, but because subjects drop out for various reasons and they dont follow the protocol exactly as they should, the ITT usually shows worse results than the PP. It stands to reason that someone taking drug for only a week wont get the same improvements as someone on it for 6 months, hence the overall effect is diluted. The more dropouts you have the less confidence you have in the results. This is one of the reasons why the p value in the ITT missed significance - this however was not the case for the PP which was significant.
    Drug companies do their best to get the investigators who get the subjects to follow the protocol exactly as is written,but everyone likes to cheat a little. Let me use an analogy - RTA hypothesises that if a driver follows ALL the road rules no-one will ever have an accident. If 1000 subjects were told to drive for 12 months exactly as required by the RTA, without taking any short cuts, never touching our phones, running a red light, never speeding etc how many of us would do so..100%, 80%, 50%? MY guess is that 0% would be 100% compliant and 70% may be 80% compliant. The hypothetical results show that 24 accidents occurred and the hypothesis that following road rules doesnt work and the study fails to meet its p value. Sure the study needs to be designed to allow for issues such as poor compliance, dropouts, estimated effect etc, but equally the subjects and their doctors need to ensure that the data they gather is of extremely high quality and making a u turn against a sign while no-one is looking wont go unnoticed in the analysis. Be patient and have faith.
 
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