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Testing a Flordis Natural Medicine: Clinical Trial Design

Testing a Flordis Natural Medicine: Clinical Trial Design

Flordis are proud of the preclinical and clinical research that has been done on each of their products. Our point of difference is that we conduct clinical trials on all of our Flordis products so we can better understand the benefit each product will bring to our customers.
Clinical insight
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Testing a Flordis Natural Medicine: Clinical Trial Design

How is a Flordis product tested?

Flordis are proud of the preclinical and clinical research that has been done on each of their products. Our point of difference is that we conduct clinical trials on all of our Flordis products so we can better understand the benefit each product will bring to our customers.
Let’s take a look at how we select for, and design a clinical trial in order to obtain reliable results that you can have confidence in.

Asking the right question

There’s absolutely no point carrying out a clinical trial, without first deciding what you want to find out. 
The key questions you want to ask with a clinical trial are:
1. What is a safe and effective dose?
2. Is the medicine effective – and what is the best way to measure ‘effectiveness’?
The ‘primary endpoint’ of a clinical trial is the main result that is measured to show that a treatment has worked. Clinical trials are set up based upon this. 
The key is to ensure that if you see a ‘treatment effect’ it is not the response of only one individual, and that it is different to the response to a placebo control (i.e. taking nothing at all!). 

The primary endpoint will depend on multiple factors including the health area that the medicine is being tested in, what is already known about the potential mechanism of action of the medicine, and the type of patients that the medicine is thought to benefit.

Ensuring a fair and trustworthy test

‘Bias’ is the potential of a trial to lead to a skewed result, that is different from the truth. Randomization and ‘blinding’ are two methods employed to reduce bias. [1F] 
-    Randomization – the process of assigning participants to different ‘treatment groups’ using a method that is ‘random’  - or down to ‘chance’. For example, this means that people selected to take a medicine vs. a placebo, are ‘randomly’ chosen, so there isn’t any bias when comparing the results. 
-    Blinding – this is the term used when a participant or investigator does not know which treatment they are getting – i.e. they don’t know if they’re taking the medicine or a placebo. This minimizes any bias when reporting effects. Trials can be both double-blind, where neither the investigator or participant know which treatment group they are in. You can also get single-blind trials where it is only the participant who is unaware of what they are taking.
The gold standard for any clinical trial is to use both of these techniques – which is called a ‘double-blind randomised controlled trial’.

The placebo effect

The placebo effect is a phenomenon in which the mind tricks you into believing that a fake treatment has real therapeutic results – i.e. the belief that you are taking the medicine makes you feel better in itself! 
To prove that this is not the case with our natural medicines, we use a placebo control. This is a separate group of participants who take a placebo instead of the medicine. The placebo looks just like medicine, without any active ingredients – so the participants are unaware of which one they are taking.
By running double-blinded randomised controlled trials, Flordis can demonstrate that it is the medicine that is having the beneficial effect - not just the thought of taking the medicine.

Sample size – how many people to test?

A clinical trial often specifies certain conditions in order for participants to be eligible to take part. But beyond that, how do you decide how many people to test your new medicine on? 
There are a number of questions to consider, but key to the decision will be the magnitude of ‘effect’ we are detecting, and with what degree of certainty should that effect be demonstrated? [1H]
Statistical methods can be developed in order to deliver the necessary data, and inform the investigators what population size they will need.  The number of participants in a clinical trial should always be large enough to provide a sufficiently precise answer to the question posed. This is known as the ‘statistical power’.

Significance – proving a product ‘works’

To be able to make a true ‘claim’, and demonstrate a scientifically valid benefit, you need numbers! And that number is known as a ‘p-value’. These are obtained by performing statistical tests.
Significance tests (such as chi-square and t tests) are used to determine how strong the evidence is for superiority of a medicine over placebo – or how likely it is the same result (or treatment effect) could have been achieved by chance. [1I] This value is often expressed as a p-value, which lies between 0 and 1.
The basic principle is that a researcher's theory (of a medicine having an effect) is considered false until demonstrated beyond ‘reasonable doubt’ to be true. This level of ‘reasonable doubt’ is known as the significance level and often in scientific research it is required to be less than 5% (or 1% in some cases). 
When putting this into the context of a p-value, it is interpreted that a p-value less than 0.05 (5%) or 0.01 (1%), indicates strong evidence for the researcher’s theory to be true, and that there is a 95%, or 99% likelihood that the effects observed in the trial were due to the action of the medicine.
All Flordis products have not only been tested in clinical trials, but the trials have been carefully designed to demonstrate that the products deliver a health outcome consistent with our expectations.

References

1.    Institute of Medicine (US) Committee on Strategies for Small-Number-Participant Clinical Research Trials; Evans CH Jr., Ildstad ST, editors. Washington (DC): National Academies Press (US); 2001.
 

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