In this unique virtual gathering, some of Atlantia Clinical Trials leading experts come together to offer insights & solutions to many sought-after industry queries. These experts included Suszie Tyree (previously Atlantia's Research Manager), Gillian Dunngalvin (Statistician), Onthatile Serehete (previously Atlantia's Study Doctor), and Alice Eggleston (previously Atlantia's Physician Assistant).
Topics Explored:
- What is the normal clinical trial process?
- What are the microbiome endpoints that you usually look at?
- When running clinical trials for microbiome-based products would you exclude vegetarians?
- If you would choose a healthy test population, how would you measure the true health effect of the intervention?
What is the normal clinical trial process?
Suszie Tyree:
“I am in the role of research manager at Atlantia, so I’m after sales, the research projects start with us so our first step is to get into the protocol development, so putting together what the main aims of the study are. One of the first steps we have is defining our objectives, which are our main goals of the trial. So we specify what we want to measure, for example, the effect of 12 weeks of treatment on a probiotic on stress, and then for that objective, we would define the endpoint; so how we're going to measure that because we want to know what assessment tools we're using.
For example, for stress we would run through some possibilities, so for example there are lots out there like the Cohen’s precision scale is a popular one, and we would define what an improvement would mean for that, where we would want to see a decrease in Cohen’s perceived stress score over that 12 weeks and usually, we have a couple of different objectives in the trial, so we would normally have a primary which is our main one, the one we care most about and then you can have some secondary objectives as well.
Sort of hand in hand with stress often is sleep, so you might want to put in a sleep assessment as your secondary and then if you have things that you're looking at where you're not really sure what direction they're going to go, we'd put those in our exploratory. For example, we could put in the effect on the microbiome over 12 weeks and so we're not sure how the different bacterium groups are going to change but we want to see it so we would add that in as an exploratory endpoint, and so that is sort of defining our objectives and endpoints.
Then we would look at what population we want to study which is quite important to figure out, whether you're looking at a healthy population or a diseased population. You would define that in your inclusion/exclusion criteria to make sure that you're looking at the people that you want to be looking at, then we'd get into the visit by visit running it down, what we're going to do with our participants, when the assessments are going to fall, screening visits, baseline visits, sort of just figuring out what the trial is going to look like”
Alice Eggleston:
“So my role as a physician assistant in the Chicago site of Atlantia, i help oversee the implementation of the clinical trial, so after we get the kind of handoff from the protocol development team then it comes to us and we have a site of research coordinators and clinical trial assistants and phlebotomists. So we all work together along with the project manager and operations manager to ensure that the study flows smoothly so we have somebody who recruits and then they bring us the participants, we do a screening visit to assess that they're the right people for the protocol and then depending on the protocol we'll follow along for a couple of weeks or months and provide them the intervention. Whether it's a probiotic or we're doing oligosaccharides, so different investigational products.
The participants will have their blood drawn, they'll get questionnaires throughout the study, so depending on what is involved in the protocol and what the sponsor is looking to address, we are the ones that implement all of that and collect all that data we observe for safety and tolerability.
Then we collect their responses on different kinds of questionnaires, whether about signs and symptoms or about quality of life or mood. Then we enter it into an electronic case report form. Then once we have all of our participants and they've gone through all of their visits we would do a close-out visit. Throughout the trial, the study is monitored by a clinical research associate who ensures that we're following all the steps that we need to make sure that we're reporting correctly and we work closely with the principal investigator for any issues along the way."
Onthatile Serehete:
“We maintain as clinicians patient safety, we work very closely with the operations team to ensure that everything goes well and then at the end we review if there have been any clinical problems and then once the data has been collated and monitored to make sure that it is reliable data for the sponsor, we have a close out and everything is handed to Gillian (Biostatistician) who handles the stats.”
and she'll tell you more about what she does with the sponsor with the data that we've collected throughout the trial well thanks Onthatile and Alice for your description of the ongoing study and Susie for your description of the protocol part."
Gillian Dunnglavin:
“At the end of the trial then once the last participants' last visit has been done, we move on to the cleaning of the data ensuring that it's valid and accurate and has high quality. Included in that we'll allocate the participants into populations, so those populations can be the intention to treat or also known as the ‘full analysis set’ and the best way to view that population is your real-world population.
They may have not taken every single dose of the product, they may have gotten ill during the trial and had to take an antibiotic or an nsaid and we make a decision on how those medications and those different events that occur during the trial will impact both safety and efficacy.
We make that decision during what's called a ‘blinded data review’ that has a committee, and that committee is made up of a statistician, a clinician, a principal investigator as well as a sponsor representative. Once we're happy with the allocation of our intention to treat we also look at our ‘per protocol’, and the best way to view that is our perfect population.
They didn't take anything that they weren't meant to, they took all the products as they were needed, so that's the population that's a ‘per protocol’. It's important to know when we're allocating people to these two different populations that the intention to treat or the full analysis set is most valuable to the regulatory bodies as well to publication standpoint, and the reason for that is the generalizability of results. If we look at someone taking a product in the real world, they're not going to take it every day, they're not going to take it every single morning on a fasted stomach as you require them to do it, they'll take it on a more ad hoc nature, which is human nature so to take that into account that's why regulatory bodies want to see that your product works in that intention to treat or that real-world population. Once we've allocated people into the populations and we decided it's clean and we're good to go we proceed to database lock on blinding and we go on to the analysis phase of the trial. This is where we run statistics and then we come back to the clinical team and our pi, who gives the interpretation for the results.”
What are the microbiome endpoints that you usually look at?
Suszie:
“Obviously microbiome is an ever-evolving field and there's a lot to be looking at, so this does change over time sort of as we get more information about it at the moment sort of our key analyses are looking at things like alpha changes in alpha diversity or beta diversity and seeing any sort of significant changes in the presence of some strains of bacteria over others. There are of course a lot of publicly available databases as well as microbiome data so there is some room to be comparing shifts in your population with those that you have seen in publicly available databases.
There are a couple of different ones you can choose from but usually, our standards are sort of the alpha-beta and differential abundance analyses are the key ones that we are sticking to at the minute but it kind of is ever-evolving so it could change in six months."
Gillian:
“Linking in with what Suszie was saying, it really depends on where what phase your trial is in development and what objectives are used. So if it's in the exploratory phase and you're just trying to see is there any benefit of your product in the microbiome? then you might do a deep dive in bioinformatics just to see what happens in the patterns. However if your trial is further along in development you may be focused just on the microbiome that is linked to for example fibre and or other products if that was what was in your study. So it really depends on what phase you're on, whether you want to do a whole exploratory look and just try different methods and see, you know what kind of trends are interesting to inform your further study development. Because most trials are part of a dossier package where you have four to five trials or more depending on your goal which start from pilot go to exploratory, and then move into confirmatory trials”
When running clinical trials for microbiome-based products would you exclude vegetarians?
Onthatile:
“No we do not exclude vegetarians, we're looking for real data that affects real people out there, so we would include all sorts of diets and this is information that we would collect with demographics. We want to know how old are you? what do you do for a living? do you smoke? how many units of alcohol do you drink? what is your day-to-day diet? because when we analyse the data before it's unblinded or even after it’s unblinded we might see trends and then we can look back and see oh was there more positive effect on vegetarians versus pescatarians? So no we do not exclude vegetarians, we want a normal sample as much as possible. We mostly tend to exclude medications like antibiotics and people taking probiotics and prebiotics just to avoid confounding and everything like that. It really depends on 1) the investigational product and 2) the type of study that we're doing. Is it confirmatory? is it exploratory? so all that will contribute to how we decide on what is on the exclusion and exclusion criteria.”
Gillian:
“The only time we would really exclude vegetarians was down to their choice themselves, so if the product happened to have animal products within the investigational product, we would, of course, disclose that to the participant before they enrol in the trial and they may then make the decision depending. Some vegetarians it depends so they would make the decision then based on their diet whether they want to be in the trial or not, so yes we keep vegetarians in but we would of course disclose all the ingredients in case there was an animal product within there that would contravene to their preference.”
Alice:
There are some other diets that study participants might be adhering to, to address their clinical symptoms so for example for an ibs study, they might be prescribed to adhere to a low fodmap diet. That's avoidance of certain foods and so for instances like that there are certain diets where they would be excluded just because it would be difficult for us to assess; are the benefits because of their strict adherence to that particular diet or if it's because of the intervention that we give them. So it definitely depends on what the sponsor is looking for, and what they're hoping to learn from their product but there are certain situations where diet can affect the study population.”
If you would choose for a healthy test population, how would you measure the true health effect of the intervention?
Onthatile:
"True health effect, there could be a clinical significance which is what me and allice would assess based on our medical background; blood pressure and vitals and there could be a statistical difference and the two may not match as clinical significance may not match to a statistical difference. One should bear that in mind when they're asking about the effect of any intervention on the test population, that there may be health benefits but not statistically making a difference.”
Gillian:
“One of the things we often see in the publication is the reliance on statistical significance for getting a paper published, p values are influenced by a sample size, so the largest sample size you are the more chance you're going to find natural variations within a population and you may pick up a p-value or statistical significance. However, you'll see an increasing desire from a lot of publications for you to also include confidence intervals or effect sizes, and they really show the true strength of that change.
So is it a natural change? is it a small change? medium large? and then based on that measure of the change, it helps inform clinicians in their interpretation of those results. It's really important that when you're looking at publications, what is the true benefit? that you look at it from okay it's statistically valid but is it also clinically meaningful? and you'll link to that terms like minimal clinical important difference, responder status, and we're seeing more and more publications using these on a regular basis.
I think the question wanted to flag you ‘how can you measure a change over time in a healthy population?’ and it's just using sensitive tools, sometimes we may have a healthy population but require them to be in the lower range within the healthy parameters so that there is still room for improvement. We would also use sensitive questionnaires and measures to be able to pick up on that, that's how we measure it within a healthy population, it can also help with recruitment if you focus on a healthy population especially for your initial studies and then once you narrow down what exactly the effect of your product is, then of course move to either a population that's you know subclinical or a clinical population then and then test your product but for those initial phases I think it's always good just to test it first in the in a healthy population using sensitive measures.”
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