Clinical Trial Design and Conduct: Roundtable Discussion

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 (Research Manager), Gillian Dunngalvin (Statistician), Onthatile Serehete (Study Doctor), and Alice Eggleston (Physician Assistant).

The discussion will be presented in an interview-style format, if you want to view the full video, enter your details at the end of this webpage.

Note: The following interview has been edited for readability purposes.

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?

Topics Discussed in the full video;

Why is data important and what are the barriers and solutions to it in trial design?

What is the general size of the trials involving microbiome therapies versus clinical support tools?

What are the main challenges and opportunities to apply clinical data to real-world data or are they mutually exclusive?

If you want to combine safety and efficacy in one clinical study how can you better choose the study population?

What is the normal clinical trial process?

(Suszie Tyree, Research Manager)  

“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, Physician Assistant)

“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, Medical Doctor)

“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 allice for your description of the ongoing study and Susie for your description of the protocol part.

(Gillian Dunnglavin, Biostatistician)

“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 Tyree, Research Manager)  

“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 Dunnglavin, Biostatistician)

“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 Serehete, Medical Doctor)

“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 Dunnglavin, Biostatistician)

“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 Eggleston, Physician Assistant)

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 Serehete, Medical Doctor)

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 Dunnglavin, Biostatistician)

“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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Speaker(s) Bio

SUSZIE TYREE | Scientific Officer at Atlantia Clinical Trials

Suszie Tyree is a Medical Writer for Atlantia Clinical Trials with a background in scientific research. Suszie received her Master’s degree from Otago University (New Zealand) studying the role of high-fat diet and dietary hormones on brain functions related to anxiety. Following that, Suszie gained her PhD from the University of Potsdam (Germany) in collaboration with the German Institute of Human Nutrition studying food choice behaviours and neural processing of taste information. Prior to joining the team at Atlantia, Suszie also spent three years as a Postdoctoral Research Fellow at Stanford University (California, USA). At Atlantia Suszie develops research protocols and ethics application documents for clinical trials testing food and microbiome-based products on a range of health measures including cognition, microbiome analysis, glucose-response, bone-health, etc. Suszie is also involved in developing clinical study reports to present findings from the studies carried out at Atlantia.

GILLIAN DUNNGALVIN | Statistician at Atlantia Clinical Trials

Gillian works as the statistician for Atlantia Clinical Food trials, which provides clinical trial expertise for the food, beverage and supplements sector. We conduct studies in functional ingredients, nutraceuticals, medical foods and dietary supplements, providing an end to end service. Her background is in psychological medicine and consumer/patient perspectives, primarily in chronic illness and nutrition. As a psychologist and statistician, Gillian has the unique perspective of understanding the interplay between physiological and psycho-social factors within clinical trial research.

Data integrity and multi-disciplinary collaboration are a central part of her work. She teaches research methodology and statistics at third-level and has published in the health field. In addition to her PhD research in chronic illness management, she is part of multi-disciplinary international team which validated ED05 dose of peanut, published in 2018. Currently she is the scientific communications manager for the EU COST Action ‘Core Outcome Measures for Food Allergy’. This project addresses the Societal Challenges in Health by improving our understanding of health and our ability to reliably monitor health outcomes, and demonstrates new options for healthcare delivery. The outcomes will help improve the quality of clinical trials, and the Action will advance the career of young researchers, strengthening Europe's leading position in pharmaceutical sciences.

ONTHATILE SEREHETE | Medical Study Manager at Atlantia Clinical Trials

Onthatile Serehete is a Clinical Research Doctor with a background in global pharmaceutical and nutraceutical research trials in both Ireland and South Africa. She obtained her primary medical qualification from the University of the Free State and worked as a junior doctor before completing her Masters in International Health and Tropical Medicine from the University of Oxford in 2017. She worked in both public and private healthcare before moving into clinical research where she worked as an Investigator across several therapeutic subject areas including HIV, NASH, Diabetes, and Osteoarthritis. In addition to her full-time role at Atlantia Food Clinical Trials as a Study Doctor, she is busy with her Royal College of Physicians MRCPI exams.

ALICE EGGLESTON | Clinical Research Investigator at Atlantia Clinical Trials

Alice Eggleston is a certified Physician Assistant at Atlantia Clinical Trials with nine years of clinical research experience in various fields. Her first role after completing her undergraduate studies at Saint Louis University was as a Research Assistant at the Rush Alzheimer’s Disease Center in Chicago, which sparked her interest in clinical research and epidemiology. She later attended George Washington University to complete a dual Masters's program in Physician Assistant Studies and Public Health, with a focus in Community Oriented Primary Care. She practiced primary care in Washington, DC at a federally qualified health center, and also served as Clinical Research Manager and sub-investigator for infectious disease studies, implementing primarily HIV treatment and prevention clinical trials. She joined Atlantia in Chicago in November 2020 and functions as the primary study clinician for participants in trials related to functional food, nutraceutical, and microbiome investigations.