Latest / Veramed Stories / Season 2 Episode 003 - It’s Just Good Science: Why Inclusive Clinical Trials Matter

Transcript

Season 2 Episode 003 - It’s Just Good Science: Why Inclusive Clinical Trials Matter · Veramed Stories

• 0:00
  Speaker 1: Hello, and welcome to today's episode of the Varamet podcast.
• 0:03
  Speaker 1: I'm your host Zoe And really pleased have you with us for this conversation.
• 0:08
  Speaker 1: Today we're exploring a topic that sits at the intersection of science
• 0:11
  Speaker 0: effects an innovation
• 0:13
  Speaker 1: diversity equity inclusion in clinical trials So subject that I care deeply about and I'm shaped by my many years working on people and learning development space so In this episode will look out real-world consequences of exclusion in clinical research The historical and structural factors that continue to shape trust today, And why more inclusive trials aren't just the ethical choice.
• 0:37
  Speaker 1: They're simply better.
• 0:38
  Speaker 1: science will also explore areas of meaningful progress and celebrate the progress is made everything from data standards in technology To innovation an approaches too early diagnosis as well.
• 0:50
  Speaker 1: There's also taking a look at what the industry can do more off to move forward with purpose and even more courage.
• 0:57
  Speaker 1: As we begin, we want to take a moment to acknowledge that some other themes discussed may feel sensitive or cause an emotional reaction within you as a listener depending on your own experiences.
• 1:08
  Speaker 1: Therefore we wish to invite you to listen in a way that feels right and safe
• 1:12
  Speaker 0: for you.
• 1:13
  Speaker 1: please Feel free to take pause Or even step away at any point if you need To And with That let's Begin the conversation.
• 1:22
  Speaker 1: Hello Roxanne Welcome to the podcast.
• 1:26
  Speaker 1: It's great to have you with us today.
• 1:29
  Speaker 1: And it was great having following your powerful talk that you did at Fuse a few months ago, which you entitled diversity inclusion and equity is just good science!
• 1:39
  Speaker 1: You actually won Best Streamed with that with your co-presenter Chris Ward?
• 1:42
  Speaker 1: That right?
• 1:43
  Speaker 0: Great yes I'm very surprised but absolutely honoured to win Best in stream.
• 1:49
  Speaker 1: Surprised?
• 1:50
  Speaker 1: Congratulations...I don't think we were very surprised anyone.
• 1:55
  Speaker 0: Thankyou
• 1:56
  Speaker 1: Roxanne, you're a technical solution delivery manager here at Varemerge.
• 1:59
  Speaker 1: You've got over fifteen years of experience in clinical programming and can have clear passion for inclusion equity and diversity in clinical research.
• 2:09
  Speaker 1: so as we hop into today's podcast I'd like to just start from the beginning.
• 2:14
  Speaker 1: You created this fascinating data rich thoughtful presentation for Fuse back in November.
• 2:24
  Speaker 1: Was there a moment where you thought we need to talk about this?
• 2:26
  Speaker 0: There's that fantastic question and the journey to create my paper, my presentation was through my own personal experience.
• 2:40
  Speaker 0: Something not just myself but I know others within industry have had similar experiences in the past as well.
• 2:47
  Speaker 0: And it was during discussion for a sort of study kick off.
• 2:54
  Speaker 1: that
• 2:55
  Speaker 0: was for mental health indication, it was for anxiety.
• 3:00
  Speaker 0: A really nice study in which we brought in subjects and after dosing we purposely tried to induce anxiety into actual situations so would get them to read a bit of paper and purposely interrupt them trying score them off the anxiety.
• 3:17
  Speaker 0: there's an interesting study design And during the discussions, it was mentioned that male subjects will do this and then the male subject's will take part.
• 3:28
  Speaker 0: When a question is asked... The protocol doesn't specifically say just males but only females.
• 3:36
  Speaker 0: And explanation we received back was pretty much that women's menstrual cycle makes it very difficult to get a baseline for a reaction, and that is a bit of an inconvenience in quite pesky.
• 3:53
  Speaker 0: And therefore we are just excluding women from this trial.
• 3:56
  Speaker 0: for the woman where I'm inconvenient.
• 3:58
  Speaker 0: That women were being purposely excluded because our reproductive system made things too difficult at the time it was just an accepted answer.
• 4:08
  Speaker 0: but something has always sat with me as I've worked longer than industry on my experience As a woman in the world, just trying to obviously figure out what is okay and not.
• 4:26
  Speaker 0: And I think that as you read more papers on the diversity of women's health You can see through cardiovascular events.
• 4:36
  Speaker 0: Women have different symptoms to men Through different diagnoses, women are more likely to get Alzheimer's than men Through mental health conditions.
• 4:45
  Speaker 0: Even race begins to play a factor in terms of different mental health conditions.
• 4:49
  Speaker 0: And, just sit and see that there is a purpose exclusion because it's considered more difficult as not okay?
• 4:59
  Speaker 0: It doesn't set right with me... I know its uncomfortable for someone who sits on the room and speaks up so all i can do moving forward would be voice speaking up.
• 5:10
  Speaker 0: That what i want to encourage others.
• 5:14
  Speaker 0: but I think that it is absolutely critical for us to move forward together, for the best possible healthcare and medicines for everyone involved.
• 5:25
  Speaker 1: Thank you sharing that.
• 5:27
  Speaker 1: so just on a slightly deeper level then hearing back at point what was the key feeling?
• 5:34
  Speaker 1: You mentioned feeling uncomfortable But Was there anything else That you felt about time?
• 5:39
  Speaker 0: Think of end-of-the day.
• 5:41
  Speaker 0: For me personally, with diversity and inclusion and equity.
• 5:45
  Speaker 0: it comes from my own principles in integrity of what I think is right or wrong.
• 5:53
  Speaker 0: I'm very passionate about being the best possible human being that i can be but also raising a young child so they will be reflecting on who he is for me as well.
• 6:03
  Speaker 0: It's my responsibility to ensure.
• 6:09
  Speaker 0: I'm very much aware a lot of people find DEI an uncomfortable conversation.
• 6:15
  Speaker 0: I am sure it is, but also believe that you need to have it and encourage it.
• 6:24
  Speaker 0: If we keep doing so then no longer becomes uncomfortable or part of our general conversations which should be aimed at.
• 6:33
  Speaker 0: We shouldn't be afraid and hide away from them as they bring out into the light and together make it more known, better for everyone else.
• 6:43
  Speaker 1: Yeah beautiful I totally agree.
• 6:46
  Speaker 1: this might just be us agreeing constantly but i did notice how you made a really good parallel in your presentation around an argument to this as well which is that DE&I isn't about ethics or doing the right thing.
• 7:00
  Speaker 1: It's about accuracy.
• 7:02
  Speaker 1: so I'd like to ask presentation, use the phrase it's just good science.
• 7:12
  Speaker 1: So can you tell me a little bit more about that and how he came to that title?
• 7:17
  Speaker 0: The title sort of came from a conversation I had with an old manager guy called Graham And we were having this discussion on being just good at science.
• 7:31
  Speaker 0: A lot people when they hear diversity equity and inclusion, that automatically think about it as a political or social issue.
• 7:40
  Speaker 0: From our perspective in clinical reporting—it is scientific and practical—it has time and place for being in politics and society.
• 7:48
  Speaker 0: absolutely but I am interested when it comes to my job at the moment.
• 7:54
  Speaker 0: The ultimate goal of clinical reporting get the best possible evidence so that all patients can benefit from safe and effective treatments.
• 8:10
  Speaker 0: I think when we start looking into this, people who participate in clinical trials do not necessarily look like those who will end up taking actual treatment at the end of it.
• 8:25
  Speaker 0: You are working with what you have as a picture right now but it is an incomplete picture and therefore, if you don't have all the data or results then your not going to be able give best possible analysis for your study.
• 8:41
  Speaker 0: And I think as well it's really important with being a scientific issue is that its'nt about finger-pointing.
• 8:51
  Speaker 0: It's just about.
• 8:52
  Speaker 0: let us make our research stronger Let's make our data more reliable.
• 9:02
  Speaker 1: Makes sense to me.
• 9:03
  Speaker 1: When you think back across both your own experience and some of the actual research we did as well, what are the risks for avoiding some of those places?
• 9:16
  Speaker 1: And like you mentioned having that incomplete picture data What other most stark risks that you've seen in your research?
• 9:23
  Speaker 0: So I think they're the more sort of obvious one but that you have found when I started doing my research was in most recent biggest changes in clinical research, which was the NIH Remitalisation Act of four.
• 9:38
  Speaker 0: Which up until that point prior women were not allowed to take part and early clinical trials so single woman using contraceptives even partners who had a vasectomies.
• 9:50
  Speaker 0: The reason being is that in nineteen seventy seven they were excluded to potentially protect potential pregnancies because the world had just went through the Thalala Mai tragedies in the nineteen sixties, which impacted thousands of children.
• 10:06
  Speaker 0: But what was meant to protect future hypothetical pregnancies?
• 10:09
  Speaker 0: Had unintended consequences or massive data gaps and understanding how drugs affected women differently from men delayed progress on women's health also overlooked that opportunity to get little woman choose what she wanted to do with her own body, if they want to take part in clinical research.
• 10:27
  Speaker 0: that was taken away from us.
• 10:29
  Speaker 0: That came at a real cost of healthcare and unfortunately still has an impact today on certain parts of medicine and clinical research.
• 10:40
  Speaker 0: but I think last year the British Health Foundation reported that fifty nine percent of women who are experiencing heart attack or misdiagnosed because the symptoms of a heart attack is still associated to those that are typical for men and not women.
• 10:57
  Speaker 0: And if this is an impact of excluding women from these studies, you don't see the full picture.
• 11:04
  Speaker 0: so not only are you delaying drugs —that could help them—you're also delaying diagnosis as well.
• 11:10
  Speaker 0: it's a ripple effect That you can't ignore.
• 11:15
  Speaker 0: You need sort-of speak up about.
• 11:16
  Speaker 0: essentially again It's not about finger pointing or you excluded woman.
• 11:21
  Speaker 0: This is why we should include women and trying to communicate it as a let's bridge those gaps rather than pointing out other people made in the first place.
• 11:34
  Speaker 1: Yeah, what I've found so interesting speaking with you about this over last few weeks that feels very simple yet powerful.
• 11:42
  Speaker 1: or the idea and solution which has just better diversity equals better evidence for everyone And it might take a while to get to that place, but through your research so far.
• 11:57
  Speaker 1: Is there any positives you'd like really highlight of where we're at now?
• 12:02
  Speaker 1: Are they anything that we can see as areas to solve sooner based on what were already moving forward with?
• 12:11
  Speaker 0: I think the amazing thing would be our right now is We've got the data, we can see everything.
• 12:20
  Speaker 0: There's so many opportunities to share data as well.
• 12:22
  Speaker 0: now there are databases and journals and reports And not to mention that we have so many tools to make a difference Back in nineteen seventy seven.
• 12:31
  Speaker 0: To be able to compare our data In the UK to US would be difficult if you didn't have technology But we could do it.
• 12:38
  Speaker 0: So we had so much opportunity to use tools to help guide this journey.
• 12:44
  Speaker 0: A lot of people won't believe it until they see.
• 12:46
  Speaker 0: essentially, but we have so many more ways to report data for digitalisation that help people understand.
• 12:53
  Speaker 0: So you don't have to be a statistician and you don' t need to become a scientist.
• 12:56
  Speaker 0: is how politicians make decisions or better healthcare?
• 13:01
  Speaker 0: And again just comes down the really simple fact of having conversation in communication.
• 13:07
  Speaker 0: social engagement accessibility information barriers there's.
• 13:15
  Speaker 0: you get more people included and that's the best way to start fixing it right now, is remove those barriers.
• 13:25
  Speaker 1: It's not all doom or gloom.
• 13:27
  Speaker 1: we have some solvable ways and some smart technology to help us get there as well?
• 13:33
  Speaker 0: Absolutely!
• 13:33
  Speaker 0: It isn't all doom and gloom And its very rare for someone who can look at a problem and go I know exactly what they are.
• 13:42
  Speaker 0: We can do this.
• 13:45
  Speaker 0: Therefore, we can fix that.
• 13:47
  Speaker 0: We're not looking at an unsolvable puzzle—we see where the barriers are and gaps are.
• 13:53
  Speaker 0: so therefore we find solutions.
• 13:57
  Speaker 1: Brilliant!
• 13:57
  Speaker 1: In terms of barriers what is research saying?
• 14:00
  Speaker 1: What key barriers do you have to overcome yet?
• 14:03
  Speaker 0: I think unfortunately we've probably experienced a lot through Covid.
• 14:10
  Speaker 0: there's been a lot of mistrust There's a lot of social economical barriers, there is a lot historical trauma.
• 14:17
  Speaker 0: The black and African-American population still think about the absolute atrocities on the Tuskegee stuff for studies in which six hundred men were basically wasted on.
• 14:34
  Speaker 0: they could have gotten access to penicillin.
• 14:36
  Speaker 0: it was purposely withheld from them.
• 14:39
  Speaker 0: It the most profound violations of medical ethics, deception and exploitation.
• 14:47
  Speaker 0: That still underscores that community today—that comes up in discussion now.
• 14:57
  Speaker 0: It will not go away overnight or you have to build trust to remove it.
• 15:03
  Speaker 0: You can't turn around saying that technology was fifty years ago but it still impacts these communities and you need to find ways to help that historical trauma acknowledge it, and help those communities move on from it.
• 15:18
  Speaker 0: Because if we don't build up more mistrust—if people have more mistrust—people will not reach out opportunities for better their healthcare.
• 15:29
  Speaker 0: That is really sad because there are still communities in the situation today.
• 15:35
  Speaker 0: We should do more.
• 15:37
  Speaker 0: to have those discussions and highlight it.
• 15:40
  Speaker 0: I know that people would rather we don't talk about, but you can only learn from your history in there for... It should be spoken and it shouldn't be forgotten or brushed under the carpet-it should still be acknowledged if that happened and then we cannot do again?
• 15:55
  Speaker 1: Yeah yeah i agree on an unaddressed trauma just breeds more hurt and more trauma.
• 16:01
  Speaker 1: You cannot not speak of it.
• 16:03
  Speaker 1: its so important acknowledgement and time to appreciate where someone is coming from, assist them in a meaningful way not treat people like someone else.
• 16:14
  Speaker 1: What do you see opportunity-wise for clinical trial teams to actually practically build more trust with different people on communities?
• 16:25
  Speaker 0: There's so many more opportunities again down to Tills & Technology – social outreach groups that will go into communities explain and have those conversations.
• 16:35
  Speaker 0: Clinical trials are very frightening, whether it's be a phase one or if there is still sometimes seen as very much the guinea pig situation.
• 16:49
  Speaker 0: I think that was about a few years ago by Ben Goldacre called Bad Pharma which really tainted industry quite a bit A lot of people sort-of thing like Again, with Covid.
• 17:02
  Speaker 0: there's so many false information and rumours that created this narrative of everyone being tested on.
• 17:13
  Speaker 0: For someone who works in the industry to hear those sort of conversations is quite insulting because when you're working hard for a drug trial people don't work in it.
• 17:25
  Speaker 0: It makes it difficult but frustrating.
• 17:29
  Speaker 0: If you reach out and educate, have the conversation.
• 17:34
  Speaker 0: You give people opportunities to feel included as well.
• 17:37
  Speaker 0: whether that be actual representation like there's studies I've shown if a doctor who is Black or African American patients are more likely come along take part in trials because they feel that representation the fears that they have about Henrietta Lacks and having no control over their body, it dissipates a bit because people feel like someone who looks at them or acts as if he understands his culture.
• 18:11
  Speaker 0: That is really important when we include people in trials—you cannot just think of them being recruited to a much more personal level.
• 18:22
  Speaker 0: I've seen trials before, like psychiatric trials when you will have raters and facilitators who ask very in-depth personal questions about someone's mental health.
• 18:33
  Speaker 0: That is a vulnerable, terrifying situation where they need to build that trust or safety.
• 18:40
  Speaker 0: It is really important for them to help improve clinical trial participation.
• 18:45
  Speaker 1: What am I pairing there?
• 18:46
  Speaker 1: There are things as fair—obviously it is with a lot of distrust is or the other side of the coin of distrust, is fear.
• 18:55
  Speaker 1: And you've actually just mentioned a lot very practical easy ways to reduce The Fear by including people in their choices they make and including them information that exists.
• 19:05
  Speaker 1: then also having People represent Them.
• 19:08
  Speaker 1: take the time To get to know Them.
• 19:10
  Speaker 1: so all small things but All That Just Dampen that Fear and Reduce that Fear.
• 19:17
  Speaker 1: therefore in turn build trust.
• 19:20
  Speaker 0: There's.
• 19:20
  Speaker 0: there's A really good paper called The Ethnicity Framework, which was published in the UK a couple of years ago.
• 19:28
  Speaker 0: It speaks clearly about ways to include diversity and clinical reporting.
• 19:34
  Speaker 0: One thing that it explains is your recruitment stage is absolutely critical for any clinical trial—the majority of studies will just be a case As quickly as you can, which I understand.
• 19:47
  Speaker 0: this is a time of money in these situations.
• 19:50
  Speaker 0: I totally understand that but are you really recruiting the correct people for the study?
• 19:58
  Speaker 0: and also not only are you recruiting the right people?
• 20:01
  Speaker 0: But will they actually benefit from the study as well?
• 20:05
  Speaker 0: That's very important.
• 20:07
  Speaker 0: again if someone has gone into clinical trials sometimes like i said who knows what their diagnosis will be.
• 20:16
  Speaker 0: They can be very frightened, but that does not necessarily mean it will help them and I think you have to consider this.
• 20:23
  Speaker 0: In doing so, it will expand your screening period or recruitment period which is a cost-to-a business.
• 20:33
  Speaker 1: It's
• 20:35
  Speaker 0: difficult for the coin to balance because how much How much do you charge for someone's well-being and someone's safety in a trial?
• 20:50
  Speaker 0: I don't work on the business side, so there are things that should be considered to make sure they get the best possible participants.
• 21:05
  Speaker 0: You
• 21:07
  Speaker 1: wouldn't have good return on investment if putting people forward who will not benefit from the
• 21:13
  Speaker 0: test.
• 21:13
  Speaker 1: Does that make sense?
• 21:15
  Speaker 0: Yeah,
• 21:16
  Speaker 1: okay.
• 21:17
  Speaker 1: so we've mentioned this sort of human barriers with trust.
• 21:22
  Speaker 1: and we've spoken briefly about data in technology.
• 21:26
  Speaker 1: um So let's just speak about that a little bit more in depth as well.
• 21:31
  Speaker 1: You did in your presentation briefly mention um at clinicaltrial.gov database.
• 21:41
  Speaker 1: Please just briefly explain a little bit more about why that's important in this topic.
• 21:48
  Speaker 0: So the NIH, clinicaltrials.gov is a database that contains thousands and thousands of studies And essentially you can go on under an API and you can select in terms of therapeutic area year sponsor anything at all.
• 22:07
  Speaker 0: You could pull out information from that study which is fantastic.
• 22:10
  Speaker 0: it very much transparency and data sharing.
• 22:14
  Speaker 0: And obviously you can use that information to help build, design future studies.
• 22:19
  Speaker 0: so on paper it all sounds brilliant.
• 22:22
  Speaker 0: we then try to determine the clinical trials of database again because there are many studies where we narrowed down and tried to focus on psychiatric studies between two thousand and twenty nineteen from ten thousand four hundred and something.
• 22:43
  Speaker 0: Studies that trials are pulled out from it, so those great we're like with so much data is fantastic.
• 22:49
  Speaker 0: the problem was always that there was a total.
• 22:54
  Speaker 0: if you can put all these studies together to look at them We had four hundred eighty variables.
• 22:59
  Speaker 0: three hundred of those variables were free text.
• 23:01
  Speaker 0: So sixty two percent off.
• 23:02
  Speaker 0: your variables Are all free.
• 23:05
  Speaker 0: take so?
• 23:06
  Speaker 0: There's no way to standardize that Additionally as well even if you're told that something which is would be considered control terminology, such as age.
• 23:16
  Speaker 0: That again wasn't standard.
• 23:19
  Speaker 0: You'd have age years or age months are H plus something else.
• 23:25
  Speaker 0: therefore again there was something that you'd expect to be standardized wasn't?
• 23:29
  Speaker 0: so it made a very difficult to actually properly do something with.
• 23:35
  Speaker 0: It probably was a little bit advantageous of us to try and date them in the short space of time that we had between getting accepted for views, delivering their presentation.
• 23:47
  Speaker 0: But I think... The lessons from trying together information were really valuable because it made you understand if you wanted to do large-scale analysis on a therapeutic area or demographic.
• 24:03
  Speaker 0: It's not simple and it just really comes down to how your data is collected as well.
• 24:09
  Speaker 0: Economic health should understand the importance of data collection today that we have, why we are so strict to see this standards and compliance and reconciliation and everything like that because order studies –the data–is NOT great!
• 24:26
  Speaker 0: So there was a lot of lessons there—it was very eye-opening in a positive way going right.
• 24:32
  Speaker 0: okay then work around this, how can we figure out ways to try and analyse it better?
• 24:39
  Speaker 0: And we're still doing that.
• 24:40
  Speaker 0: Even though there were no longer a few of our presentation, We are sort-of looking into it because I'm interested in seeing what we can get from all the data they have.
• 24:52
  Speaker 0: There is so much information you could get.
• 24:56
  Speaker 0: It's just trying to find the best way to analyse them.
• 25:02
  Speaker 1: Yeah, I can understand that it's a big undertaking when you're waiting to see if your presentation has been approved and then rushing into the deadline.
• 25:13
  Speaker 1: But yeah also demonstrates really beautifully.
• 25:15
  Speaker 1: how exactly do they say?
• 25:17
  Speaker 1: The data is not as good as it can be.
• 25:20
  Speaker 1: It is harder And will take longer and more investment To look through what technologies we are using at this point through some of this work.
• 25:34
  Speaker 0: Yes, so we were using a Juniper notebook and sort of Python to try and pull out the information and analyze it.
• 25:43
  Speaker 0: I know that just be truly through time restraints.
• 25:47
  Speaker 0: We didn't have opportunity then but now you can use different forms like natural language processing And he can help us do some statistical analysis of textual data.
• 26:02
  Speaker 0: So these techniques allow you to sort of access the data and analyze it a bit better, but easier than standard traditional programming roles.
• 26:13
  Speaker 0: AI especially tools like Cloud Code can really just generate all that code for you as well so we don't have to try and figure out how.
• 26:23
  Speaker 0: I'm not strongest Python programmer.
• 26:26
  Speaker 0: The fact that I have the opportunity to use something like Claude, is hugely beneficial and all these AI tools are coming out.
• 26:35
  Speaker 0: By all means as I would sort of highlight here there's our tools.
• 26:41
  Speaker 0: you don't just blindly go and use them.
• 26:44
  Speaker 0: whatever you get back.
• 26:45
  Speaker 0: it must be correct.
• 26:47
  Speaker 0: You still need human oversight, expertise.
• 26:51
  Speaker 0: or do your own human loop understanding as well, make sure that you are telling the AI what to do and want.
• 27:00
  Speaker 0: That is one thing I really stress because a lot of people have lots of hallucinations out there so they need to be made sure their prompts are absolutely clear-as-they can be in order for your AI to know if it makes decisions or does not come back.
• 27:19
  Speaker 0: Yeah, there's been a lot of challenges and but also what all the learning opportunities in doing this part.
• 27:25
  Speaker 0: The project
• 27:26
  Speaker 1: yeah can definitely save some time on it But it won't take away at critical review.
• 27:31
  Speaker 1: that is needed.
• 27:32
  Speaker 0: You still have to be the human.
• 27:33
  Speaker 0: I didn't do the review yet.
• 27:34
  Speaker 0: Yeah
• 27:36
  Speaker 1: It is your...it..is a colleague To have.
• 27:39
  Speaker 1: but like you say its not your overseer.
• 27:41
  Speaker 1: Its not gonna solve everything for you.
• 27:44
  Speaker 1: It means it's just them two.
• 27:47
  Speaker 0: That's how it is.
• 27:47
  Speaker 0: Like you use SAS to help do your analysis or you use like Excel, to look at a spreadsheet.
• 27:55
  Speaker 0: AI is a tool to help you do your job easier and better but you're still the person responsible for doing that job?
• 28:01
  Speaker 1: Yeah amazing other than getting support from Viramid to make this presentation happen and continue to look into those data sets now what else are you seeing us do differently?
• 28:21
  Speaker 0: From my perspective, one of the hardest things that's probably happened whilst I was sort of preparing for this project is at start last year in January.
• 28:35
  Speaker 0: The FDA had previously had a diversity and equity inclusion plan essentially where they were trying to put forward their future trials very quietly.
• 28:48
  Speaker 0: overnight that documentation goes removed, which was due to presidential order at the time.
• 28:56
  Speaker 0: Which obviously is frustrating and disappointing because I left a will of industry unsure where we're going next.
• 29:10
  Speaker 0: The one positive thing here in Veramedd everyone encouraged me conversation and this presentation, no one had that sort of thing.
• 29:23
  Speaker 0: I've been like oh i don't know... It was very much a case about.
• 29:26
  Speaker 0: regardless of shifting political landscapes we were still encouraged to have.
• 29:37
  Speaker 0: the conversation on equity and inclusion is really sort of refreshing and reassuring to have because I know a lot of companies, after i had my presentation at few years.
• 29:55
  Speaker 0: A lot of individuals from different companies including big pharma came up to me.
• 29:59
  Speaker 0: we're like what did you know this company's actually?
• 30:02
  Speaker 0: they've removed their DEI policy internally now or do you that?
• 30:07
  Speaker 0: We've stopped the process as well.
• 30:10
  Speaker 0: so and we support this, was definitely very reassuring for me.
• 30:22
  Speaker 0: I felt much more confident going forward with the presentation knowing that although this is all my opinion speaking for a bit of it by any means It's just very reassured to know there were colleagues had same attitudes as moving forward.
• 30:39
  Speaker 1: Yeah must be nice to feel backed up in the sense again about accuracy data.
• 30:45
  Speaker 1: more than anything else, that's what we're proud of doing well and supporting across the streets.
• 30:51
  Speaker 1: So having that encouragement just affirms to not shy away from a conversation could jeopardise that accuracy?
• 31:01
  Speaker 0: Definitely I think it is always having that encouragement off.
• 31:04
  Speaker 0: do the right thing.
• 31:05
  Speaker 0: you can do easy things maybe not talk about it or fly under the radar but as i said this was sort a project of mine that I'm very passionate about and in my principles, i wanted to talk about it.
• 31:21
  Speaker 0: I wanted to have that discussion and to know that a very much supports you.
• 31:27
  Speaker 0: doing the right thing was definitely reassuring to say the least.
• 31:32
  Speaker 0: yeah
• 31:33
  Speaker 1: how reassuring?
• 31:34
  Speaker 1: Was It To Then Win Best In Stream Two?
• 31:38
  Speaker 0: Honestly um...I was utterly surprised even the feedback that I got from them.
• 31:45
  Speaker 0: Because it could be perceived as controversial and uncomfortable, so I went in very much aware of this.
• 31:53
  Speaker 0: And I was cautious about how I communicated with my husband before I submitted a presentation to him on which he took all and put everything into co-pilot like paper or presentation.
• 32:11
  Speaker 0: you know, I potentially have an audience of seventy percent white men in the room.
• 32:17
  Speaker 0: How does this come across?
• 32:18
  Speaker 0: Because i'm very much where...I don't want to point fingers!
• 32:22
  Speaker 0: I do not want to exclude
• 32:22
  Speaker 0: anyone!!
• 32:24
  Speaker 0: I want everyone to be part.
• 32:37
  Speaker 0: told me where, like maybe don't say this or maybe we don't see that.
• 32:43
  Speaker 0: And yeah the whole way through there was a prep for it working with TSHG and they were always really encouraging in terms of you know Don't be afraid to sort of ruffle feathers is kind of thing.
• 32:57
  Speaker 0: have those comforts happen.
• 32:58
  Speaker 0: It's okay.
• 32:59
  Speaker 0: make people feel uncomfortable because your saying something potentially is uncomfortable.
• 33:04
  Speaker 0: so That was a bit nerve-wracking, but also fun as well at the same time.
• 33:11
  Speaker 1: Yeah pushing the boundary a little bit that's great I think i noticed looking through all of materials and even speaking to you when we prepped for this podcast episode as well that You have taken a lot of time to consider how you communicate these things And particularly focusing on the positives.
• 33:30
  Speaker 1: so it doesn't feel like so far to go with this and making sure that all of the improvements are credited, celebrated.
• 33:42
  Speaker 1: So we don't lose sight of those achievements from me.
• 33:48
  Speaker 1: Kudos you have the right attitude and yeah you completed a great job at it.
• 33:54
  Speaker 1: was suitable for audience uncomfortable enough but really impactful as well.
• 34:00
  Speaker 1: Yeah, well done.
• 34:01
  Speaker 1: I'm not surprised that
• 34:02
  Speaker 0: you won!
• 34:03
  Speaker 0: Thank you...I
• 34:04
  Speaker 1: had nothing to do with the win but yeah i was very happy to hear it.
• 34:09
  Speaker 1: and um that was the result.
• 34:13
  Speaker 1: okay yeah go ahead.
• 34:14
  Speaker 1: No no
• 34:15
  Speaker 0: just- I was going to say that it was really rewarding and I think for winning.
• 34:23
  Speaker 0: it kind of made me realise this is something all of us together were all all involved together and we can move forward as well.
• 34:31
  Speaker 0: This is not just about one race or sex, it's that kind of moving forwards... We're stronger together!
• 34:43
  Speaker 0: I was the very last presentation on this day because I had a bit anxiety for the whole conference but then to win I was beyond chuffed to say the least.
• 35:00
  Speaker 1: Yeah, good thank you so much for raising my awareness.
• 35:04
  Speaker 1: we all need to do our bit like you said.
• 35:06
  Speaker 1: So as we start come to end of time today while will probably talk about this for forever just you and me what are those one-to two next best steps that would love industry take in a year?
• 35:23
  Speaker 1: or You can wave a magic wand, what would you like to see happen?
• 35:29
  Speaker 0: I think that industry right now is going through technologically speaking quite dramatic change.
• 35:37
  Speaker 0: We have automation we have open source languages with AI and when I sat at Fuse for those three days come across some of the most interesting innovative tools and development processes, it is really inspiring to be in that environment for those three or four days.
• 36:02
  Speaker 0: The thing that's so important.
• 36:06
  Speaker 0: we're doing all this amazing stuff but DEI has been embedded at every stage with its trial design recruitment data analysis leadership And it can't be just considered a checkbox.
• 36:21
  Speaker 0: It's the foundation of good science, basically and sometimes as I was sort of watching all this stuff that can make you think if your have got an automation tool that can produce data sets in two days?
• 36:36
  Speaker 0: That is fantastic!
• 36:38
  Speaker 0: But who do you recruited into your study?
• 36:41
  Speaker 0: If you've got all these open source languages so that you can program in SAS.
• 36:48
  Speaker 0: that is amazing but whose data are you analysing?
• 36:53
  Speaker 0: and so if the trials don't reflect the populations we serve, they will just keep widening in the gaps instead of bridging them.
• 37:02
  Speaker 0: It's not going to be easy moving forward.
• 37:03
  Speaker 0: like technology advances so quick.
• 37:06
  Speaker 0: it's exciting something people want to be part.
• 37:10
  Speaker 0: It is just as important.
• 37:18
  Speaker 0: And I think also it requires courage and collaboration because we can't do that by ourselves, you need everyone to want to do it.
• 37:30
  Speaker 0: Also the commitment of making a change so when things get difficult they don't sort back down or keep going forward.
• 37:42
  Speaker 0: The next best step carry on with the momentum of the exciting clinical trial.
• 37:49
  Speaker 0: If you can report a clinical trial in two days, that's fantastic!
• 37:53
  Speaker 0: Who have you got?
• 37:54
  Speaker 0: Let us talk about data visualisation and look at different types of races or genders including recruitment for your study.
• 38:04
  Speaker 0: Do we have males, females or transgender?
• 38:08
  Speaker 0: It is all about opening up those opportunities to everyone.
• 38:15
  Speaker 0: That is where we need to go.
• 38:17
  Speaker 0: We need to keep progressing, the FDA removing the diversity plan was a step back and that was really disappointing.
• 38:25
  Speaker 0: but we should still be stepping forward.
• 38:28
  Speaker 0: Political parties don't last forever!
• 38:31
  Speaker 0: We all know about it.
• 38:32
  Speaker 0: so let's just keep stepping forward and let us not stop at momentum or have those conversations because I think its important no matter how uncomfortable.
• 38:44
  Speaker 1: This also strikes me quite interesting as well, how we can use more technology now to save even more time.
• 38:51
  Speaker 1: And actually the question here really is where do you replace that time?
• 38:56
  Speaker 1: So the times saved... Where else are you putting it?
• 38:59
  Speaker 1: You've just beautifully highlighted a few areas where maybe we can minimize that gap instead of broadening in it by putting that time back into the selection process and making sure they're right people, not right demographic are involved because other things may be a bit smoother or faster
• 39:17
  Speaker 0: to do.
• 39:19
  Speaker 1: Because we have the
• 39:19
  Speaker 0: tech.
• 39:22
  Speaker 0: The whole point of clinical trials is if there's people involved in them.
• 39:27
  Speaker 0: so we should put
• 39:28
  Speaker 1: our time
• 39:29
  Speaker 0: into those people make sure it's as best possible for people who get the chance at effective treatments?
• 39:36
  Speaker 1: Yeah Wonderful.
• 39:38
  Speaker 1: Speaking of people, if you take a few moments now to think about speaking directly to trial participants especially those from communities like we've mentioned where they're historically underrepresented or been mistreated in the past what key message would you like to share with them?
• 39:57
  Speaker 0: I thank two individuals.
• 40:00
  Speaker 0: it's more to say than i'm listening.
• 40:05
  Speaker 0: What are your fears what are your concerns, worries?
• 40:09
  Speaker 0: What don't you understand and do want to know.
• 40:13
  Speaker 0: If I am not listening to them then they cannot help me.
• 40:17
  Speaker 0: That is the only way we can move forward—I can go in and tell all of those things but that will not alleviate their fears because they need to feel seen or heard.
• 40:31
  Speaker 0: so therefore they feel represented.
• 40:33
  Speaker 0: I want to do, let people know that.
• 40:37
  Speaker 0: I'm listening and... That together not me Not just them it's a collaboration.
• 40:45
  Speaker 0: Together we can move forward because they deserve the opportunity They deserve to have medicine that works for them.
• 40:57
  Speaker 0: They deserve feel safe.
• 40:58
  Speaker 0: More than anything they deserve to
• 41:01
  Speaker 1: be healthy.
• 41:02
  Speaker 0: Yeah
• 41:05
  Speaker 1: Absolutely Thank you, Roxanne.
• 41:07
  Speaker 1: It's so important isn't it?
• 41:09
  Speaker 1: You can tell someone else is learning and understanding what they need to know.
• 41:17
  Speaker 1: So yeah...
• 41:19
  Speaker 0: I might not know other people cultures or their histories but i could listen in there from that And then once I have the understanding I will help them move forward with something better for themselves.
• 41:35
  Speaker 0: I can do that by myself.
• 41:36
  Speaker 0: I need to work with them, because they're into doing it.
• 41:39
  Speaker 1: Yeah absolutely and Rhys Brockson what would you like to share or learn more from everyone else in the industry?
• 41:50
  Speaker 1: That's involved with trials Or share with their group To ensure we keep that DE&I at top of our list And not a tick box.
• 41:59
  Speaker 1: exercise
• 42:02
  Speaker 0: One is one of most important aspects for clinical research and science in medicine.
• 42:12
  Speaker 0: A lot of times we hear the discussion that prevention is better than a cure, I think there are so many communities out there who are underrepresented but do not have access to health care.
• 42:28
  Speaker 0: by some point it's too late for their diagnosis with different conditions.
• 42:33
  Speaker 0: Early diagnosis if they can find a way through different means and manners is so critical for clinical research.
• 42:41
  Speaker 0: The sooner you can diagnose someone, the better chance they also have as well for successful treatment.
• 42:47
  Speaker 0: And there's... As we sort of spoke earlier about tools in technology There are so many interesting innovative studies that aren't happening right now For early diagnosis.
• 42:56
  Speaker 0: it was a really good one Last year.
• 42:59
  Speaker 0: That was led out of Imperial College London.
• 43:04
  Speaker 0: It was called Clocks.
• 43:05
  Speaker 0: It was based in the UK and it is a cancer loyalty card study.
• 43:11
  Speaker 0: We had about four hundred women who were diagnosed with a variant of cancer, three-hundred women would never have been diagnosed but they got access to their loyalty card records from Boots which is an UK health & beauty retailer.
• 43:28
  Speaker 0: for those that don't know what Boots is And what they discovered through looking at their club card and their loyalty card data was that these women were self-diagnosed, self treating pain.
• 43:43
  Speaker 0: And nausea for about eight months prior to seeking medical care.
• 43:51
  Speaker 0: from when the first attended a GP visit.
• 43:53
  Speaker 0: it was roughly three and half months before there are diagnosed with a lady in cancer being an incredibly aggressive female cancer.
• 44:03
  Speaker 0: but it's showing that the project sort of was looking at real-world behavioural data to help identify symptoms and patterns, how you can use them by looking at vague early symptoms.
• 44:16
  Speaker 0: But obviously in venues because if your going into a shop on buying gastrointestinal medication or pain medication due as an individual won't realise the pattern?
• 44:26
  Speaker 0: If actually look at it from actual scale then see and identify patterns.
• 44:32
  Speaker 0: And they're using these processes to also now try and detect pancreatic cancer, colon cancer.
• 44:40
  Speaker 0: Stomach cancers act as where your symptoms are maybe so early and so vague that a GP wouldn't necessarily be able to identify it.
• 44:49
  Speaker 0: but by just this behaviour of using your cards—your loyalty cards you can actually help give diagnosis and therefore early detection, better healthcare.
• 45:05
  Speaker 0: I really liked that it was such a beautiful inclusive data strategy to help with public engagement as well again.
• 45:16
  Speaker 0: With it being female cancer or variant cancer some women uncomfortable going to GP but encouraging conversation of early diagnosis treatment results.
• 45:30
  Speaker 0: they're using these strategies, not just for variant cancer but towards other cancers as well.
• 45:37
  Speaker 0: It's really innovative and also not invasive because it is something you are doing every single day without even realising that?
• 45:45
  Speaker 1: Yeah!
• 45:45
  Speaker 1: That a good use of selling data on essentially... there's a lot of people that are nervous about what data is being used about them but if it could help you
• 45:57
  Speaker 0: absolutely actually
• 45:58
  Speaker 1: find out that you feel cancer sooner rather than having those awkward GP appointments or at being, I think he said always the year right?
• 46:05
  Speaker 1: Of self-medicating then having the GP appointment has taken three more months.
• 46:10
  Speaker 1: A year is too long yeah
• 46:13
  Speaker 0: for that kind of diagnosis can be the difference between life and death.
• 46:16
  Speaker 0: unfortunately apprehensive about sharing their data and absolutely, like you know that is your data but it's nice again to see it being used in such a positive and inspiring way.
• 46:33
  Speaker 1: Yeah absolutely really yes.
• 46:37
  Speaker 1: thank you so much Rupsan.
• 46:39
  Speaker 1: we are going too.
• 46:41
  Speaker 1: Thank You So Much for joining us.
• 46:43
  Speaker 1: And um thank you Again all the hard work you put into Your presentation For raising That awareness for continuing to do so today as well and doing it with such positivity, an encouragement.
• 46:55
  Speaker 1: To include people in this discussion and the work that we'll continue to do in the future as well.
• 47:01
  Speaker 1: no finger-pointing has you say?
• 47:03
  Speaker 1: It's all about working together for the better truly is a clear and uplifting message who thank you for sharing there.
• 47:10
  Speaker 1: um...and its very timely.
• 47:12
  Speaker 1: these uncertain times were experiencing us also.
• 47:15
  Speaker 1: Thank You!
• 47:16
  Speaker 1: As We Come to A Close We like to ask our guests two very important questions.
• 47:22
  Speaker 1: And as you may know, we're very much in love with all of our pets and animals at their events.
• 47:28
  Speaker 1: so start with...we need
• 47:47
  Speaker 0: the chance of me.
• 47:48
  Speaker 0: getting a cat or dog probably isn't going to happen, unfortunately.
• 47:52
  Speaker 0: But my brother does have a tortoise which I like to go over and see quite a lot.
• 47:56
  Speaker 0: so yes... My son gets to go there and see Herbert the Tortoise instead of a cat-or-dog.
• 48:04
  Speaker 1: Herb it's great name for a turtle!
• 48:07
  Speaker 1: So actually it sounds that you're more team husband than in this case but good to know you can live vicariously for all the other cat lovers that we have at The Business.
• 48:18
  Speaker 0: I want see all of their pictures and always get very excited by them!
• 48:21
  Speaker 1: Yeah me too, me too...I had this space and no one else in the house to infect with an animal.
• 48:29
  Speaker 1: um But i love travel a bit too much And would just feel very very sad leaving then behind.
• 48:33
  Speaker 1: so now is not the right time To Have A Dog Or
• 48:37
  Speaker 0: A Cat But..
• 48:38
  Speaker 1: I Would Love Both or Either Or A Tortoise Be Great Too.
• 48:42
  Speaker 0: I do say to my husband if a hand married him, he probably would have about five cats by now.
• 48:47
  Speaker 0: So maybe it's the best that i didn't see them.
• 48:51
  Speaker 1: Okay yeah.
• 48:56
  Speaker 1: and then um If you were to have dinner with three people dead or alive who would you choose on?
• 49:04
  Speaker 1: why?
• 49:05
  Speaker 0: You told me this question ahead of us And said don't overthink it.
• 49:10
  Speaker 0: Oh, it's the staff that we were in last night trying to think.
• 49:16
  Speaker 0: So if I could have this one person i would be happy and that one person would be Tony Robbins?
• 49:25
  Speaker 0: I don't know who you know how Tony Robins is.
• 49:29
  Speaker 0: for those of us who do not know as an American speaker and businessman he doesn't refer himself And I genuinely think he would be absolutely incredible just to sit and listen to him.
• 50:07
  Speaker 0: I feel like i would come out as a whole transformed person.
• 50:14
  Speaker 0: I just think he's so interesting and inspiring, yeah?
• 50:21
  Speaker 0: He'd be number one on my list to have dinner with me!
• 50:27
  Speaker 0: I also want to have Sir David Attenborough because it'll be very interesting for him.
• 50:36
  Speaker 0: It's so fascinating to learn from him.
• 50:40
  Speaker 0: And then the third person I would have, it'd be the late Robin Williams as a very nostalgic childhood in love for him and he was absolutely hilarious at having a dinner party.
• 50:56
  Speaker 0: Tony Sir David and Robin.
• 51:00
  Speaker 1: Together you could fix the world!
• 51:02
  Speaker 0: Do we have like thirty minutes yet?
• 51:07
  Speaker 1: the unstoppable, what a combination.
• 51:10
  Speaker 1: Yeah but you're really great.
• 51:11
  Speaker 1: dinner party Roxanne it really would-
• 51:13
  Speaker 0: You can come along Zoe!
• 51:13
  Speaker 0: I'll do that again
• 51:15
  Speaker 1: in back, okay cool?
• 51:17
  Speaker 1: That'd be great.
• 51:18
  Speaker 1: no that's fantastic.
• 51:19
  Speaker 1: thank you so much for spending your time with me today.
• 51:24
  Speaker 1: um i think sorry sharing all of your wisdom and from referencing all of the studies that you have as well we'll make sure all of those are in the notes.
• 51:31
  Speaker 1: so people And until next time, thank you so much for joining us and take care.
• 51:39
  Speaker 0: Thank you very much!
• 51:40
  Speaker 0: It's been an absolute pleasure to speak with you... ...and I hope the positivity in this conversation resonates with so many people.
• 51:48
  Speaker 1: Me too…I think it will.
• 51:50
  Speaker 1: Pretty certain that we'll be going for Tony's job next.
• 51:57
  Speaker 1: All right thanks everyone bye-bye.