Are you ready to dive into the future of statistical work in drug development?
Are large language models like ChatGPT the future of data analysis?
How does the increasing trend towards transparency and open-source programming influence the pharmaceutical industry?

In this episode, Benjamin Piske and I explore the dynamic landscape of trends shaping the statistical field. As we reconvene after a significant hiatus, we delve into intriguing topics that will undoubtedly get the interest of anyone involved in statistical analysis for pharmaceuticals.

Join the conversation as we discuss the implications of these trends and more, offering insights that will challenge your perspective on the evolving nature of statistical work.

We talk about these 6 trends:

  • Trend 1: The Rise of Large Language Models
  • Trend 2: Transparency in Data and Privacy Concerns
  • Trend 3: Virtual and Augmented Reality in Work Environments
  • Trend 4: Collaboration through Specialized Marketplaces
  • Trend 5: Open Source Programming and Collaboration
  • Trend 6: Payer Involvement in Drug Development

In this thought-provoking episode, Benjamin and I provide valuable insights into the dynamic trends shaping the statistical landscape. From AI and data transparency to virtual reality and payer involvement, statisticians are navigating a rapidly evolving terrain. As the industry adapts to these trends, staying informed and embracing new approaches becomes paramount for effective statistical work in drug development. Tune in and stay ahead of the curve! Share this with your friends and colleagues that can benefit from this!

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Transcript

Trends That Will Have an Increasing Impact on Our Work

 [00:00:00] Alexander: Welcome to another episode of the effective statistician and after quite some time. This is with Benjamin again. Hi Benjamin. How are you doing?

[00:00:10] Benjamin: Good. Thanks Alex. Yeah, it’s been amazingly long, right? And actually we are, we’re hitting a very special day today. Isn’t it your birthday?

[00:00:19] Alexander: Yes, yes.

[00:00:20] Benjamin: Congratulations. I’m not sure, like, you know, I mean, we haven’t met for 50 years, but it’s been, you know, congratulations to a very round and, you know, half century birthday for you.

[00:00:31] Alexander: Yeah. Thanks. Thanks.

[00:00:32] Benjamin: All the best for, next 50 years.

[00:00:35] Alexander: Exactly because of this, I thought about you know, a topic that is a little bit looking into the future and looking backwards and looking into trends and of what’s happening. But just to give you a little bit also some background on why Benjamin hasn’t been on the show for so long. Because he was [00:01:00] renovating an old house and moving into it and well, that comes with a lot of logistics, a lot of work and a lot of, yeah, following up with people.

[00:01:12] Benjamin: Yes. And it’s also like looking at the future because it’s, it’s not nearly finished. Right. So I hope I don’t spend the next two and a half years as we did with the, you know, until getting here, with the same type of work. So, yes, it’s so, you know, I had my, my second job was rebuilding a house, or organizing it.

[00:01:32] Alexander: so I have a couple of trends that I think will have quite some impact on our day to day work was in development of new drugs and from a statistics point of view, and these, yeah. Well, just some kind of more or less random things, of course, there’s lots of lots of other things going around as well but here I have some kind of [00:02:00] case studies and I see more and more kind of direction in terms of that. And of course, the first one is large language models to what kind of everybody is talking about AI with chat GPT and all these other things.

[00:02:20] I think that’s definitely will have an impact. I’ve just seen announcements at Claire and chat from PSI, I have the next lunch and learn also about this topic and how it will impact our workplace, how it is impacting our workplace already, and how it will kind of change the future of how we work.

[00:02:46] How are things in terms of, you know, using it, for example, also for programming and things like this, how have you seen any kind of developments in terms of that?

[00:02:55] Benjamin: Yeah, I don’t, I think professionally you know, I haven’t seen any [00:03:00] impact on, you know, on my day to day work. I mean, there’s, I mean, obviously I give it a try. Right. So writing an email and just, you know, using chat GTP and, and kind of getting like, you know, grouping information and nicely phrasing it, especially for me as a, you know, non native English speaker, it is helpful in many ways to get like the formulations and phrasing of, of words and, and so these kinds of things. So but nevertheless, I think the potential is gigantic, right? So there’s so much of you know, it’s so frightening and amazing at the same time, and how, you know, these algorithms or these support functions are actually usable already for the day to day life. Right. I mean, I just. See, you know, kids writing texts for school , or not writing texts, but, you know, getting the text written for school.

[00:03:55] And, and also I’ve seen examples. It’s [00:04:00] also not in, you know, more in the, in the private environment is in using programming languages and translating from one language to another, which, so I was told was working. Accidentally. So it was really amazing what frame of programming language was created by chatGTP in this case, from, you know, either giving instructions of what needs to be done or using one language and translate it into another language. So that is amazing. But again, I’m not sure yet where we get there professionally.

[00:04:38] Alexander: So I have seen, for example around data visualization. Yeah, so that can help quite a lot if you want to improve data visualizations said you can use, you know, AI to help with the programming of these kinds of different things. Yeah. So I’m pretty sure that will have an impact.

[00:04:58] Benjamin: I believe, I mean, I [00:05:00] just remember how, you know, how difficult it was to find, you know, do nice visualization or, you know, graphical environments in SAS. So giving examples and just, you know, making it nicer by, by just. Talking to ChatGPT is, will be probably extremely helpful.

[00:05:15] Alexander: Yeah, I think the other area where it will definitely have an impact is analyzing unstructured data. If you just think about clinical literature reviews, systematic literature reviews, all these kinds of different things, I think that will definitely have an impact. I’ve already seen companies using it to, for example, evaluate new indications.

[00:05:49] For existing compounds or existing drugs, existing, you know therapies, gene therapies whatsoever. Yeah. So [00:06:00] looking into what is in the literature available around all these kinds of different things and then synthesizing it into a report that gives you also also references in terms of. Which studies, which publications and so on help you to determine, okay, these are all the potential other indications you can look into. Yeah. And I think that is really, really interesting.

[00:06:31] Benjamin: It is probably absolutely, you know, absolutely helpful. I mean, it would save time and, just the, you know, the structure and finding it my, I’m wondering how reliable the information is. Or how bulletproof it is, let’s say, because I know that, you know, there, there have been examples and, you know, how you feed chat GPT with some information, which was right or wrong.

[00:06:55] And at the end, the same information is being spread to other people asking for the same. So, [00:07:00] you know, you can feed actually. Incorrect information into ChatGPT easily. And also that, that references are made to, you know, sound absolutely right, but non existing papers.

[00:07:13] Alexander: And so I think there is there’s the chat GPTs, and then there’s also the models that are trained within certain companies.

[00:07:23] Benjamin: Yeah, that is. And that is my question. What is kind of the, I mean, that will actually mean that. This is something that companies need to invest a lot in, in order to get it out. I mean, also for, you know, for privacy reasons, right? So if you, you know, if you put in information and kind of trying to find a strategy and how to move forward with you, you know, so that you know, there’s some, some sensibility on the data.

[00:07:50] Alexander: And that is privacy is actually a very, very interesting topic because that clashes with [00:08:00] yet another trends that I see and that is transparency. I think the, we have already started with clinicaltrials.gov and, and these kind of things. There’s a lot of move towards more transparency and I’m just thinking about one specific case that is the the, the trends that potentially we will have raw data being submitted.

[00:08:24] Patient level data being submitted to the EU and based on the EU regulations, lots of this data will become public. Yeah. They said basically, you know, patient listings are already in, in a sense, public. And it’s just a, just a different format. Yeah. So, I think that will, there will be major shifts about this.

[00:08:51] I was recently at a EFSPI regulatory workshop in Basel, where I so some presentations [00:09:00] and discussions about this, and I think this will have a tremendous effect on the overall industry. If there’s more transparency in terms of clinical trial data.

[00:09:12] Benjamin: Yeah, but that is, I mean, collecting data and having data and then making it transparent. That is something that I can, that is easily. Well, it’s for me, I mean, I can understand how this is functioning and what benefit it has, and also what restrictions we could actually apply. So I think from where I see more, I wouldn’t say danger, but more challenges is not only the, the privacy of it.

[00:09:42] Data of, you know, personal data or patient data or what type of data, but what, what I’m seeing more is that then the, the trends, I mean, you were describing something where you find you know, where you see trying to gather information of a different, either, you know, [00:10:00] indications or treatments or, and, and fine.

[00:10:03] So that is actually. Creating companies are having a strategy or planning for a strategy. So, and if you have competitors on the market and you use publicly available chat, GTPs, let’s say to figure out your own trend or to find your own strategy. That is actually information that will be very beneficial for your competitors.

[00:10:30] So I’m, I’m more talking about not the privacy of personal data or patient data, but more about the, the sharing and the spreading of information that you feed into systems that are publicly available. Yeah. I think there’s, there’s a big risk. And that’s why I think it’s, it’s a good idea for big companies to actually create their own chat.

[00:10:50] Like. Tools and, and have it. But on the other hand, this is restricted to big companies because small companies can’t afford it.

[00:10:58] Alexander: Yep. All [00:11:00] I don’t know whether they’ll, you know, will be services made available by small companies that say, Hey, you can have, you know, we host your large language model here and you, you know, can just, you know, purchase a license to it and we ensure that, you know, all your models.

[00:11:21] Data stays within your area. Yeah. So that is definitely will have a lot of impact overall on our work. And yeah, that’s just amazing.

[00:11:34] Benjamin: But that is actually independent of us. You know, of farmer industry. So it is,

[00:11:39] Alexander: it’s beyond the farmer. There’s another thing that also is a trend that is beyond the farmer industry and that is virtual and augmented reality.

[00:11:51] A couple of years ago, I was already kind of talking about, wouldn’t it be nice to have, you know virtual screens that, you [00:12:00] know, you can see much more kind of data and you can interact with more kind of different things. And at the time it was possible, but really, really expensive. anD there were lots of kind of initial problems with it.

[00:12:16] And I think. From that trend has definitely evolved more with, you know, meta having these different virtual reality things that you use for gaming and all kinds of different things. And there is now more and more applications coming for work environments so that you have, can have. You’re not restricted to just your physical screen that you have on your desk, but you can have many, many more interactions there.

[00:12:48] And I think that will become really interesting for working virtually together. But also for example, interacting with data. You know, data visualizations, data [00:13:00] displays all these kinds of different things.

[00:13:03] Benjamin: Yeah, I believe you’re right. I’m not sure. I hope you’re right. But I think the speed that I was expecting this to come is much slower.

[00:13:12] So from just thinking back, I don’t know when it was like the metaverse announced and the big hype assumed to be starting with five years, maybe six years. I don’t know. So it’s, it’s a while ago. And since then it is, well, it’s, there’s nothing. I mean, Apple brought up some other, you know, ways of. You know, virtual reality and I, you know, I haven’t really followed the trend, but to me it didn’t come through yet.

[00:13:43] Alexander: I think there’s lots of small iterations. But prices for virtual reality classes have fallen quite a lot. Yeah. By the way, I just got one for my birthday presents. And I’ve seen already kind of [00:14:00] applications where where people basically sit in the, you know, the living room and kind of have all the different things.

[00:14:09] Benjamin: Yeah, I think what you mentioned about the data presentation of deep dive into data and looking at the interactive, et cetera. So I think there’s some potential indeed.

[00:14:18] So where, where you say, you know, sitting in your chair, armchair, and then just, you know, you know, walking through the data. So I think, no, I mean, there’s probably really potential, but I think. Until we get there we first have to create this in terms of the data. So the availability of data in that format on the, in the way how to purchase.

[00:14:42] And I think most of the companies are still struggling in organizing and doing this in. 2d data. So, so the visualization of visualization is still like a big hassle, even on a screen on a single screen. And putting this in virtual reality [00:15:00] and maybe, you know, in gestures and, handing data.

[00:15:03] So that will be probably quite convenience, but I just now imagine like, you know, like a gathering of people waiting for the results and those sitting with virtual reality, 3d glasses in a meeting room in a company and, you know, walking their fingers through the air and just get stress. So it’s kind of an interesting It’s an interesting imagination, but I think the potential is there not only for gaming, but really for using this professionally.

[00:15:34] I haven’t seen anything for me. It’s just imagination at the moment. I haven’t seen any, any of these, nor do I have glasses. I mean, I’m not yet 50. So maybe it’s.

[00:15:44] Alexander: Not yet. Yes. There’s one other thing that I see is more in terms of the contracting overall. Yeah, I think the I’ve seen now [00:16:00] a couple of marketplaces that are specialized for clinical development and pharmaceutical area.

[00:16:09] Yeah. And they have a business model to help big companies work more easily with small companies. Which is an interesting trend, because you have, of course, on one side, you have lots of, you know, big pharma companies that need a lot of volume and work to get done. And on the other side, you have lots of small specialist companies.

[00:16:39] I see it, especially also in the stats area, you know there’s so many freelancers, so many, you know, small companies that have maybe, you know, five people, 20 people, 30 people, 40 people, you know, which don’t have the critical mass that [00:17:00] one of the big players on the farmer side says, yeah, they have enough volume.

[00:17:04] So it makes sense to, to organize a contract with them. But these marketplaces basically create master service agreements and all these kind of different things so that the big companies can easily work with the small vendors. And I’ve seen now a couple of these emerging. And I think this is, this is an interesting trend that I haven’t seen before so much, you know.

[00:17:34] And will be interesting how that pans out, you know, whether that makes, it’s just yet a completely different alternative to the way of working, you know. Because there’s also a lot of regulations that permits this kind of. Also things that, that people kind of fire companies fire the people and [00:18:00] then rehire them through a third party just to kind of save costs. I think there’s, there’s some potential there as well.

[00:18:08] Benjamin: Yeah. I don’t, I haven’t seen it personally, but I know it existed already for quite a while for individuals. So that, that freelancer. Basically open their laptop in the morning, the Bahamas or anywhere they currently are, and have an assignment, kind of a job to do so not necessarily work the whole life or year or month with one task and company, but have through like a distribution or maybe these kind of companies that are between the ask and the, you know, and the gift and have assignments in the, you know, changing or on an hourly or daily or whatever basis. So I don’t, I don’t know exactly what. Type of [00:19:00] companies or type of freelance that this was, I believe it’s more on the marketing side.

[00:19:04] So, and so where they have been assignments, which are smaller, not like for what we usually have, like full study life or in compounds cycle of developing. And so, which is more about years or even decades, depending on.

[00:19:23] Alexander: Yeah, I’ve seen that also kind of for, especially on the high end side, you know, people that are very, very experienced and who choose to not work for one of the, you know, big pharma companies or the big zeros that say, Hey, I can, you know so me.

[00:19:45] Expertise more kind of individually and more granularity, you know, and say, hey, you want to have a discussion about your safety strategy and you can book, I don’t know, 30 hours with me and because I’m one [00:20:00] of the experts on safety statistics, you know and so you can have this kind of work with me and that’s kind of send through this overall master service agreement. Very, very easy to do. Yeah.

[00:20:13] Benjamin: I think it is something beneficial. I would say it’s not applicable for all people, obviously, definitely not for first of all flexibility. The uncertainty is kind of You know, that people may not like, I mean, may not you know, value. I mean, certainly I may not, you know, live with.

[00:20:33] And also what I think is that, you know, sometimes people do need to invest more into, I kind of identify themselves with. They’re what they’re doing, which is fine. Sometimes that you have a short period of of involvement in certain things, but then it should be maybe always the same company [00:21:00] that you either work for or work with so that, that your kind of identify.

[00:21:05] Not only that, oh, that’s my task. And then, you know, after 30 hours, I’m going home or I’m just finishing it. And then I’m off and I don’t care, but it’s more about the identification with the, with the road. But yes, I think it’s a, it is a trend and it’s also, especially with the. With the cost savings that are, you know, and, and slimming down the, the whole structure and infrastructure depart HR supportive departments, et cetera.

[00:21:33] So that is probably trend that might, I don’t know, I, you know, I haven’t, I don’t have any experience there, but I think this is I can imagine it has a future.

[00:21:44] Alexander: Yeah. So, and I completely agree. It will not be applicable to everybody. Yeah. I think it’s just another way of working now and for, it gives an edge to small companies to [00:22:00] better compete with, with the big ones for these big clients.

[00:22:04] Another of pretty clear kind of trend is everything about open source programming. Oh, yeah. Well, I think that’s not a new trend. That’s not a new trend. It’s just kind of accelerating more and more and more and more companies are going into this. I recently even talked to someone from SAS who mentioned, Hey, by the way, you can also, you know, Use are within the environment and says interfaces for that and says validated our library was in sauce and all these kinds of different things. So even SAS has kind of seen that. Well, they can’t kind of just. Do without it anymore.

[00:22:43] Benjamin: Yeah. You know, it’s again I’m not, you know, I’m not programming anymore. Unfortunately, in some way I do miss this was really like one of the, my deep work experiences in programming, but the. What I see there is that it’s absolutely true because [00:23:00] the variety and the variability and the the offer that you have on the open source market is the wrong word, but it’s kind of, you know, the, the platforms, so whatever’s available, that’s gigantic.

[00:23:13] So it’s really nice because everyone is implementing it. They’re using it and reuse it. The downside, especially in our industry is that it is open source. Right. Meaning that more or less everyone has access and you, you know, if you, and things are evolving and changing and whatever you validate and whatever you use may be outdated.

[00:23:34] And there’s, there’s, depending on what you’re using. I mean, there are also. You know, offers or, or packages that, that are validated or that are controlled. But that again, it’s then a little bit trending away from the open source type of thing, even though it is open source, it is not, has, doesn’t have the flexibility and the, and the authorship.

[00:23:59] I mean, the, [00:24:00] the input you get from, from the different, it’s from the different you know, programmers. That are actually improving, adding parts to, to open source software. So there’s, it always sounds very good, more like a buzzword now saying open source programming, because if it’s open source, it’s not usable for us.

[00:24:22] If it’s not open source, or if it’s useful for us, it may be, the source may be open source, but at the end, it’s a little bit more restricted.

[00:24:31] Alexander: Yes, I think it comes together with more and more collaboration. Yes, I think that’s, that’s a piece and there’s the. Big, there’s a lot of big pharma companies, and especially, of course, Roche, we talked about this quite a lot but many others like Acer, GSK invest a lot in this area, and there’s more and more kind of platforms for collaboration, for, automation, standardization, [00:25:00] so I think if you are mostly working with kind of creating standard tables a predictor job will be, will be get done. By using open source and a lot of more automation in the future.

[00:25:17] Benjamin: Also SITEL is now involved there. So they’re, they’re cooperating with other, you know, pharma companies on this. So this is, it is, it is right. But at the end you know, then, then we need to kind of define exactly what the open source means, because if you, yeah, packages and cooperation.

[00:25:34] It is not open source anymore. And the, in the classical sense, it is then on a value. So that’s why I’m, I think what really is and what the future is, because this, this is now a trend for the last 10 really like an No, it’s not a complete, it’s not, it’s not a new trend, but I think what the benefit is, and we’ll, we don’t know, I mean, we are talking R at the moment primarily, but who knows.

[00:25:58] Right. Let’s [00:26:00] gather again in five years and let’s see what a Python or anything else is the trend now. But I think what the benefit is and why, why this is changing. And since you mentioned SAS is that the flexibility in, and the creativity that we see. In the programs and in the development of the, of the, of the language and the programs is setting the directions.

[00:26:26] So the, industry is following open source. So, and I think that is, that is the thrilling piece of it because there, it’s not that we develop something or, or SaaS is developing and then together in cooperation with what, what is needed. No, you know, the, the, the trend is that it’s out there already and somebody detects it and use it and thinks, Oh, it’s a good idea.

[00:26:49] So, and so I think the, the, the variability and the flexibility is increasing and we need, just need to kind of fence it into, you know, our environment or a [00:27:00] regulated environment more or less. Yeah.

[00:27:02] Alexander: Yeah. So definitely this new trend creates completely new questions. Yeah. Absolutely. Absolutely. The last trend I want to speak about is the increase in terms of payer involvement.

[00:27:17] And, the importance of payer, and of course that is also not a new trend. Yeah. So, the power of payers, of insurance companies, of national policy makers have definitely increased over, over the years. Now with the new EuHTA. Regulations coming into play in start of 2025 for the oncology area this will have a huge impact overall on the industry and see if you haven’t, if you’re working in phase 2 and phase 3 and you think, well, I don’t need to know about this. [00:28:00]

[00:28:00] Sorry, you’re wrong. Because we will see a lot more parallel efforts going on both for the EU submission and the EU payer involvement, and that will definitely have an impact on how we work when, you know, how we work together, we will need, you know, we can’t just, you know, first, let’s take care of the regulatory submission.

[00:28:25] And once we have figured that out, we, we think about all the payout questions, you know, things need to go in parallel and. That will require organizations to have different procedures, to have different processes, to have potentially different capabilities. I’m just thinking in terms of indirect comparisons, network meta-analysis, these kind of different things.

[00:28:50] But it will definitely need to, speaks for better understanding of the overall process and more collaboration [00:29:00] across the different I think very often siloed functions. And it says it’s both, you know, the development people need to more embrace what’s happening on, on the other side and the HTA and marketing and sales people need to more embrace on what’s happening on the regulatory side. there will be definitely much more interactions in that regard.

[00:29:22] Benjamin: Yeah, I think that is that is a trend in general. Well, what we see is that the involvement, you know, that you moving away from the, you know, the silo with responsibilities. So you think, Oh, let’s develop this. And then, you know, then next phase on it.

[00:29:37] So we already started this in the developing of the phases, but actually with the peer involvement, I think there’s generally a trend of planning a drug. Not only until submission, but beyond it. So anything that’s, you know, that’s coming next and to already involve. I mean, in the past, or most of the times, [00:30:00] probably even today, it’s different groups, different departments that are working in on the different phases.

[00:30:07] And this itself is like a, it’s an, you know, it’s not a correct construction of the, of the, of the company, correct. But it’s at least there are downsides to it. What you just described is the involvement of, you know, the, the respective people appear in this case early on is important, but how do you manage this in, you know, if you have siloed worst case siloed groups.

[00:30:36] Alexander: I think this is the people that don’t or the companies that don’t embrace this trend. We’ll suffer from it. Yeah. If your clinical development organization is just, you know, measured based on time to regulatory approval and all these other regulatory timelines well, bad for you. Yeah. Because you [00:31:00] will get something on the market that nobody will be able to use. Yeah. Or there were pairs. And by the way, not just the European payers will say, Okay. No, we don’t pay for that and.

[00:31:11] Benjamin: There’s, I mean, it’s just, you know, it’s time consuming to actually correct this expensive, right?

[00:31:17] Alexander: It’s time consuming, expensive. And.

[00:31:19] Benjamin: Yeah, so at the end you, you manage, but whatever you save in the beginning by investing a lot, a lot more money and getting the regulatory approval. You know, you’ll spend double the money then just redoing everything in order to get the payers.

[00:31:33] Alexander: Imagine you run a big phase 3 studies that costs a couple of hundreds of millions of euros and then you see, well. You haven’t included certain variables like quality of life or whatever that the payers are interested in.

[00:31:51] Well, how do you get the data? Yeah, you can’t kind of travel back in time and ask patients, Oh, by the way, how was your quality [00:32:00] of life at baseline? Yeah. You messed up. Yeah. And this is nearly impossible to, to, to correct again. Yeah. So these kind of failures Will be really, really costly and damaging to organizations. And I think some organizations will just learn it’s the hard way. Yeah.

[00:32:22] Benjamin: Unfortunately, Well, I mean, this isn’t anything, I mean, again, it’s not a, trend for the future. It’s a trend that we’ve already seen that there and learned a lot. I mean, we, it’s always bits and bits because we you know, we learned at first of, you know, in, in starting phase one or even before and already thinking about phase three.

[00:32:43] Right. So that is, that is something that the, you know, the industry learned a while ago, but now it’s beyond that. It’s not only regulatory sufficient. It is.

[00:32:52] Alexander: Yep. So, and in summary for you. That means you can, of course, [00:33:00] ignore these. But as for companies, it’s not helpful to ignore these. I think it’s much more, good to at least embrace them, get to know about these, and potentially even build your career strategy on it.

[00:33:18] Yeah. See how you can lead certain curves here. Can you become an expert in this area? Can you? Spearhead, kind of raising awareness within your company around, around these things make you more kind of be seen, you know recently I had you on the podcast where we talked about within AZ and he has driven that forward quite a lot and benefited personally from spearheading this initiative.

[00:33:55] So have a look into this. How can you potentially [00:34:00] ride one of these waves and with that really benefit and have an impact on your career. Thanks so much, Benjamin. That was another awesome discussion. And I’m really looking forward for future ones. Yeah.

[00:34:16] Benjamin: My trend is more frequent episodes with you.

[00:34:21] Alexander: Okay. Bye. Bye.

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I work to achieve a future in which everyone can access the right evidence in the right format at the right time to make sound decisions.

When my kids are sick, I want to have good evidence to discuss with the physician about the different therapy choices.

When my mother is sick, I want her to understand the evidence and being able to understand it.

When I get sick, I want to find evidence that I can trust and that helps me to have meaningful discussions with my healthcare professionals.

I want to live in a world, where the media reports correctly about medical evidence and in which society distinguishes between fake evidence and real evidence.

Let’s work together to achieve this.