Moving into the Digital Era of Alzheimer’s Disease Research

Headshot of Rhoda Au
Rhoda Au, PhD

Dementia Matters Special Series: The National Strategy for Alzheimer's Disease Data and Research Part 5

Whether it be due to new research findings, innovative approaches and ideas, or technological advancements, Alzheimer’s disease research is constantly evolving. Now, dementia research is headed into the digital frontier. Dr. Rhoda Au joins the podcast to discuss digital biomarkers, gamifying cognitive testing, and how the field of Alzheimer’s disease research is entering its digital age.

Guest: Rhoda Au, PhD, digital technology leader, Boston University Alzheimer’s Disease Research Center, co-principal investigator, director of neuropsychology, Framingham Heart Study, professor, Boston University School of Medicine

Show Notes

Watch Dr. Rhoda Au’s presentation from NACC’s Spring ADRC Meeting on NACC’s YouTube channel.

Learn more about Dr. Au at her bio on the Boston University Chobanian & Avedisian School of Medicine website.

Learn more about the National Alzheimer’s Coordinating Center at their website.

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Intro: I’m Dr. Nathaniel Chin, and you’re listening to Dementia Matters, a podcast about Alzheimer's disease. Dementia Matters is a production of the Wisconsin Alzheimer's Disease Research Center. Our goal is to educate listeners on the latest news in Alzheimer's disease research and caregiver strategies. Thanks for joining us.

Dr. Nathaniel Chin: Welcome back to Dementia Matters and to our special series on the National Strategy for Alzheimer’s Disease Data and Research. Today I’m joined by Dr. Rhoda Au, digital technology leader at Boston University’s Alzheimer’s Disease Research Center and professor of anatomy and neurobiology at Boston University. She is also co-principal investigator and director of neuropsychology at the Framingham Heart Study, a research project launched in 1948 to study heart disease and stroke. Dr. Au is known for spearheading the digital age of cognitive change research, and gave a presentation at the Spring ADRC Meeting on digital biomarkers and cognitive testing in the ADRCs. Dr. Au joined me live at the conference to discuss her work and the developments being made to push the field of Alzheimer’s disease research into the digital age. Welcome to Dementia Matters, Dr. Rhoda Au.

(Music Interlude)

Dr. Nataniel Chin: Welcome to Dementia Matters, Dr. Rhoda Au. At this year’s meeting, you presented on digital biomarkers. This is what you said was your eighth presentation on the topic. I didn’t realize you had your MBA and it takes at least seven iterations before something can stick – I think that’s how you said it. You’re very excited this year and I am too. I was hoping you could start by, just for our audience who’s new to this, what is a digital biomarker?

Dr. Rhoda Au: So you would think that that would be an easy question, but it’s actually not. Right now, the term “digital biomarker” is often referring to collecting clinical measures digitally, but I actually think that we need to be more thoughtful in our consideration of what do we mean by digital biomarker. I do think we need to start thinking about categories of digital biomarkers. The reason I think that is because you need to have some near term pragmatic for what we would call digital biomarkers because we’ve got clinical studies, clinical trials, etc cetera. I think that that’s the majority of when you use digital health technology to collect some sort of digital metric. I think right now, that is – that describes what most people would call a digital biomarker. In my mind, that’s actually more digital phenotyping – right? – which is that you are certainly characterizing the information, the behavior, digitally, but that doesn’t necessarily mean it’s a digital biomarker. I do think that the digital biomarker concept, just like a traditional biomarker, is going to need some validation work. I still think that we have – we’re steps away from really having a robust class of digital biomarkers, and then I think that there’s even another class of digital biomarkers, and that’s the one that I think is still in the future. That’s something that I see as being much more free-flowing, dynamic, and not – doesn’t fit our traditional concept of a digital biomarker.

Chin: What you said about most of us thinking of digital biomarkers as digital testing – taking traditional cognitive tests that we do in clinic or in research and digitizing them – what does that look like though? For those of our listeners who are research participants or are patients who have gone through traditional testing, which of these things can actually be put into a digital format?

Au: I would say that almost any test that’s being given could actually be put in a digital format. For instance, if we think about traditional cognitive testing – right? – there’s two forms of responses. One is that you ask a question and they respond verbally. How would you convert that into digital? You would digitally voice record it, right? That’s an audio recording, and that’s just a digital recorder. The other way in which we collect responses is written responses, and that you can do with a digital pen, with a stylus on a tablet. Then, of course, there’s computer-based versions of picking that up as well. Those would all be means in which you could take anything that you’re already doing as a paper-and-pencil test and collecting that data. It just means capturing it digitally rather than just in the traditional way we do now.

Chin: Some people have test anxiety. I know that’s something, as a neuropsychologist, we always have to consider the context of the person taking the test, not doing well on a test but maybe that doesn’t reflect how they’re actually performing in real life. So I’ve heard people say “gamifying” – doing some novel or new type of cognitive assessment that’s done with a computer, an iPad, or some type of tablet device that’s not traditional. It’s not something that you’d normally see, but it’s still sort of measuring some of the different parts of the brain.

Au: Mm-hmm.

Chin: Do you see that as equally as useful or maybe entering – starting to get into the more creative world of digital testing?

Au: Yeah, I think that the gamification, I think, right now that’s what we think about in terms of making cognitive assessments a little bit more creative is to make them “more fun” with these different tests. It is true, because everything we do we do through our brain. When we’re doing these different games and etc cetera, we definitely are reflecting our cognitive capabilities. It’s all about how are we capturing that data and then how are we analyzing and interpreting that, but I would say that we could go one step further. I would say that we could even remove, sort of, the game version of that and then just start to think about how do we collect people’s behaviors in their natural environments as they’re interacting with it, right? There’s lots of different sensor-based technologies that are available today. If we do that, we take away, maybe, the artificial aspect of thinking about cognitive assessment and more think about how do we capture in a more natural, ongoing way. That’s where you’re going to get away from this concept of test anxiety because you’re no longer testing people. I like to always remind people, you know, when we do clinical intakes of people for the first time and we ask them, “When did you first notice your memory impairment?”, they don’t give you a list of scores – test scores. What they do is they give you, “Oh, well this is what I did and I forgot this. I remember this and I forgot to pay that bill. I got lost.” And the family member will be, “Yeah, you know, they keep repeating that same story over and over again.” And then the other family member – “Well, you remember that time…”. What’s interesting here though, and I think the point is, is that there’s no one question. There’s no one answer that says that person has a memory impairment, but if you put the whole compilation of different kinds of behaviors that they’ve been engaging in and emitting, I think there is a consensus there’s a memory impairment. That’s what we have to get to. That’s what I think digital can do. I think when we start to do that, we’re starting to get at accurate cognitive assessments.

Chin: What has taken us so long in the field of cognitive evaluation to go from this standard paper-pen testing to this type of evaluation of people’s normal, regular behaviors?

Au: Well, I think that, because we like to engage in the scientific process, I think that we have these standardized methods and in order – and there’s multiple steps that we need to take to get to this – what I would call – more free-flowing way of collecting data. The other thing is that digital is really new, even the concept of digital biomarkers. You know, when I went to PubMed and I just put in the words “digital biomarkers” together. If you look at the publications, the very first one that really comes up is 2014. This is how new the field is, and I think there was like one publication. If you actually look at the number of publications since 2014 til now, the majority have been in the past few years. So I think we need to appreciate that this is a whole new frontier, right? It’s always very hard to go from where you are to where you should be, particularly when where you should be is still so well-defined. One of the things that people always think is, “Oh, it’s so great to be so innovative, cutting-edge, forward-thinking, blah, blah, blah.” Well it turns out that it’s actually not. I tell people it’s terrible to be first and it’s actually better to be tenth because then there’s at least some sort of pathway that’s been carved. It’s really hard remembering that we work within a precedent-based system, right? It’s peer-review. We do peer-review grants; we do peer-review papers. What happens if you’re trying to get to this vision of where to go but there’s no precedent, there’s no peers? How do you even start, because you can’t get grants funded for it. Certainly once you produce a manuscript, you can’t get it published, at least not very easily.

Chin: I would say that a lot of our participants and a lot of our patients when they think of digital, the first thing they’ll ask me is, ‘Well, can I go online and do a brain game?’

Au: Mm-hmm.

Chin: So often now when we talk about brain health and keeping people’s brains active, it kind of shifts to that as far as a treatment modality now. This is different then, of course, what you’re talking about, this free flow and this idea of just measuring people’s abilities in their everyday life. When it comes to people trying to improve brain activity, what do you think of digital, online brain games?

Au: I think that anything that keeps your brain active is a good thing. If it happens to be a brain game that you really enjoy, and keeps you engaged and moving forward, and gets those competitive juices up because you’re trying to do better, that’s not a bad thing. It’s no different than you going and doing crossword puzzles or you reading a book or staying on top. Anything that moves those executive functions around, I don’t think it’s ever bad. I don’t care what you call it, whether it’s in the form of a brain game or if it's a form of going and playing bridge with your friends or whatever. There’s something to be said about the concept of “use it or lose it,” so you might as well continue using it however you can find the way to do so.

Chin: You know, a question that came up at this Spring Meeting, which is one I’ve heard asked of you before, is this idea of safety and privacy. Of course, in the world of technology and, frankly, recent digital attacks, what are you – are you worried about this or are there things in place that have already protected people?

Au: I think that if you do not figure out a way to do this without protecting peoples’ confidentiality and privacy, you’re going to be dead in the water. (laughs) So this is something that I worry about all the time. I think that certainly anybody in the digital realm – as far as, you know, being HIPAA-compliant, making sure that they’re doing encryption so that if anybody intercepts midway they’re not actually getting any personal identifying information. I think those are all pretty standard practice. I do think we have to be honest, though, too. As we know in the digital world, there is no such thing as a 100% guarantee, but I do think that there are many different steps right now that are taken to mitigate the risk. Having said that, I think where we really need to go if we really want to fully protect is we want to get to the point where we have more self-contained evaluations that are doing feedback internally so that it’s really restricted to the participant or the person and to whomever they want to share that information with, but we’re not there yet. In order to get to that truly private world, we have to go through this period of discovery, which we are trying to make sure that we always put security, privacy top of mind. But I do think we also have to be very clear – and we’ve seen this in breaches of data – no data is 100% secure. I do think that we’re as secure as you can possibly be, at least at this point but that doesn’t mean that we can’t get better.

Chin: And you mentioned how things have really exploded from 2014 to now, and certainly this is a topic that’s discussed more often. I guess I just wonder, how do people account for the acceleration in the technology, in the creativity of how people are looking at this? How does that… how do you future-proof – I believe you said – how do you future-proof for these new things that we haven’t thought of yet?

Au: Yeah, so I think that right now no matter what is best of class, it’s going to be obsolete in about a year or two. Version one of nothing has stood the test of time. Knowing that, what you have to think about strategically is, as you’re collecting the data, understanding that whatever derived measures you’re getting, whatever algorithms you’re using – I don’t actually really care because it doesn’t matter because it’s going to be obsolete soon. But you know that upfront and that part is definitive. Therefore it becomes, how do you collect that data in a way so that when these future opportunities come along, you can actually bring all of your measures up to contemporary standards. For me, I always look for technologies that not just give me the more immediate, kind of, measure of interest. I’m interested in, do you give me the raw digital data stream from which that's based on because if I have that then, as these new algorithms appear, I can go back and reanalyze that data again, right? I always compare this to blood, when you store blood. You know, we didn’t know when we collected blood way back in the 80s or whatever that genetics or multiomics would be such a big thing or AD biomarkers, which didn’t really exist then. But because we have the stored blood and we had stored it in its whole blood form, plasma serum, we stored it in a state that allowed us to apply these new advances. I think of digital in the same way as that. It’s just that it’s a non-diluting resource so it’s something that you can keep reusing and reusing and reusing, so you can be a lot more liberal with how you try out different ways of looking at digital because you never lose it.

Chin: And so at this conference you presented the Digital UDS pilot, which I think we’re all very excited about and everyone in the audience had a lot of great questions and they all seemed very enthusiastic. Could you share with our listeners what this pilot is and what you’re looking forward to?

Au: Sure. So I think what we’re trying to do is figure out how do we get the digital era started, essentially, but we have to do it thoughtfully because we have to be mindful of the fact that there is already a tradition within the UDS, right? We have clinical measures that have been long collected and we have cognitive tests that have been long collected, and so we want to make sure that we also protect the longitudinal integrity of that data as well and then, on top of that, bring in some digital. What we’ve tried to do is we try to find things that would complement or amplify what’s being collected on the clinical measures side, what’s going to be collected on the cognitive side, in order so that we can enhance and move things forward. Again, in a more strategic way because we can’t put every bell and whistle in there. We don’t even want to put every bell and whistle in there because some of those bells and whistles aren’t going to stand the test of time. So we want to make sure that we strategically select different kinds of digital measures that are, I would say, supplementary and complementary to what’s already in place. You know, the whole still moves. I think the enterprise – the longitudinal, it protects sort of the longitudinal component but then also sets the stage for the future opportunities.

Chin: Well, Dr. Rhoda Au, thank you so much for being on this podcast and highlighting your presentation. I do hope to have you on again for a different reason highlighting one of your other many publications.

Au: Thank you very much.

Outro: Thank you for listening to Dementia Matters. Follow us on Apple Podcasts, Spotify, Google Podcasts, or wherever you listen or tell your smart speaker to play the Dementia Matters podcast. Please rate us on your favorite podcast app -- it helps other people find our show and lets us know how we are doing. Dementia Matters is brought to you by the Wisconsin Alzheimer's Disease Research Center at the University of Wisconsin--Madison. It receives funding from private, university, state, and national sources, including a grant from the National Institutes of Health for Alzheimer's Disease Centers. This episode of Dementia Matters was produced by Amy Lambright Murphy and edited by Caoilfhinn Rauwerdink. Our musical jingle is "Cases to Rest" by Blue Dot Sessions. To learn more about the Wisconsin Alzheimer's Disease Research Center and Dementia Matters, check out our website at, and follow us on Facebook and Twitter. If you have any questions or comments, email us at Thanks for listening.