June 25, 2026 • 54 mins
As genomic medicine advances, questions around consent, data sharing, ownership and trust are becoming increasingly important. In this episode of When the Code Speaks, we are joined by Prof Jantina de Vries and Dr Melissa Nel to explore the ethical and governance challenges that sit at the heart of genomic research.
Together, we discuss what responsible data stewardship looks like in an African context, why community engagement matters, how genomic data can be shared ethically and what it takes to ensure that the benefits of research are returned to the communities who make it possible. This conversation highlights the critical role of ethics in building a genomic future that is equitable, trustworthy and sustainable.
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Episode Transcript
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(00:00):
Hello, my name is Erin Kinghorn and this is When the Code Speaks.
(00:03):
This podcast is a space where we explore what it actually takes to practice genomic medicine in South Africa.
The science, yes, but also the people, the systems and the realities behind it all.
Across this season, I'll be speaking to clinicians, researchers, advocates and system builders
working at the forefront of this field, unpacking everything from diagnosis and data
(00:24):
to ethics, infrastructure and patient experience.
We'll be getting into the complexity, asking some difficult questions and hopefully
making this space feel a little bit more accessible along the way.
I'm really glad you're here with me today.
All righty, on today's episode, we're turning our attention to ethics, governance and data stewardship in genomic research.
(00:49):
As genomic research continues to expand, questions around consent, data sharing, community trust and
equitable benefit are becoming increasingly central to how research is designed and implemented.
This conversation is really about how we balance scientific progress with responsibility and how we build systems that not only enable discovery,
(01:10):
but also protect and serve the communities involved.
Before we dive in, I'll just briefly introduce our guests for today.
I'm joined today by Professor Yantina de Vries, who heads up the ethics lab at UCT, and Dr. Melissa Nell, Director of the Clinical Omics and Informatics Unit.
Thank you both for being here and taking time out of your day.
Melissa, I'd like to start with you.
(01:33):
Could you tell us a little bit about what your work looks like in practice at the moment?
And then, Yantina, I'll come to you.
Thanks, Erin.
So I'm a medical doctor by training, who then moved over to the science field.
And my research focus is on genomic medicine.
So asking how we can use genome sequencing to uncover the genetic basis of rare diseases.
(02:01):
So it's very much through a diagnostic lens, so to speak, although we conduct this work in a research setting.
Great.
Yantina?
Great.
Thank you.
So thank you for having me, too.
My work really constitutes thinking about the ethics of health care and health research broadly, and specifically sometimes in the context of genomics research.
(02:25):
So especially in the past, I've been spending lots of time thinking about ethics in genetics, genomics, including what we owe people, how we use genomic science to promote fairer and just societies, where the risks of harm are and where they arise, and what we can do to address them and things like that.
(02:47):
These are the big questions that I suppose everyone should be asking.
And I think ethics can sometimes feel like something that happens maybe in the background or that's prioritized before any research takes place.
But it really shapes a lot of decision making in genomic research.
And Yantina, I want to know first, what first drew you to working in genomic medicine ethics?
(03:14):
That's an interesting question because I don't really remember.
It's been a very long time ago.
And I was wondering the other day for some other work I was doing whether and where that interest blossomed first.
And I'm not so sure.
And I think it was partly some really interesting books I read.
So I was young at the time when the Human Genome Project was happening with the big announcement by President Bill Clinton that scientists have now sequenced the full human genome.
(03:44):
And I think reading some books at that time, The Common Thread by John Salston at the time, who was very much involved in that Human Genome Project, I think sparked my interest.
But I've also got a lifelong fascination for biology.
In fact, I studied biology for a few years and dropped out, but retained the excitement of learning about genomics and genetics at the time in the early 2000s, late 1990s.
(04:10):
And so I think that's where it started.
Yeah.
And for about 20 years, I've been focusing on or witnessed to the entire field of genomics as it moved from small-scale genetic studies to large population cohort studies to increasingly advanced technologies to eventually human genome editing.
That's interesting.
I resonate actually quite a lot with what you have said now about just having this fascination with biology in general.
(04:35):
But it's interesting to me that you've sort of extended out beyond, quote-unquote, traditional biology a little bit, but still use that fascination in your day-to-day work.
I love that.
Melissa, is there a point that you find that you've come to in your career when you realized sort of how central ethics can be in this field and how important it is?
(05:04):
Yes, definitely.
And I think being part of the academic fabric and being, for example, in the same institute as Jantina and kind of immersed in the genomics research and the efforts that were happening and that have happened over the last couple of years,
(05:26):
has really shown me the breadth of the topic and how important it is to consider ethics really throughout the pursuit of your research.
I mean, I think from a practical and administrative point of view, you know, the first thing any researcher has to do before they undertake research is obtain ethics approval.
(05:47):
That's really just one particular point in time.
Yeah.
But really acknowledging that these processes are dynamic, scientific questions change, what we want to do with data changes, and really ethics and consent is an ongoing topic and something we need to be engaging with all the time.
(06:07):
Yeah.
Yeah.
And really also thinking ahead as to how our field is moving and what is changing and what is going to be needed in the future.
I mean, that sounds like it would actually be quite hard to do.
I mean, you don't know what you don't know, right?
And so do you find that it's difficult sometimes to sort of predict the future when you're engaging with an ethics platform to sort of think about that?
(06:31):
Definitely.
I mean, in my very short career, the way we do genomic research has changed drastically.
I mean, in the last couple of years, we've seen the introduction of AI, which is helping us immensely with interpretation and making things a lot faster.
Yeah.
We're seeing movements to share data globally, to use federated platforms.
(06:55):
And so the requirements of our consent are really, you know, needing to tick a lot of boxes.
Yeah.
And so I'm sure Yantina can definitely speak more to this.
But one approach is to really say, well, let's try and seek broad consent, you know.
And a lot of that, I suppose it has a link with future proofing in that one isn't entirely sure exactly how things are going to pan out.
(07:22):
Yeah.
And we all can't see into the future.
Yeah.
And so kind of ensuring that the resources one is creating, because many of these genomic sequencing technologies are expensive.
And much, you know, scientific input and financial input is invested in generating them.
Mm-hmm.
And we want to derive the most benefit from them.
(07:45):
Totally, yeah.
For the patients and the communities that we're trying to serve.
And so, yeah, I think it's one always has to kind of balance that with current consenting models.
But I'm sure Yantina's got more reflections on that topic.
Yeah.
I've got quite a lot to say about consent.
But maybe I can take a step back.
Yeah.
Because I think there's also another question that you're asking, which is why is ethics important in the field of genomics?
(08:08):
Mm-hmm.
At least that's what I think I heard you ask as well.
And I think the field of genomics is really interesting.
Yeah.
For two different reasons.
One is it has a really long and very troubled history, right?
So we know most people would have some understanding of eugenics, right?
Mm-hmm.
The use of arguments, not genetic science so much, but ideas about genetics that informed really discriminatory practices in many parts of the world.
(08:40):
Yeah.
And that has evoked such a strong sense, I think, that still seeds a really strong sense that in the field of when we use genes or genetics in research, we must be super cautious because we can also get it wrong.
Yeah.
And there is real harm that we can do to the world.
(09:01):
And I think more than any other field in medicine or health science, genetics attracts ethical concern and ethical regard.
So I find that really interesting.
I think it's also really interesting to think about the way that we often speak about genomics and genetics.
(09:21):
So the metaphors that we invoke to explain what genes are somehow tend to always emphasize how absolutely essential it is to what makes us human.
So we speak about, for instance, the blueprint of life.
It's like the archetype, whatever, the blueprint of your, yes, very strong words that signal to everyone else that when we use genes and genetics in research, we're shaping something fundamental, right?
(09:53):
We are affecting something that defines you at its core.
Now, I don't know that that's true.
I think that's probably, you know, sometimes not, it's not always very useful to use these kinds of metaphors.
But I think both of those explain why we feel strongly about ethics in this particular field.
And then I think another feature of genomics that's really interesting, and this is what Melissa was getting at, I think, is that even though I've been involved in that field for a very long time, it's forever at the forefront.
(10:22):
It never seems to not be at the forefront of where science is.
Yeah.
And that's really interesting because it was absolutely at the forefront 20 years ago.
But it has also been at the forefront of the entire open access revolution, for instance.
So Bermuda principles, you know, ideas about how do we share data?
Do we have an obligation to share data?
(10:44):
We're articulated in the field of genomics.
Big data, so the move towards really, really vast data sets about humans.
And again, the field of genomics pioneered that, as well as personalized medicine.
The field of genomics is at the forefront of that field, too.
And so what happens is there's a field where there's a strong ethical inclination on the one hand.
(11:09):
And the kinds of ethics that we need in order to think carefully about our practice is forever changing.
Yeah.
We never arrive.
We're forever innovating.
And that makes it a really fascinating field.
Yeah, for sure.
It's very exciting.
And I think the rate at which genomics just specifically is evolving and the markers always moving, while it's exciting, I think it can also make the whole question of being at the forefront of ethics challenging in some ways.
(11:47):
Because, like we mentioned earlier, you don't know what you don't know, and sometimes predicting how that marker is going to move can be a little bit tricky sometimes, right?
So what do you think could go wrong or what does go wrong if ethics clearance wasn't done well in a genomic medicine instance?
(12:09):
Are there any ideas that immediately pop to mind?
Either of you can jump in.
Sure.
Yeah.
So I think the consent process is integral.
I mean, I'm speaking as a researcher, you know, with that hat on.
And once you've obtained ethical approval to do something, you know, once you enroll research participants, you have to obtain informed consent from them.
(12:33):
And so what that means is that they really need to understand what it is they're agreeing to do as part of your research study.
And you need to be able to deliver that information in a way that is understandable to the population that you're dealing with without coercion.
You know, it's an informed process that the participant can, you know, you know, an equal sense of deciding whether they want to participate or not.
(13:03):
Yeah.
Yeah.
And also, you know, we're increasingly thinking about the other side of once the research has been done, you know, as part of the benefit sharing, how do we also, during the consent process, explain to participants how, what we're actually going to do with that information that they've contributed to generating?
(13:25):
How is it going to be shared? You know, what are the benefits and what are the risks? I mean, I think that's another, you know, aspect that we can't get away from.
Yeah.
It's an inherent property of the kind of work that we do. You know, we generate data, we store it and we share it. You know, there will be other sectors where that is true as well.
(13:48):
Your bank, you know, list any number of them and there are inherent risks. Yeah. And obviously we do everything in our power to minimize them, but they exist. So making sure that the consent process also is transparent about that. Yeah. And I think, yeah.
I like the way you've explained it because I've got it in my notes here. Actually, I've written down consent is not a form. It's more of a relationship that you're building. And I think you outlined a lot of sort of cornerstones of what that what a relationship like that would look like.
(14:24):
I mean, you spoke about risk. You spoke about trust. You spoke about being transparent. You spoke to a few a few points there that I think are very important. And I think people often misunderstand what ethics is. I mean, it's not necessarily just the green light to go ahead and do your research.
It really is like an ever evolving thing. Like I said in the beginning that you have to continuously be thinking about throughout your research. And then also when it's done, you know, you've got the onus sort of lies on you to say, well, what now? And and Yantina, do you have any perspective on on once maybe some research has been completed, what the responsibility should be for for someone ethically?
(15:12):
Yeah, I've got lots of thoughts on that question. But I just want to take a step back, if I may, and and just just do some kind of defining of what goes on in the space of ethics. So you mentioned ethics approval, and that's really important. So ethics approval is one way in which we ensure that researchers don't just go off and do something that nobody has looked at. Yeah. So it is a national obligation in South Africa, legal obligation for all health
(15:42):
health research to be reviewed by an ethics committee. And institutions like UCT, where Melissa and I work, have ethics committees, and then there's a national accrediting body that that makes sure that those ethics committees are constituted appropriately, do their work well, and so on and so forth. So that's a really important part of the almost like ethics landscape within which research takes place. Consent is part of that process. So an ethics committee will not
(16:12):
give you approval for a study until you have consent until you commit to taking consent and
until they've seen the consent form but but consent alone first of all simply getting ethics
approval doesn't mean that you that your study is then ethical right and and melissa has just
outlined that that simply having a form that says yes we will get consent and this is the information
(16:36):
will give people is not sufficient to ensure that people actually understand what they're being asked
to do yeah and so there is there are other obligations for researchers but there are also
bigger questions about what makes science ethical that are not that are not within the participants
purview so a participant may not think about who are the participants that are being invited for
(17:01):
this study are those the right participants which which groups which groups of the population
are left out is that right why are they left out yeah um what diseases are not being investigated
what are the consequences so those questions are far bigger questions than than than any single study
(17:23):
can or any single participant can think about or or address and so the work of ethics is to do both of
those things to look at the minute and that what the participant can see and or that what the individual
researcher can control but also to look at that bigger question what is the role of science in south africa
how do we use what is the obligation of scientists to contribute to societal transformation
(17:48):
to address questions of injustice that's the bigger work of ethics that we mustn't forget about
do you want me to go you can keep going you know that's that's cool but maybe you can remind me of the
question i i was just saying um that melissa outlined sort of a good a good analogy to use for for maybe
(18:10):
getting consent is to not look at it like a form but more like you're building a relationship between
maybe participant and researcher or you know if you want to look at it like that but it's an ever-evolving
thing where you like you mentioned in the beginning it's not just um it's good to get clearance in the
start but it's an evolving um it's a process consideration that yes exactly that should be at
(18:34):
the forefront of research throughout the process and then at the end there's also i think a responsibility
of researchers to think about what they're going to do with their output so my initial question was what your
thoughts are on what the responsibility is okay wonderful so there's a range of responsibilities i think
(19:00):
at the most basic level the idea of do no harm so and and i mean melissa's a medical doctor
doctors pledged the hippocratic oath the hippocratic oath says multiple things but amongst them it says do
good and do no harm or do as little harm as possible now in in the context of research that might mean
(19:23):
how do you make you how do you make sure that your research findings get translated into policy
so that your research doesn't end with a paper which builds your academic career but actually has a real
effect in the world now ethical questions that arise there is are to do with what what is the researcher's
(19:44):
responsibility what ought they do when they when their research ends when the funding ends yeah um there
are questions about benefit sharing so especially in some areas of the field in in areas of application
in the field of genomics there is possibly i'm saying that with some caution because i don't think
(20:06):
there there is huge commercial benefit to applications in general but it is imaginable that there are some
findings that have commercial application a big question is well who shares in the profit what do we do how do we share benefits from research with the people that participated with particular patient communities for instance a rare disease community and so on and so forth so those are also kind of questions that i think are really important
(20:34):
important yeah and then how do you feedback your findings to your participants what do you owe your participants after after the study
ends i think those are very important questions that might get uh somewhat overlooked i think by
um a majority of of of research just in the pursuit of an academic like in that academic pursuit you know to to obtain your
(21:00):
final final final final answer or to to get your result and show your result and like you mentioned i think you said your academic quest or something like that for the for the journal articles um so i think it is important to just consider you know the aftermath of what you've what you've done and i wonder if it is important to think about in the beginning when you're sort of applying for your initial approval is that something that's currently done melissa do you have any perspective on that um
(21:28):
um yes i mean that is something that we that we think about um and and engage with um and and in our information that we share with potential participants that we have outlined a clear plan for for what it is that we propose to do with with the findings um and yeah i think that's particularly in the in the rare disease community um
(21:56):
which I engage with as a researcher
there is a potential for individual results
that we might obtain through the research process
being beneficial to individual participants
and we have built in the appropriate mechanisms
(22:17):
to return those results
with the help of a genetic counsellor
who I know you've also spoken with on other episodes.
But potentially for the majority
because rare diseases are so rare
there is a strength in numbers
and in trying to collectively study diseases
(22:40):
from many different individuals
in order to try and uncover answers.
And in that way the contribution is unlikely
to generate any individual level results
for the research participant
but may benefit individuals with the same disease
that they have in communities etc.
(23:01):
And so I think where I'm going with that
is that the data sharing
and the kind of dissemination plans
and what we plan to do with the results
is a kind of really integral part
in the rare disease space.
And maybe just to jump slightly on a tangent
(23:22):
with respect to benefit sharing
I mean certainly what we try to do in our team
is that in the conduct of the research
we try to, I mean and this goes beyond
just simply sharing a result
or writing a lay summary
or speaking about it on the radio
in the very process of how we conduct our research
(23:45):
we are very passionate about doing it within South Africa.
Right.
So the very fact that, you know,
the research team that's actually doing the work
is doing it here.
The DNA sequencing that's being performed
is happening in country.
So every step in that pipeline
by being very intentional
about how that research process is designed
(24:06):
by that very nature we are thinking ahead.
Yeah.
And we are thinking in a way that says
we want this to benefit South Africans.
And so what we're grappling with
and what we're testing
what we're designing in the research space
is going to have value.
Sure.
Because that engine has now, has the potential
(24:29):
to benefit populations and our discoveries.
Yeah.
And I think that's really important.
Yeah.
I mean for us it's a key philosophy
that we're really passionate about.
Yeah.
And we'll really go to all lengths to make it happen.
Yeah.
Even if it costs a bit more.
In RAND terms.
I think we've spoken about this broad topic
(24:50):
on a few of the episodes so far actually
on what you just touched on
towards the end of your answer there.
In that, you know, the work that's
or the research that's being done
can be done in South Africa
and is being done.
And it also just speaks to that narrative
I think that people often have
that it can't be done here
(25:11):
and that it's only done in the global north
and that we're worse off.
And, you know, I think it's
I just like that you touched on that as well.
This is sort of removed from the
maybe the broader ethics conversation now.
But I just love that you said that though
because it's been so interesting
as you've been recording the episodes
for the series to see what themes emerge naturally
through the conversation.
And for me, that is an ethical issue.
(25:32):
I mean, that's a personal kind of conviction
that I have that I feel
that there's an ethical way
to conduct the research in practical terms.
Yeah.
It also brings in kind of a slightly bigger question
which is, so a lot of the research
that I would imagine Melissa and others do
(25:52):
has an ultimate aim
to improve the lives of patients
with particular diseases.
Yeah.
So in the field of rare genetics
that might be better diagnostics.
Yes.
Better diagnostic, genetic diagnostic test
that accurately represents the spectrum of mutations
that cause particular illnesses in this population.
(26:16):
The huge ethical question in that desire, right,
to see change in the healthcare system is
how do you make a claim for cost effectiveness
of those interventions?
How do we collectively as researchers
influence the entrepreneurial ecosystem
(26:37):
so that companies are incentivized
to actually produce those tests?
Yeah.
Offer them on the market.
How do we motivate for the inclusion of these tests
in the public health budget?
Yeah.
Not the public health budget,
but in the budget of public hospitals
so that these innovations reach the poorest people?
(26:59):
And that kind of question is often far outside
of what the primary researcher is concerned with or does.
I mean, Melissa, you don't have access probably
to hospital executive to motivate for a new genetic test,
but researchers play a huge role in motivating,
in being part of panels and committees
(27:23):
at the national level, for instance,
so that they can shape the discourse years in advance
so that by the time that your research actually leads to innovations
that affect people's lives directly,
you've set the stage for those innovations to be adopted.
And I think that too is an ethical question of
(27:43):
how do we ensure, practically,
how do we ensure that the research we do leads to actual differences
for people, for actual patients, even if not now,
then in the next decade or the next five years or so?
Yeah.
I think that is a major question and a very important one, for sure.
(28:04):
Do you think there's a straight-out answer for that, though?
Or do you sort of feel like advocating for South Africanness,
for lack of a better word,
and doing research here for the people that are here,
to benefit the people that are here,
is already making strides in that direction?
(28:28):
So I think the reason I mentioned it is because that's the end goal.
It's not the starting point.
And so the point that Melissa made about the importance
of fostering an entire ecosystem within the country,
within which genetics thrives,
and that goes from doing the research,
(28:50):
but also from training the research assistants,
from graduating students,
from outsourcing things to private companies
that operate in South Africa.
Like I mentioned, some of the sequencing happens,
not in the public sector, but in private companies.
All of that starts to build an environment
within which genomics and personalized medicine,
(29:12):
which is ultimately, I think,
what some people are hoping to foster,
builds the environment within which that goal can be realized.
Right.
And so I think we're on the way.
Yeah.
I don't think that's an impossibility.
But that kind of conscientiousness towards the importance
(29:37):
of not just outsourcing to international organizations,
for instance, is really important.
Yeah.
So I think Melissa's well on the way to having that kind of impact.
But patient advocacy is huge too.
Yeah.
So I think the rare disease community has an important role to play
in advocating both for the research,
(30:00):
but also for potential products that might come from research,
such as genetic tests.
Yeah.
And I think that's really something that we're increasingly thinking about,
is how to engage individuals with lived experience.
So this would be somebody who would be part of a particular population
that you are recruiting from for your research study to really ask,
(30:25):
well, how can they shape this research that we plan to undertake?
And thinking about how we can invite participation
from these kinds of individuals from the beginning of the research journey
to make sure that the questions we're trying to answer have benefits,
they have value, that we're studying the right, you know,
(30:45):
even simple things like Yantina mentioned,
that we're investing our efforts in the problems that matter here.
Yeah.
You know, making sure that the agenda is serving the communities here
who need it.
Yeah.
And, yeah, we've got, you know, different ideas, I suppose,
on how to gain feedback because, you know,
people with lived experience, obviously, the best.
(31:08):
Yeah, I think I agree with what both of you have said,
that I think it's an ongoing thing
and research is definitely moving in the right direction.
It's very exciting to see.
And I think that goes hand in hand
with how the space of genomic medicine is evolving so quickly.
I just want to use that to loop back onto something
(31:30):
that, Melissa, you mentioned earlier,
just in passing in one of your answers,
and you said the words data sharing.
And I think just for maybe for our listeners as well,
that can be a little bit of like to say data sharing could be like,
whoa, that's humans.
Like, you know, how does,
what is data sharing in the space of genomic medicine?
And can you just explain a little bit about what that is
(31:54):
and maybe why it's so important?
Sure.
I'm happy to tackle that.
So it's very relevant for us in rare diseases specifically.
And I think perhaps in other studies with different designs,
the data sharing would be sort of viewed as maybe a secondary objective.
So there would be the primary research question,
you know, the questionnaire that you're filling in
(32:16):
or the, you know, intervention you're going through
to generate an answer.
And the data sharing is, yeah, sort of very separate from that.
And I think the difference in rare diseases
is that the sharing of the data is really integral
and is what we really see as very powerful from a research perspective.
(32:36):
And as I mentioned, rare diseases are rare.
For some of the disorders that we study,
you could have just a handful of individuals in the entire world
with a particular condition that arises from a very specific genetic variant.
So when you encounter this genetic variant in isolation,
it can be difficult to make sense of.
But through a process that is known as matchmaking in our community,
(33:00):
if we are able to set up systems that can sort of ping us as researchers,
for example, that, you know, there's a researcher in Europe
who has now found the same variant as you and it matches,
we can actually be put in contact with one another
and can, between the two of us, actually solve a case.
(33:21):
Yeah.
And so that process of matchmaking is done on the data.
Right.
And so the data sharing and having systems, safe systems,
that allow us to connect in ways that we don't know we need to, right,
are really powerful for us.
And we've seen really, say, very innovative ways of achieving this,
(33:44):
of putting data in systems in an aggregate way.
So that's something that has really been very enabling for us as researchers
to share data.
And maybe I can just explain a little bit of what that is
because it might seem quite counterintuitive.
I was just going to say, yeah.
If you think of personal identifying information.
(34:04):
So let's say we used another form of personal identifying information
like your ID number or your street address.
And we were to collect this from a number of individuals
and we were to aggregate it or so-called mix it all up together
and just have a collection of all the numbers and all the names
and all the suburbs.
You can see that this, firstly, would be not very meaningful for anybody
(34:27):
if it's all completely jumbled and random numbers.
Yes, yes.
Even though you might not be able to re-identify anybody from that.
The difference with genomics is that aggregating in that way
is incredibly powerful for us.
And what it actually is, is looking at every single position
in the human genome code.
(34:49):
And for example, saying from a group of 100 people, how many individuals have got a certain base pair
at this position versus another?
And doing that for every single position in the genome.
It's what we call an allele frequency.
It's a particular frequency of a nucleotide.
And that is incredibly useful for us.
And in fact, when we study rare diseases, that's generally the single sort of first thing
(35:12):
that we're interested in is how rare is this variant?
Because if it's common, then its candidacy for causing a disease falls away.
And so by taking genetic information, so the code, from many different individuals
and aggregating it in this way, such that you could never re-separate it,
match it back to the individual participant, but you have a collective data set,
(35:36):
that is very powerful.
And it's through that vehicle that many of our research projects propose to share the genetic information.
And so I think it's really worthwhile that you've highlighted that,
because the kind of other lens by which people might assume it to be is like saying,
(35:57):
well, I'm just going to share all your address, all your personal information on the internet,
which is definitely not what it is.
But I think Jantina had some interesting reflections that we spoke about,
about the identifiability of the genome.
And what do you think of that?
I'll give you, I'll share what I said, but I'm also very keen, Melissa, before I do that.
(36:22):
Just for people to get a sense, can you just explain how many data points you work with
when you look at someone's genome?
Because I think that's just really interesting.
It's a great question.
Yes.
And people don't realize, I think, millions, right?
Yes.
The data actually is.
Yeah.
Yeah.
So if you're looking at the nucleotide sequence, you're looking at over 3 billion base pairs.
(36:44):
So this would be the composition of your genome if you were to string it out in a line
and read it with your A's, C's, T's and G's.
So it really is very large data.
And then within that kind of scaffold, we would be describing differences in an individual's code compared to a reference.
(37:05):
So where are there nucleotides?
Where are there nucleotides that are added or removed or flipped around in the sequence?
Yeah.
So yes, it's very large data.
It can be expensive to generate, particularly with the newer technologies.
Yeah.
And I think it's really always important to recognize how many single data points you have for an individual.
(37:32):
Yeah.
Because I think that's another reason for why data sharing is so important in the field of genomics is because the number of comparisons between two or three individuals are many, infinite, too many for you to work with meaningfully.
At least this is how I understand your field.
(37:52):
And so the only solution that you have to really meaningfully analyze that kind of data is to get more and more people so that the number of possible comparison reduces, right?
Something like that.
Yeah.
And so what I find useful as a metaphor there is people often refer to it's like a needle in a haystack.
Yeah.
And the more people you have, the more…
(38:16):
The more needles they are.
Well, the more needles they are, the greater the chance that you actually find one in that haystack.
And so that's why genomic scientists share data is so that their research can be more effective.
I think the metaphor that you referred to earlier is that something that I find very helpful in that question about genomic data and data sharing and are people identifiable is the analogy of the fingerprint.
(38:44):
So we're sitting in a studio and I might leave my fingerprint on a glass of water.
But if you don't know that that glass of water, that it's my fingerprint, right?
If there's no information, if you just have a random glass of water and with a fingerprint on it and you've got no way of knowing that that's me, there's no way of linking that back to me.
(39:08):
So it's the crucial question about is that fingerprint identifiable is can it be linked to a named individual, right?
Can the police, for instance, in a criminal case, police has nothing if they find a fingerprint without a way of linking it to a concrete individual, ideally with an address or a way of finding them.
(39:29):
Genomics is a little bit similar, I think.
So when that information gets shared, if there's no way of making that identifiable, i.e. that was Yantina's data, Yantina's genomic information, then that question seems to me to be less important, if you get what I mean?
Yeah. I mean, that's the concept of de-identification, which is built in from the sample collection phase all the way through to the data sharing.
(39:55):
So that idea that, yes, you are a research participant with a name and identifiable information, but once you've donated your sample, it is de-identified and you get a code and that code lives with the data.
And so when it's shared, all that so-called metadata about you and your identifying information does not live alongside the genomic data.
(40:19):
These are obviously two separate.
Yeah, totally.
I think it's also just important to note on that, that, I mean, if you do give your sample for, and it gets sequenced and all of that, it's not that it all of a sudden becomes irrelevant, like in the grander scheme and no one will ever be able to help you.
You know, it is sort of, that's, we're speaking in the context of aggregate data now, right?
(40:42):
Yes.
And, you know, it's not necessarily that your data is just going to go into this abyss that will never, or that, you know, it's not necessarily that your data is just going to go into this abyss that will never, or that, you know, it's not necessarily that your data is going to go into this abyss.
It could never come back to you and give you some sort of information.
The possibility is there for that.
But I mean, yeah, we're talking in the context of aggregate data now, right?
Yes.
The second thing that I wanted to say is just, I think what you guys both touched on is that there's a little bit of a disconnect between what genetic, like what the understanding of what genetic data is as well.
(41:15):
And I think that answers the question of, is it identifiable?
You touched on it now, Yantina, quite well in that, I mean, if you think about the data that we get from a sequencing platform, once you open it, you can open it in a text file and it's literally just ACs, Gs and Ts in different configurations and in different, like, combinations.
(41:37):
So getting a data file from a patient is not like, this is the genetic information of Erin Kinghorn.
And here it begins now, AC, GT, AC, AC, you know, it's literally just As and Cs and Gs.
So I think that also just is a connection that needs to be made and that, you know, it's de-identified, but it also is really difficult to identify that it's Erin Kinghorn on this, in this data file if you're just looking at ACs, Gs and Ts.
(42:08):
Yeah, right.
But we mustn't also underplay the possibility of identification.
For sure.
Especially with AI.
Totally.
Available.
And personal genomic companies, right?
So increasingly it is possible for people to have their own genome sequence.
Yeah.
For family history reasons, for instance, you might want to figure out your ancestry.
(42:31):
And so it is possible to identify people through their genomic information.
Yeah.
And it is becoming increasingly easier, I think, to do that, especially with big data analytics through AI being more readily available.
I think the critical question is, first of all, what are the risks?
(42:57):
So when and why would it be a problem if people are identified?
In the rare genetic disease community, there are some advocates, patient advocates, who have made very strong claims that the protectionism in the ethics field to say that people mustn't be identified is actually misguided.
(43:20):
Because if you have a severe illness, then you might exactly want people to know that this is your genetic data.
So that things can be shared.
So, and I'm speaking specifically about advocacy in the United States, for instance, by an organization called the Genetic Alliance.
Sharon Terry, as the president, made that claim many, many times and really powerfully.
(43:44):
So, who are we protecting for?
Who are we protecting?
And what are we protecting against?
So we're obviously protecting against harm, forms of harm.
The field of genomics has struggled to articulate exactly what harm could arise from someone's identification through participation in a genomic study.
(44:09):
So how do we, what are the imaginable scenarios where somebody would access data, research data, and use it to identify someone?
In order, you know, with the intention of harming them, I'm still not sure exactly what that would look like, what that scenario is.
(44:30):
And so there is definitely a drive to protect.
There are also other ethicists that say that maybe the focus shouldn't be so much on protecting against harm of identification, but actually on supporting an entirely different orientation.
Maybe we should share data in solidarity.
This is somebody from Austria, a colleague who's called Barbara Prensack has written quite a lot about data solidarity as a guiding principle and an alternative principle that we should think about when we think about data and the risk of identification.
(45:10):
And so I think the work of ethics, ethics happens where it's not clear what you ought to do.
It's in the gray zone.
When things are neither black nor white, we're not sure what to do.
And when we're not sure what to do, that's when we start to think about or use the language of ethics to help us figure out what the right thing is to do.
(45:34):
In the case of data sharing is scientifically enormously advantageous.
Yeah, I think.
Yeah, do it otherwise.
Yeah.
But there are also risks.
And so the balance is to think about where does that balance lie?
Yeah, I was just going to revert to that concept is that when you're weighing all these things up, you know, one often reverts back to thinking about, well, what benefits balance that risk?
(46:00):
You know, we're not saying the risk is not there.
Don't you know, it's articulated that we're not sometimes sure exactly what that risk is.
Yeah.
But what I often think about is what are the, you know, to look at it the other way, what are the potential harms of not sharing the data?
Right.
You know, we represent Africa in some platforms.
We're one of the only teams producing a certain data type from local populations in South Africa.
(46:27):
And if we are not contributing to this federated global database, the risk in my eyes is that the insights that are ultimately going to be derived from this amazing scientific resource, you know, that is informing our identification of the cause of disease that will possibly lead to, you know, the development of future therapies of better diagnostics.
(46:49):
If our populations are not part of that global resource that informs these discoveries, we have a fundamental issue because we are not sure then how translatable those findings are in a different population.
And so that's really also informed my thinking around the balancing of the, you know, acknowledging that the risks, you know, that there are risks.
(47:13):
Yeah.
But that, as Yantina said, it is a huge scientific and population benefit.
You know, it's not just about the science.
It's about the, for me, it's about the translation.
These are very translatable issues, you know, the, why are we all doing the work in the first place?
Yeah.
Is that we can diagnose these conditions better and that we can start to think about treating them.
(47:34):
Yeah.
Preventing them.
Yeah.
And if, yeah, if we're missing key pockets of genetic information, then we're building a biased data set.
Which has its own potential risks and harms.
Yeah.
I think I just want to actually have, I have a follow-up question based off of your answer now is, do you think there's like more importance or less importance needs to be put on, or do you think it's important?
(48:01):
Let me say that rather, to have or maintain African stewardship of African data if we're generating it here and we're like one of the only people or groups doing it in some instances.
Bit of a loaded one, maybe.
I think so.
But I think to keep it very simple, I think I just would like to bring it back to the, the chat we had around building a local ecosystem.
(48:30):
And so I think for me that the generation of African genomic data must be led by us on the continent.
Mm-hmm.
And I think that that's, that, that getting that practice, you know, feeling that that approach is ethical for me is what the importance is.
Mm-hmm.
Mm-hmm.
(48:50):
Because if you have somebody here with, with a rare disease, there is benefits in that data being shared in the global arena.
Yeah.
These are not, these are not problems that exist in silos.
Yeah.
These are global endeavors.
Yeah.
And I feel that Africans should be participating in global endeavors.
So I don't see, I don't see it, you know, in terms of sovereignty that, you know, that, that data shouldn't be shared.
(49:14):
Yeah.
I think that's, if, if that makes sense.
Yeah.
I think we must just be intentional about, about how we generate it.
Mm-hmm.
Um, with what intention, with what purpose.
Mm-hmm.
Um, and making sure that, that we are doing due diligence with the data that we've generated.
And I think that is really important.
I think if you've, I think we spoke about this the other day, that if you have taken consent from a research participant.
(49:39):
Mm-hmm.
And stated that, that the intention is to share the data.
Mm-hmm.
And that that sharing would really encapsulate the kind of benevolence of the participant's participation.
Mm-hmm.
Mm-hmm.
Where they've fully acknowledged that they may be unlikely to derive any personal benefit from participating.
Mm-hmm.
I feel as a researcher, you know, we have, you, we have to ethically uphold.
(50:01):
Yeah.
That commitment to share the data.
And perhaps that's what you were referring to in some of the rare disease kind of protectionist ideologies that, yeah, you can't let your academic, you know, be influenced by academics or publications or whatever.
Mm-hmm.
You have to be ethical in, in, in committing to how you propose to share the data.
(50:25):
Yeah. Which kind of brings us back to that original clarification that I tried to bring, which is ethics is about more than simply just ethics approval. It's the entire approach. It informs every step of that scientific journey.
I think that's just really important. How, as a researcher, do you respond to questions around data sharing, stewardship, and so on and so forth, is as important as whether you've got ethics approval. A bit of hesitation there because getting ethics approval is a legal obligation, which is a different kind of obligation. Ethics and law are not always the same.
(51:14):
But it's a holistic approach. Thinking about ethics means thinking about everything that happens in the context of a scientific research project.
I love that you have just said that, actually, that we've sort of come full circle in this conversation now because we're going to have to end off soon.
But I hope that our listeners have sort of also seen that full circle conversation.
(51:37):
I mean, we started off sort of quite simply by just speaking about what ethics actually looks like and maybe describing that for those who might not have a good understanding or have even heard about it at all.
And then we sort of got into what that looks like in genomic medicine and sort of how it's evolving in the in the ecosystem that we currently find ourselves in.
(52:00):
And then we also touched on data sharing and a little bit on stewardship, which I think are all like you just said, it's it's a really holistic way to look at ethics.
And again, it's it's it is really something that should be considered throughout the full decision making in in a research environment.
(52:22):
So, yeah, I just want to thank you guys again for taking time out of your day to be here and to have a chat with me.
I hope you enjoyed sitting in the hot seat today.
I don't know, Yantina, you are obviously with the Ethics Lab.
Do you maybe want to give them a little shout out for your LinkedIn, maybe your socials?
(52:42):
If people are interested in finding out more about what you do, where they could find that info?
Yeah, sure. So we are the Ethics Lab at UCT.
So I think if people just Google us, Ethics Lab UCT, you'll find us.
We are also on LinkedIn and we've got a very active website where we like to post lots of blogs with reflections about science and ethics,
(53:03):
including lots of thoughts around AI and ethics, genomics and ethics and so on and so forth.
So please follow us.
Great. Melissa, would you like to give Coyne a shout out?
Yes. So again, similar channels. So you can find us on LinkedIn.
So we're the Clinical Omics and Informatics, abbreviated to Coyne Unit, in the Department of Medicine at UCT.
(53:26):
You can have a look at our LinkedIn. Also on our website, we'll give you more of a feel for the kinds of research topics we explore.
Yeah. And we love hearing from anyone interested in genomics and genomic medicine.
So please feel free to reach out.
Great. Thanks, everyone.
If you're interested in hearing more about the work we're doing at the Clinical Omics and Informatics Unit,
(53:48):
you can explore other episodes in this season where we unpack different aspects of genomic medicine,
from clinical care and research to ethics, infrastructure and advocacy.
You can also follow us on social media at the Coyne Unit and read more about our work on our website at www.health.uct.ac.za.com.
In our next episode, we'll be chatting about from sample to sequence and how building the infrastructure that makes large-scale genomics possible takes place.
(54:18):
Stay tuned for that.
Hello, my name is Erin Kinghorn and this is When the Code Speaks.
(00:03):
This podcast is a space where we explore what it actually takes to practice genomic medicine in South Africa.
The science, yes, but also the people, the systems and the realities behind it all.
Across this season, I'll be speaking to clinicians, researchers, advocates and system builders
working at the forefront of this field, unpacking everything from diagnosis and data
(00:24):
to ethics, infrastructure and patient experience.
We'll be getting into the complexity, asking some difficult questions and hopefully
making this space feel a little bit more accessible along the way.
I'm really glad you're here with me today.
All righty, on today's episode, we're turning our attention to ethics, governance and data stewardship in genomic research.
(00:49):
As genomic research continues to expand, questions around consent, data sharing, community trust and
equitable benefit are becoming increasingly central to how research is designed and implemented.
This conversation is really about how we balance scientific progress with responsibility and how we build systems that not only enable discovery,
(01:10):
but also protect and serve the communities involved.
Before we dive in, I'll just briefly introduce our guests for today.
I'm joined today by Professor Yantina de Vries, who heads up the ethics lab at UCT, and Dr. Melissa Nell, Director of the Clinical Omics and Informatics Unit.
Thank you both for being here and taking time out of your day.
Melissa, I'd like to start with you.
(01:33):
Could you tell us a little bit about what your work looks like in practice at the moment?
And then, Yantina, I'll come to you.
Thanks, Erin.
So I'm a medical doctor by training, who then moved over to the science field.
And my research focus is on genomic medicine.
So asking how we can use genome sequencing to uncover the genetic basis of rare diseases.
(02:01):
So it's very much through a diagnostic lens, so to speak, although we conduct this work in a research setting.
Great.
Yantina?
Great.
Thank you.
So thank you for having me, too.
My work really constitutes thinking about the ethics of health care and health research broadly, and specifically sometimes in the context of genomics research.
(02:25):
So especially in the past, I've been spending lots of time thinking about ethics in genetics, genomics, including what we owe people, how we use genomic science to promote fairer and just societies, where the risks of harm are and where they arise, and what we can do to address them and things like that.
(02:47):
These are the big questions that I suppose everyone should be asking.
And I think ethics can sometimes feel like something that happens maybe in the background or that's prioritized before any research takes place.
But it really shapes a lot of decision making in genomic research.
And Yantina, I want to know first, what first drew you to working in genomic medicine ethics?
(03:14):
That's an interesting question because I don't really remember.
It's been a very long time ago.
And I was wondering the other day for some other work I was doing whether and where that interest blossomed first.
And I'm not so sure.
And I think it was partly some really interesting books I read.
So I was young at the time when the Human Genome Project was happening with the big announcement by President Bill Clinton that scientists have now sequenced the full human genome.
(03:44):
And I think reading some books at that time, The Common Thread by John Salston at the time, who was very much involved in that Human Genome Project, I think sparked my interest.
But I've also got a lifelong fascination for biology.
In fact, I studied biology for a few years and dropped out, but retained the excitement of learning about genomics and genetics at the time in the early 2000s, late 1990s.
(04:10):
And so I think that's where it started.
Yeah.
And for about 20 years, I've been focusing on or witnessed to the entire field of genomics as it moved from small-scale genetic studies to large population cohort studies to increasingly advanced technologies to eventually human genome editing.
That's interesting.
I resonate actually quite a lot with what you have said now about just having this fascination with biology in general.
(04:35):
But it's interesting to me that you've sort of extended out beyond, quote-unquote, traditional biology a little bit, but still use that fascination in your day-to-day work.
I love that.
Melissa, is there a point that you find that you've come to in your career when you realized sort of how central ethics can be in this field and how important it is?
(05:04):
Yes, definitely.
And I think being part of the academic fabric and being, for example, in the same institute as Jantina and kind of immersed in the genomics research and the efforts that were happening and that have happened over the last couple of years,
(05:26):
has really shown me the breadth of the topic and how important it is to consider ethics really throughout the pursuit of your research.
I mean, I think from a practical and administrative point of view, you know, the first thing any researcher has to do before they undertake research is obtain ethics approval.
(05:47):
That's really just one particular point in time.
Yeah.
But really acknowledging that these processes are dynamic, scientific questions change, what we want to do with data changes, and really ethics and consent is an ongoing topic and something we need to be engaging with all the time.
(06:07):
Yeah.
Yeah.
And really also thinking ahead as to how our field is moving and what is changing and what is going to be needed in the future.
I mean, that sounds like it would actually be quite hard to do.
I mean, you don't know what you don't know, right?
And so do you find that it's difficult sometimes to sort of predict the future when you're engaging with an ethics platform to sort of think about that?
(06:31):
Definitely.
I mean, in my very short career, the way we do genomic research has changed drastically.
I mean, in the last couple of years, we've seen the introduction of AI, which is helping us immensely with interpretation and making things a lot faster.
Yeah.
We're seeing movements to share data globally, to use federated platforms.
(06:55):
And so the requirements of our consent are really, you know, needing to tick a lot of boxes.
Yeah.
And so I'm sure Yantina can definitely speak more to this.
But one approach is to really say, well, let's try and seek broad consent, you know.
And a lot of that, I suppose it has a link with future proofing in that one isn't entirely sure exactly how things are going to pan out.
(07:22):
Yeah.
And we all can't see into the future.
Yeah.
And so kind of ensuring that the resources one is creating, because many of these genomic sequencing technologies are expensive.
And much, you know, scientific input and financial input is invested in generating them.
Mm-hmm.
And we want to derive the most benefit from them.
(07:45):
Totally, yeah.
For the patients and the communities that we're trying to serve.
And so, yeah, I think it's one always has to kind of balance that with current consenting models.
But I'm sure Yantina's got more reflections on that topic.
Yeah.
I've got quite a lot to say about consent.
But maybe I can take a step back.
Yeah.
Because I think there's also another question that you're asking, which is why is ethics important in the field of genomics?
(08:08):
Mm-hmm.
At least that's what I think I heard you ask as well.
And I think the field of genomics is really interesting.
Yeah.
For two different reasons.
One is it has a really long and very troubled history, right?
So we know most people would have some understanding of eugenics, right?
Mm-hmm.
The use of arguments, not genetic science so much, but ideas about genetics that informed really discriminatory practices in many parts of the world.
(08:40):
Yeah.
And that has evoked such a strong sense, I think, that still seeds a really strong sense that in the field of when we use genes or genetics in research, we must be super cautious because we can also get it wrong.
Yeah.
And there is real harm that we can do to the world.
(09:01):
And I think more than any other field in medicine or health science, genetics attracts ethical concern and ethical regard.
So I find that really interesting.
I think it's also really interesting to think about the way that we often speak about genomics and genetics.
(09:21):
So the metaphors that we invoke to explain what genes are somehow tend to always emphasize how absolutely essential it is to what makes us human.
So we speak about, for instance, the blueprint of life.
It's like the archetype, whatever, the blueprint of your, yes, very strong words that signal to everyone else that when we use genes and genetics in research, we're shaping something fundamental, right?
(09:53):
We are affecting something that defines you at its core.
Now, I don't know that that's true.
I think that's probably, you know, sometimes not, it's not always very useful to use these kinds of metaphors.
But I think both of those explain why we feel strongly about ethics in this particular field.
And then I think another feature of genomics that's really interesting, and this is what Melissa was getting at, I think, is that even though I've been involved in that field for a very long time, it's forever at the forefront.
(10:22):
It never seems to not be at the forefront of where science is.
Yeah.
And that's really interesting because it was absolutely at the forefront 20 years ago.
But it has also been at the forefront of the entire open access revolution, for instance.
So Bermuda principles, you know, ideas about how do we share data?
Do we have an obligation to share data?
(10:44):
We're articulated in the field of genomics.
Big data, so the move towards really, really vast data sets about humans.
And again, the field of genomics pioneered that, as well as personalized medicine.
The field of genomics is at the forefront of that field, too.
And so what happens is there's a field where there's a strong ethical inclination on the one hand.
(11:09):
And the kinds of ethics that we need in order to think carefully about our practice is forever changing.
Yeah.
We never arrive.
We're forever innovating.
And that makes it a really fascinating field.
Yeah, for sure.
It's very exciting.
And I think the rate at which genomics just specifically is evolving and the markers always moving, while it's exciting, I think it can also make the whole question of being at the forefront of ethics challenging in some ways.
(11:47):
Because, like we mentioned earlier, you don't know what you don't know, and sometimes predicting how that marker is going to move can be a little bit tricky sometimes, right?
So what do you think could go wrong or what does go wrong if ethics clearance wasn't done well in a genomic medicine instance?
(12:09):
Are there any ideas that immediately pop to mind?
Either of you can jump in.
Sure.
Yeah.
So I think the consent process is integral.
I mean, I'm speaking as a researcher, you know, with that hat on.
And once you've obtained ethical approval to do something, you know, once you enroll research participants, you have to obtain informed consent from them.
(12:33):
And so what that means is that they really need to understand what it is they're agreeing to do as part of your research study.
And you need to be able to deliver that information in a way that is understandable to the population that you're dealing with without coercion.
You know, it's an informed process that the participant can, you know, you know, an equal sense of deciding whether they want to participate or not.
(13:03):
Yeah.
Yeah.
And also, you know, we're increasingly thinking about the other side of once the research has been done, you know, as part of the benefit sharing, how do we also, during the consent process, explain to participants how, what we're actually going to do with that information that they've contributed to generating?
(13:25):
How is it going to be shared? You know, what are the benefits and what are the risks? I mean, I think that's another, you know, aspect that we can't get away from.
Yeah.
It's an inherent property of the kind of work that we do. You know, we generate data, we store it and we share it. You know, there will be other sectors where that is true as well.
(13:48):
Your bank, you know, list any number of them and there are inherent risks. Yeah. And obviously we do everything in our power to minimize them, but they exist. So making sure that the consent process also is transparent about that. Yeah. And I think, yeah.
I like the way you've explained it because I've got it in my notes here. Actually, I've written down consent is not a form. It's more of a relationship that you're building. And I think you outlined a lot of sort of cornerstones of what that what a relationship like that would look like.
(14:24):
I mean, you spoke about risk. You spoke about trust. You spoke about being transparent. You spoke to a few a few points there that I think are very important. And I think people often misunderstand what ethics is. I mean, it's not necessarily just the green light to go ahead and do your research.
It really is like an ever evolving thing. Like I said in the beginning that you have to continuously be thinking about throughout your research. And then also when it's done, you know, you've got the onus sort of lies on you to say, well, what now? And and Yantina, do you have any perspective on on once maybe some research has been completed, what the responsibility should be for for someone ethically?
(15:12):
Yeah, I've got lots of thoughts on that question. But I just want to take a step back, if I may, and and just just do some kind of defining of what goes on in the space of ethics. So you mentioned ethics approval, and that's really important. So ethics approval is one way in which we ensure that researchers don't just go off and do something that nobody has looked at. Yeah. So it is a national obligation in South Africa, legal obligation for all health
(15:42):
health research to be reviewed by an ethics committee. And institutions like UCT, where Melissa and I work, have ethics committees, and then there's a national accrediting body that that makes sure that those ethics committees are constituted appropriately, do their work well, and so on and so forth. So that's a really important part of the almost like ethics landscape within which research takes place. Consent is part of that process. So an ethics committee will not
(16:12):
give you approval for a study until you have consent until you commit to taking consent and
until they've seen the consent form but but consent alone first of all simply getting ethics
approval doesn't mean that you that your study is then ethical right and and melissa has just
outlined that that simply having a form that says yes we will get consent and this is the information
(16:36):
will give people is not sufficient to ensure that people actually understand what they're being asked
to do yeah and so there is there are other obligations for researchers but there are also
bigger questions about what makes science ethical that are not that are not within the participants
purview so a participant may not think about who are the participants that are being invited for
(17:01):
this study are those the right participants which which groups which groups of the population
are left out is that right why are they left out yeah um what diseases are not being investigated
what are the consequences so those questions are far bigger questions than than than any single study
(17:23):
can or any single participant can think about or or address and so the work of ethics is to do both of
those things to look at the minute and that what the participant can see and or that what the individual
researcher can control but also to look at that bigger question what is the role of science in south africa
how do we use what is the obligation of scientists to contribute to societal transformation
(17:48):
to address questions of injustice that's the bigger work of ethics that we mustn't forget about
do you want me to go you can keep going you know that's that's cool but maybe you can remind me of the
question i i was just saying um that melissa outlined sort of a good a good analogy to use for for maybe
(18:10):
getting consent is to not look at it like a form but more like you're building a relationship between
maybe participant and researcher or you know if you want to look at it like that but it's an ever-evolving
thing where you like you mentioned in the beginning it's not just um it's good to get clearance in the
start but it's an evolving um it's a process consideration that yes exactly that should be at
(18:34):
the forefront of research throughout the process and then at the end there's also i think a responsibility
of researchers to think about what they're going to do with their output so my initial question was what your
thoughts are on what the responsibility is okay wonderful so there's a range of responsibilities i think
(19:00):
at the most basic level the idea of do no harm so and and i mean melissa's a medical doctor
doctors pledged the hippocratic oath the hippocratic oath says multiple things but amongst them it says do
good and do no harm or do as little harm as possible now in in the context of research that might mean
(19:23):
how do you make you how do you make sure that your research findings get translated into policy
so that your research doesn't end with a paper which builds your academic career but actually has a real
effect in the world now ethical questions that arise there is are to do with what what is the researcher's
(19:44):
responsibility what ought they do when they when their research ends when the funding ends yeah um there
are questions about benefit sharing so especially in some areas of the field in in areas of application
in the field of genomics there is possibly i'm saying that with some caution because i don't think
(20:06):
there there is huge commercial benefit to applications in general but it is imaginable that there are some
findings that have commercial application a big question is well who shares in the profit what do we do how do we share benefits from research with the people that participated with particular patient communities for instance a rare disease community and so on and so forth so those are also kind of questions that i think are really important
(20:34):
important yeah and then how do you feedback your findings to your participants what do you owe your participants after after the study
ends i think those are very important questions that might get uh somewhat overlooked i think by
um a majority of of of research just in the pursuit of an academic like in that academic pursuit you know to to obtain your
(21:00):
final final final final answer or to to get your result and show your result and like you mentioned i think you said your academic quest or something like that for the for the journal articles um so i think it is important to just consider you know the aftermath of what you've what you've done and i wonder if it is important to think about in the beginning when you're sort of applying for your initial approval is that something that's currently done melissa do you have any perspective on that um
(21:28):
um yes i mean that is something that we that we think about um and and engage with um and and in our information that we share with potential participants that we have outlined a clear plan for for what it is that we propose to do with with the findings um and yeah i think that's particularly in the in the rare disease community um
(21:56):
which I engage with as a researcher
there is a potential for individual results
that we might obtain through the research process
being beneficial to individual participants
and we have built in the appropriate mechanisms
(22:17):
to return those results
with the help of a genetic counsellor
who I know you've also spoken with on other episodes.
But potentially for the majority
because rare diseases are so rare
there is a strength in numbers
and in trying to collectively study diseases
(22:40):
from many different individuals
in order to try and uncover answers.
And in that way the contribution is unlikely
to generate any individual level results
for the research participant
but may benefit individuals with the same disease
that they have in communities etc.
(23:01):
And so I think where I'm going with that
is that the data sharing
and the kind of dissemination plans
and what we plan to do with the results
is a kind of really integral part
in the rare disease space.
And maybe just to jump slightly on a tangent
(23:22):
with respect to benefit sharing
I mean certainly what we try to do in our team
is that in the conduct of the research
we try to, I mean and this goes beyond
just simply sharing a result
or writing a lay summary
or speaking about it on the radio
in the very process of how we conduct our research
(23:45):
we are very passionate about doing it within South Africa.
Right.
So the very fact that, you know,
the research team that's actually doing the work
is doing it here.
The DNA sequencing that's being performed
is happening in country.
So every step in that pipeline
by being very intentional
about how that research process is designed
(24:06):
by that very nature we are thinking ahead.
Yeah.
And we are thinking in a way that says
we want this to benefit South Africans.
And so what we're grappling with
and what we're testing
what we're designing in the research space
is going to have value.
Sure.
Because that engine has now, has the potential
(24:29):
to benefit populations and our discoveries.
Yeah.
And I think that's really important.
Yeah.
I mean for us it's a key philosophy
that we're really passionate about.
Yeah.
And we'll really go to all lengths to make it happen.
Yeah.
Even if it costs a bit more.
In RAND terms.
I think we've spoken about this broad topic
(24:50):
on a few of the episodes so far actually
on what you just touched on
towards the end of your answer there.
In that, you know, the work that's
or the research that's being done
can be done in South Africa
and is being done.
And it also just speaks to that narrative
I think that people often have
that it can't be done here
(25:11):
and that it's only done in the global north
and that we're worse off.
And, you know, I think it's
I just like that you touched on that as well.
This is sort of removed from the
maybe the broader ethics conversation now.
But I just love that you said that though
because it's been so interesting
as you've been recording the episodes
for the series to see what themes emerge naturally
through the conversation.
And for me, that is an ethical issue.
(25:32):
I mean, that's a personal kind of conviction
that I have that I feel
that there's an ethical way
to conduct the research in practical terms.
Yeah.
It also brings in kind of a slightly bigger question
which is, so a lot of the research
that I would imagine Melissa and others do
(25:52):
has an ultimate aim
to improve the lives of patients
with particular diseases.
Yeah.
So in the field of rare genetics
that might be better diagnostics.
Yes.
Better diagnostic, genetic diagnostic test
that accurately represents the spectrum of mutations
that cause particular illnesses in this population.
(26:16):
The huge ethical question in that desire, right,
to see change in the healthcare system is
how do you make a claim for cost effectiveness
of those interventions?
How do we collectively as researchers
influence the entrepreneurial ecosystem
(26:37):
so that companies are incentivized
to actually produce those tests?
Yeah.
Offer them on the market.
How do we motivate for the inclusion of these tests
in the public health budget?
Yeah.
Not the public health budget,
but in the budget of public hospitals
so that these innovations reach the poorest people?
(26:59):
And that kind of question is often far outside
of what the primary researcher is concerned with or does.
I mean, Melissa, you don't have access probably
to hospital executive to motivate for a new genetic test,
but researchers play a huge role in motivating,
in being part of panels and committees
(27:23):
at the national level, for instance,
so that they can shape the discourse years in advance
so that by the time that your research actually leads to innovations
that affect people's lives directly,
you've set the stage for those innovations to be adopted.
And I think that too is an ethical question of
(27:43):
how do we ensure, practically,
how do we ensure that the research we do leads to actual differences
for people, for actual patients, even if not now,
then in the next decade or the next five years or so?
Yeah.
I think that is a major question and a very important one, for sure.
(28:04):
Do you think there's a straight-out answer for that, though?
Or do you sort of feel like advocating for South Africanness,
for lack of a better word,
and doing research here for the people that are here,
to benefit the people that are here,
is already making strides in that direction?
(28:28):
So I think the reason I mentioned it is because that's the end goal.
It's not the starting point.
And so the point that Melissa made about the importance
of fostering an entire ecosystem within the country,
within which genetics thrives,
and that goes from doing the research,
(28:50):
but also from training the research assistants,
from graduating students,
from outsourcing things to private companies
that operate in South Africa.
Like I mentioned, some of the sequencing happens,
not in the public sector, but in private companies.
All of that starts to build an environment
within which genomics and personalized medicine,
(29:12):
which is ultimately, I think,
what some people are hoping to foster,
builds the environment within which that goal can be realized.
Right.
And so I think we're on the way.
Yeah.
I don't think that's an impossibility.
But that kind of conscientiousness towards the importance
(29:37):
of not just outsourcing to international organizations,
for instance, is really important.
Yeah.
So I think Melissa's well on the way to having that kind of impact.
But patient advocacy is huge too.
Yeah.
So I think the rare disease community has an important role to play
in advocating both for the research,
(30:00):
but also for potential products that might come from research,
such as genetic tests.
Yeah.
And I think that's really something that we're increasingly thinking about,
is how to engage individuals with lived experience.
So this would be somebody who would be part of a particular population
that you are recruiting from for your research study to really ask,
(30:25):
well, how can they shape this research that we plan to undertake?
And thinking about how we can invite participation
from these kinds of individuals from the beginning of the research journey
to make sure that the questions we're trying to answer have benefits,
they have value, that we're studying the right, you know,
(30:45):
even simple things like Yantina mentioned,
that we're investing our efforts in the problems that matter here.
Yeah.
You know, making sure that the agenda is serving the communities here
who need it.
Yeah.
And, yeah, we've got, you know, different ideas, I suppose,
on how to gain feedback because, you know,
people with lived experience, obviously, the best.
(31:08):
Yeah, I think I agree with what both of you have said,
that I think it's an ongoing thing
and research is definitely moving in the right direction.
It's very exciting to see.
And I think that goes hand in hand
with how the space of genomic medicine is evolving so quickly.
I just want to use that to loop back onto something
(31:30):
that, Melissa, you mentioned earlier,
just in passing in one of your answers,
and you said the words data sharing.
And I think just for maybe for our listeners as well,
that can be a little bit of like to say data sharing could be like,
whoa, that's humans.
Like, you know, how does,
what is data sharing in the space of genomic medicine?
And can you just explain a little bit about what that is
(31:54):
and maybe why it's so important?
Sure.
I'm happy to tackle that.
So it's very relevant for us in rare diseases specifically.
And I think perhaps in other studies with different designs,
the data sharing would be sort of viewed as maybe a secondary objective.
So there would be the primary research question,
you know, the questionnaire that you're filling in
(32:16):
or the, you know, intervention you're going through
to generate an answer.
And the data sharing is, yeah, sort of very separate from that.
And I think the difference in rare diseases
is that the sharing of the data is really integral
and is what we really see as very powerful from a research perspective.
(32:36):
And as I mentioned, rare diseases are rare.
For some of the disorders that we study,
you could have just a handful of individuals in the entire world
with a particular condition that arises from a very specific genetic variant.
So when you encounter this genetic variant in isolation,
it can be difficult to make sense of.
But through a process that is known as matchmaking in our community,
(33:00):
if we are able to set up systems that can sort of ping us as researchers,
for example, that, you know, there's a researcher in Europe
who has now found the same variant as you and it matches,
we can actually be put in contact with one another
and can, between the two of us, actually solve a case.
(33:21):
Yeah.
And so that process of matchmaking is done on the data.
Right.
And so the data sharing and having systems, safe systems,
that allow us to connect in ways that we don't know we need to, right,
are really powerful for us.
And we've seen really, say, very innovative ways of achieving this,
(33:44):
of putting data in systems in an aggregate way.
So that's something that has really been very enabling for us as researchers
to share data.
And maybe I can just explain a little bit of what that is
because it might seem quite counterintuitive.
I was just going to say, yeah.
If you think of personal identifying information.
(34:04):
So let's say we used another form of personal identifying information
like your ID number or your street address.
And we were to collect this from a number of individuals
and we were to aggregate it or so-called mix it all up together
and just have a collection of all the numbers and all the names
and all the suburbs.
You can see that this, firstly, would be not very meaningful for anybody
(34:27):
if it's all completely jumbled and random numbers.
Yes, yes.
Even though you might not be able to re-identify anybody from that.
The difference with genomics is that aggregating in that way
is incredibly powerful for us.
And what it actually is, is looking at every single position
in the human genome code.
(34:49):
And for example, saying from a group of 100 people, how many individuals have got a certain base pair
at this position versus another?
And doing that for every single position in the genome.
It's what we call an allele frequency.
It's a particular frequency of a nucleotide.
And that is incredibly useful for us.
And in fact, when we study rare diseases, that's generally the single sort of first thing
(35:12):
that we're interested in is how rare is this variant?
Because if it's common, then its candidacy for causing a disease falls away.
And so by taking genetic information, so the code, from many different individuals
and aggregating it in this way, such that you could never re-separate it,
match it back to the individual participant, but you have a collective data set,
(35:36):
that is very powerful.
And it's through that vehicle that many of our research projects propose to share the genetic information.
And so I think it's really worthwhile that you've highlighted that,
because the kind of other lens by which people might assume it to be is like saying,
(35:57):
well, I'm just going to share all your address, all your personal information on the internet,
which is definitely not what it is.
But I think Jantina had some interesting reflections that we spoke about,
about the identifiability of the genome.
And what do you think of that?
I'll give you, I'll share what I said, but I'm also very keen, Melissa, before I do that.
(36:22):
Just for people to get a sense, can you just explain how many data points you work with
when you look at someone's genome?
Because I think that's just really interesting.
It's a great question.
Yes.
And people don't realize, I think, millions, right?
Yes.
The data actually is.
Yeah.
Yeah.
So if you're looking at the nucleotide sequence, you're looking at over 3 billion base pairs.
(36:44):
So this would be the composition of your genome if you were to string it out in a line
and read it with your A's, C's, T's and G's.
So it really is very large data.
And then within that kind of scaffold, we would be describing differences in an individual's code compared to a reference.
(37:05):
So where are there nucleotides?
Where are there nucleotides that are added or removed or flipped around in the sequence?
Yeah.
So yes, it's very large data.
It can be expensive to generate, particularly with the newer technologies.
Yeah.
And I think it's really always important to recognize how many single data points you have for an individual.
(37:32):
Yeah.
Because I think that's another reason for why data sharing is so important in the field of genomics is because the number of comparisons between two or three individuals are many, infinite, too many for you to work with meaningfully.
At least this is how I understand your field.
(37:52):
And so the only solution that you have to really meaningfully analyze that kind of data is to get more and more people so that the number of possible comparison reduces, right?
Something like that.
Yeah.
And so what I find useful as a metaphor there is people often refer to it's like a needle in a haystack.
Yeah.
And the more people you have, the more…
(38:16):
The more needles they are.
Well, the more needles they are, the greater the chance that you actually find one in that haystack.
And so that's why genomic scientists share data is so that their research can be more effective.
I think the metaphor that you referred to earlier is that something that I find very helpful in that question about genomic data and data sharing and are people identifiable is the analogy of the fingerprint.
(38:44):
So we're sitting in a studio and I might leave my fingerprint on a glass of water.
But if you don't know that that glass of water, that it's my fingerprint, right?
If there's no information, if you just have a random glass of water and with a fingerprint on it and you've got no way of knowing that that's me, there's no way of linking that back to me.
(39:08):
So it's the crucial question about is that fingerprint identifiable is can it be linked to a named individual, right?
Can the police, for instance, in a criminal case, police has nothing if they find a fingerprint without a way of linking it to a concrete individual, ideally with an address or a way of finding them.
(39:29):
Genomics is a little bit similar, I think.
So when that information gets shared, if there's no way of making that identifiable, i.e. that was Yantina's data, Yantina's genomic information, then that question seems to me to be less important, if you get what I mean?
Yeah. I mean, that's the concept of de-identification, which is built in from the sample collection phase all the way through to the data sharing.
(39:55):
So that idea that, yes, you are a research participant with a name and identifiable information, but once you've donated your sample, it is de-identified and you get a code and that code lives with the data.
And so when it's shared, all that so-called metadata about you and your identifying information does not live alongside the genomic data.
(40:19):
These are obviously two separate.
Yeah, totally.
I think it's also just important to note on that, that, I mean, if you do give your sample for, and it gets sequenced and all of that, it's not that it all of a sudden becomes irrelevant, like in the grander scheme and no one will ever be able to help you.
You know, it is sort of, that's, we're speaking in the context of aggregate data now, right?
(40:42):
Yes.
And, you know, it's not necessarily that your data is just going to go into this abyss that will never, or that, you know, it's not necessarily that your data is just going to go into this abyss that will never, or that, you know, it's not necessarily that your data is going to go into this abyss.
It could never come back to you and give you some sort of information.
The possibility is there for that.
But I mean, yeah, we're talking in the context of aggregate data now, right?
Yes.
The second thing that I wanted to say is just, I think what you guys both touched on is that there's a little bit of a disconnect between what genetic, like what the understanding of what genetic data is as well.
(41:15):
And I think that answers the question of, is it identifiable?
You touched on it now, Yantina, quite well in that, I mean, if you think about the data that we get from a sequencing platform, once you open it, you can open it in a text file and it's literally just ACs, Gs and Ts in different configurations and in different, like, combinations.
(41:37):
So getting a data file from a patient is not like, this is the genetic information of Erin Kinghorn.
And here it begins now, AC, GT, AC, AC, you know, it's literally just As and Cs and Gs.
So I think that also just is a connection that needs to be made and that, you know, it's de-identified, but it also is really difficult to identify that it's Erin Kinghorn on this, in this data file if you're just looking at ACs, Gs and Ts.
(42:08):
Yeah, right.
But we mustn't also underplay the possibility of identification.
For sure.
Especially with AI.
Totally.
Available.
And personal genomic companies, right?
So increasingly it is possible for people to have their own genome sequence.
Yeah.
For family history reasons, for instance, you might want to figure out your ancestry.
(42:31):
And so it is possible to identify people through their genomic information.
Yeah.
And it is becoming increasingly easier, I think, to do that, especially with big data analytics through AI being more readily available.
I think the critical question is, first of all, what are the risks?
(42:57):
So when and why would it be a problem if people are identified?
In the rare genetic disease community, there are some advocates, patient advocates, who have made very strong claims that the protectionism in the ethics field to say that people mustn't be identified is actually misguided.
(43:20):
Because if you have a severe illness, then you might exactly want people to know that this is your genetic data.
So that things can be shared.
So, and I'm speaking specifically about advocacy in the United States, for instance, by an organization called the Genetic Alliance.
Sharon Terry, as the president, made that claim many, many times and really powerfully.
(43:44):
So, who are we protecting for?
Who are we protecting?
And what are we protecting against?
So we're obviously protecting against harm, forms of harm.
The field of genomics has struggled to articulate exactly what harm could arise from someone's identification through participation in a genomic study.
(44:09):
So how do we, what are the imaginable scenarios where somebody would access data, research data, and use it to identify someone?
In order, you know, with the intention of harming them, I'm still not sure exactly what that would look like, what that scenario is.
(44:30):
And so there is definitely a drive to protect.
There are also other ethicists that say that maybe the focus shouldn't be so much on protecting against harm of identification, but actually on supporting an entirely different orientation.
Maybe we should share data in solidarity.
This is somebody from Austria, a colleague who's called Barbara Prensack has written quite a lot about data solidarity as a guiding principle and an alternative principle that we should think about when we think about data and the risk of identification.
(45:10):
And so I think the work of ethics, ethics happens where it's not clear what you ought to do.
It's in the gray zone.
When things are neither black nor white, we're not sure what to do.
And when we're not sure what to do, that's when we start to think about or use the language of ethics to help us figure out what the right thing is to do.
(45:34):
In the case of data sharing is scientifically enormously advantageous.
Yeah, I think.
Yeah, do it otherwise.
Yeah.
But there are also risks.
And so the balance is to think about where does that balance lie?
Yeah, I was just going to revert to that concept is that when you're weighing all these things up, you know, one often reverts back to thinking about, well, what benefits balance that risk?
(46:00):
You know, we're not saying the risk is not there.
Don't you know, it's articulated that we're not sometimes sure exactly what that risk is.
Yeah.
But what I often think about is what are the, you know, to look at it the other way, what are the potential harms of not sharing the data?
Right.
You know, we represent Africa in some platforms.
We're one of the only teams producing a certain data type from local populations in South Africa.
(46:27):
And if we are not contributing to this federated global database, the risk in my eyes is that the insights that are ultimately going to be derived from this amazing scientific resource, you know, that is informing our identification of the cause of disease that will possibly lead to, you know, the development of future therapies of better diagnostics.
(46:49):
If our populations are not part of that global resource that informs these discoveries, we have a fundamental issue because we are not sure then how translatable those findings are in a different population.
And so that's really also informed my thinking around the balancing of the, you know, acknowledging that the risks, you know, that there are risks.
(47:13):
Yeah.
But that, as Yantina said, it is a huge scientific and population benefit.
You know, it's not just about the science.
It's about the, for me, it's about the translation.
These are very translatable issues, you know, the, why are we all doing the work in the first place?
Yeah.
Is that we can diagnose these conditions better and that we can start to think about treating them.
(47:34):
Yeah.
Preventing them.
Yeah.
And if, yeah, if we're missing key pockets of genetic information, then we're building a biased data set.
Which has its own potential risks and harms.
Yeah.
I think I just want to actually have, I have a follow-up question based off of your answer now is, do you think there's like more importance or less importance needs to be put on, or do you think it's important?
(48:01):
Let me say that rather, to have or maintain African stewardship of African data if we're generating it here and we're like one of the only people or groups doing it in some instances.
Bit of a loaded one, maybe.
I think so.
But I think to keep it very simple, I think I just would like to bring it back to the, the chat we had around building a local ecosystem.
(48:30):
And so I think for me that the generation of African genomic data must be led by us on the continent.
Mm-hmm.
And I think that that's, that, that getting that practice, you know, feeling that that approach is ethical for me is what the importance is.
Mm-hmm.
Mm-hmm.
(48:50):
Because if you have somebody here with, with a rare disease, there is benefits in that data being shared in the global arena.
Yeah.
These are not, these are not problems that exist in silos.
Yeah.
These are global endeavors.
Yeah.
And I feel that Africans should be participating in global endeavors.
So I don't see, I don't see it, you know, in terms of sovereignty that, you know, that, that data shouldn't be shared.
(49:14):
Yeah.
I think that's, if, if that makes sense.
Yeah.
I think we must just be intentional about, about how we generate it.
Mm-hmm.
Um, with what intention, with what purpose.
Mm-hmm.
Um, and making sure that, that we are doing due diligence with the data that we've generated.
And I think that is really important.
I think if you've, I think we spoke about this the other day, that if you have taken consent from a research participant.
(49:39):
Mm-hmm.
And stated that, that the intention is to share the data.
Mm-hmm.
And that that sharing would really encapsulate the kind of benevolence of the participant's participation.
Mm-hmm.
Mm-hmm.
Where they've fully acknowledged that they may be unlikely to derive any personal benefit from participating.
Mm-hmm.
I feel as a researcher, you know, we have, you, we have to ethically uphold.
(50:01):
Yeah.
That commitment to share the data.
And perhaps that's what you were referring to in some of the rare disease kind of protectionist ideologies that, yeah, you can't let your academic, you know, be influenced by academics or publications or whatever.
Mm-hmm.
You have to be ethical in, in, in committing to how you propose to share the data.
(50:25):
Yeah. Which kind of brings us back to that original clarification that I tried to bring, which is ethics is about more than simply just ethics approval. It's the entire approach. It informs every step of that scientific journey.
I think that's just really important. How, as a researcher, do you respond to questions around data sharing, stewardship, and so on and so forth, is as important as whether you've got ethics approval. A bit of hesitation there because getting ethics approval is a legal obligation, which is a different kind of obligation. Ethics and law are not always the same.
(51:14):
But it's a holistic approach. Thinking about ethics means thinking about everything that happens in the context of a scientific research project.
I love that you have just said that, actually, that we've sort of come full circle in this conversation now because we're going to have to end off soon.
But I hope that our listeners have sort of also seen that full circle conversation.
(51:37):
I mean, we started off sort of quite simply by just speaking about what ethics actually looks like and maybe describing that for those who might not have a good understanding or have even heard about it at all.
And then we sort of got into what that looks like in genomic medicine and sort of how it's evolving in the in the ecosystem that we currently find ourselves in.
(52:00):
And then we also touched on data sharing and a little bit on stewardship, which I think are all like you just said, it's it's a really holistic way to look at ethics.
And again, it's it's it is really something that should be considered throughout the full decision making in in a research environment.
(52:22):
So, yeah, I just want to thank you guys again for taking time out of your day to be here and to have a chat with me.
I hope you enjoyed sitting in the hot seat today.
I don't know, Yantina, you are obviously with the Ethics Lab.
Do you maybe want to give them a little shout out for your LinkedIn, maybe your socials?
(52:42):
If people are interested in finding out more about what you do, where they could find that info?
Yeah, sure. So we are the Ethics Lab at UCT.
So I think if people just Google us, Ethics Lab UCT, you'll find us.
We are also on LinkedIn and we've got a very active website where we like to post lots of blogs with reflections about science and ethics,
(53:03):
including lots of thoughts around AI and ethics, genomics and ethics and so on and so forth.
So please follow us.
Great. Melissa, would you like to give Coyne a shout out?
Yes. So again, similar channels. So you can find us on LinkedIn.
So we're the Clinical Omics and Informatics, abbreviated to Coyne Unit, in the Department of Medicine at UCT.
(53:26):
You can have a look at our LinkedIn. Also on our website, we'll give you more of a feel for the kinds of research topics we explore.
Yeah. And we love hearing from anyone interested in genomics and genomic medicine.
So please feel free to reach out.
Great. Thanks, everyone.
If you're interested in hearing more about the work we're doing at the Clinical Omics and Informatics Unit,
(53:48):
you can explore other episodes in this season where we unpack different aspects of genomic medicine,
from clinical care and research to ethics, infrastructure and advocacy.
You can also follow us on social media at the Coyne Unit and read more about our work on our website at www.health.uct.ac.za.com.
In our next episode, we'll be chatting about from sample to sequence and how building the infrastructure that makes large-scale genomics possible takes place.
(54:18):
Stay tuned for that.
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