How Genomics Can Transform Cancer Treatment in Africa | A Conversation with Prof. Oluyemi Akinloye

At WHX Lagos, we had an inspiring conversation with Professor Oluyemi Akinloye on the future of cancer care in Africa.
His groundbreaking research is helping to put African genomic data on the global map, opening the door to more accurate diagnoses, better treatments, and truly personalized care for African patients.
This is more than a conversation about challenges, it’s about solutions, innovation, and the partnerships that can transform healthcare outcomes across the continent.
The future of precision medicine in Africa is already taking shape and it’s promising.
Listen to the full interview and be part of the change
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🔗 Link in bio
#WHXLagos #WHXLagos2026 #WHX2026 #HealthcareInAfrica #Genomics #PrecisionMedicine #CancerCare

Transcript

SPEAKER_02 0:10

Hello, healthcare enthusiasts, and welcome back to The Cure. We are at day three of WHX Lagos, and we are sitting with Professor Uluyami Akinluye, the director of the Center for Genomics of Non-Communicable Diseases and Personalized Healthcare. Thank you so much for speaking with us, Professor Akinouye.

SPEAKER_00 0:30

Thank you. Thank you.

SPEAKER_02 0:31

So I had so many questions prepared, but you gave such an amazing keynote that I had to actually write all new questions. So it's only the new questions I'm going to be asking you. My first question is you shared a very powerful example in your keynotes. You said that a small seven-patient study that you ran across Nigeria and Tanzania for patients with a very aggressive form of leukemia, acute myeloid leukemia, turned off mutations and splicing variants that weren't represented in the existing global library of the genomics for that disease. And Illumnia is now customizing their library based on your team's findings. And how can we proliferate this model for NCDs as a whole? How can we continue to foster these types of partnerships?

SPEAKER_00 1:30

Yeah, you know, uh, Inunna biotechnology complaint is um is a very versatile biotechnology complaint. They over the years have customized library, especially for uh oncology diagnosis. Some of their libraries are currently being used in most places of the world. But from the pilot study that we did, we found out that some of the genes that were uh that some of the mutations that we identify, some of the spices are not included in the common libraries that are available. It is nothing special for Illumina. They can always customize library based on your gene of interest. So what we did uh when I what I did in Canada, not in Nigeria, was to have a discussion with them and to share our data with them and to tell them that some of these genes that we have uh identified, some of these mutations that we have identified, but we want to put them into their cocktail, yeah, so that we can then use it for a larger study. And they were excited to do that, they are willing to do that. Yeah, they the the the the question is funding. We are looking for grant, but at the same time, like I told you, Induna is a very uh research-friendly. They are immediately considering giving us um support to be able to run the first 20 patients, and um but we actually want to extend beyond that, but we will take that advantage and see what we can do with what they are offering us.

SPEAKER_02 3:02

Yeah, and what does it mean for the Nigerian patient? Yeah, what it is.

SPEAKER_00 3:05

What it means for the general patient is that you know, you like just like I give you an example with acute myelone leukemia, in Europe right now, it's integrated into the routine edge care. Yeah, and uh genome sequences are done on almost every patient with acute uh myelone leukemia. And because they already have a lively, they already have a cocktail that is flat with the common mutations in their environment. The the the pharmaceutical company can then immediately produce a targeted, precise, what we call uh uh uh precision mixing for the patient care. And like I said, in Gamini right now, close to 85% success rate is what they have. What it means for the is that we'll be able to produce a similar coffee from our own patients.

SPEAKER_01 3:53

Yeah.

SPEAKER_00 3:54

So that when our patient comes in, we can immediately run uh new genome sequencing on those patients with genes that we have already identified over time, yeah, that are flagged in those patients, and that we know that they have uh therapeutic promises so that they can then and we can then partner with the pharmacological industry that within a very short time, when those panel of genes are discovered in our patient, they can then customize a targeted therapy for the care.

SPEAKER_01 4:29

Yeah.

SPEAKER_00 4:29

What means that there is going to be a better treatment for cancer in Africa. That's what that's the implication.

SPEAKER_02 4:36

And that's amazing because you also mentioned that some of the examples in AML, for example, the immunotherapies in cancer that are being used can cost over 2.5 million naira per week. And these are even immunotherapy products that were studied on a vastly Caucasian or Western audience. So this not only does it make the data more um accurate to Africans and the treatments more successful, yeah. I'm curious to hear your thoughts on how do we then bridge that gap of the cost of the treatment.

SPEAKER_00 5:07

Well, we need to, just like we have been discussing, we need an active partnership with industries to be able to customize some of this innovation into our peculiar population. Uh, immunotherapy, for example, most of those therapies uh, most of those antibodies that were used to develop those medications were produced in Caucasian. Our antibody response in Africa is a little bit different because it's well challenged. We are in the tropics, yeah, where there are infections all the time. So we don't we do not have that simple immune responses like they have in Caucasian environments. So most of those immunotherapies that you are custom that were designed with that population are really not working for our patients. Yeah, and I don't I actually do not expect them to work to work. Some people have some two people are lucky, but majority of people are not responding to therapy in African Asian population, uh accessory population.

SPEAKER_01 6:06

Yeah, yeah.

SPEAKER_00 6:06

The implication is that we need to customize our own immunotherapy drug for specific cancer, yeah, generated from our uh our population. Yeah, and uh that is where what should be our focus. That is cost intensive, that is also facility intensive. It is only possible with private, uh public-private partnership, collaboration between the industry, the government, and especially the university and the research center, yeah, that are going to initiate the foundation and produce the initial data for the purpose of this pharmacogenomics that we are talking about.

SPEAKER_02 6:43

Yeah, yeah. And you mentioned partnerships. I there's a the landscape of our pharmaceutical industry is very interesting because maybe between 70 to 80 percent, perhaps even higher, of the drugs are imported. Yeah, and we don't even create for the vast majority our own APIs. Now, I want to understand from your perspective, because you're more upstream in the development of pharmaceuticals, what do you need to see downstream, especially from the industry, to really make this possible?

SPEAKER_00 7:17

Again, partnership generating the basic data that is you that is needed to customize and to develop those country, uh those those cocktails of uh of medications. Now we have in S-System, and I'm not just saying this to praise the uh pharmacy society of Nigeria. In S system, uh pharmacy is one area that that has been underutilized, despite the level of knowledge and intelligence that they are.

SPEAKER_01 7:47

Yeah, yeah.

SPEAKER_00 7:48

And I believe that a a good number of pharmacies are now moving into biotechnology, they're now moving to research. Okay, and that is good for Nigeria. Yeah, because then they will be able to make there are so many possibilities for drug development when we have the basic genomic data.

SPEAKER_01 8:08

Yeah.

SPEAKER_00 8:09

What the level where we are now that we should be aggressive about is generating this data.

SPEAKER_01 8:14

Yeah, yeah.

SPEAKER_00 8:15

We do not even have the normal genetic expression of our normal healthy society. Uh in the Center for Genomics, we are currently putting together a team of collaboration with uh North America to be able to do the uh a 10,000 genome sequencing for Africa. Yeah, and this is just targeting population genomics. If we have an understanding of how our gene, our genome behave under normal circumstances, it will be easier to do intervention when there are deviation from base normal. Yeah, you have a baseline data. You have a baseline data. And those baseline data are essential, and that is why most people are missing it because the interest is on pathology. Yeah, the the interest is on diseases, how do we solve the problem? Yeah, but for you to be able to address genomic problems, you must have an understanding of normal genome providing of that population. You must also be able to understand how siblings relate with the deviation that you are seeing in the patients for you to be able to give an intervention to those patients. Yeah, so for personalized mind, we need precision diagnosis. You need data, there is no doubt about it, and generating that data is where the challenges are because it's expensive, it's uh cost intensive, yeah, it also requires special skill. It requires special skill. Yeah, but I want to believe with the partnership, the collaboration that is ongoing with our center and so many other people in the world. We are so happy in the center because what we are talking here, what we are discussing here, we can do everything in the center, so we don't need to take it outside anywhere in the world.

SPEAKER_01 10:01

Yeah, yeah.

SPEAKER_00 10:01

We can do the expression, we can do the sequencing. What we are doing in the center, the setup that we have is actually what you will see in any developed country. Yeah, yeah. And we also have a lot of graduate students that are very inquisitive. In fact, I am amazed at the inquisitiveness of the of the Gen C generation because all I hear about them is the negative thing all the time. But these are a fantastic generation. All you need to do is to give them the opportunity, all you need to give them is to give them challenges. They love digital interface, they love full. So make use of all the law. Yeah, and that's what we are doing in the center. Yeah, we are doing a lot of uh data mining, data acquisition, like some of the things I've just presented, where we mine image data for from North America. These are well classified image data, yeah, even though we have to pay to be able to access those data. Now we have enough data to be able to teach the machine learning and use artificial intelligence to be able to add uh to be able to detect variation in those lives.

SPEAKER_01 11:07

Yeah.

SPEAKER_00 11:07

And then we then need to customize them with our own local samples, and that is where the challenge is.

SPEAKER_01 11:13

Yeah, yeah.

SPEAKER_00 11:13

Because to be able to get patient sample requires a lot of collaboration, the lack of trust among the edge professionals, yeah, yeah. They are all kind of funny, funny things that is not there in America, that is not there in North America. But I think we will we will we will overcome at the end of the day.

SPEAKER_01 11:33

Yeah, yeah. Yeah.

SPEAKER_00 11:34

The AI uh machine learning post-tate cancer project that we are doing is together with with with pathologists, with urologists, with physicians, and we have an engineer in the team. Yeah, we have mathematicians in the team. We have somebody that all alive, she's been doing artificial intelligence. My job as a director is not to put to coordinate the effort. And uh and we are having an amazing result.

SPEAKER_02 11:58

Yeah. And during your talk, just to touch on this AI point, you said something very exciting. You said that through cloud-based pathology and machine learning assisted tools, that your team has been able to look at. Um, I think it was in the prostate cancer study, a prostate cancer slide across people in Canada, people in Nigeria, even people in Kenya. And with all this new technology, you're able to do all of that in real time and work across borders. Could this be, in your opinion, could this be the pathway to expand our local capabilities by leveraging learnings from the global environment because we're able to work like that with technology in real time, given we're in a resource-limited setting, could this help us progress our capabilities? Yeah, you know.

SPEAKER_00 12:44

You see, when we talk about resource-limited society, sometimes we exaggerate it. Because some of the things we are talking about here is not so intensive. If you are talking about telepathology, for example, what you need is a good server and a nice computer. You don't need cheaper because you don't need 100 microscopes, you need a good microscope.

SPEAKER_01 13:09

Yeah.

SPEAKER_00 13:09

And if you have a super resolution microscope that is compliance with what they have in other parts of the world, you can network it with other parts of the world. And the advantage then is that it makes the work of the local uh physicians and the pathologists here easy.

SPEAKER_01 13:26

Yeah.

SPEAKER_00 13:26

Because while you are looking at the slide, other people in different parts of the world are also looking at the same slide.

SPEAKER_01 13:32

Yeah, yeah.

SPEAKER_00 13:32

And you are able to synchronize your decision on that. So it's not just one person's decision. Yeah. So the woman error is almost eliminated. Because if you are looking at a pathological slide, like a nationese slide, somewhere in uh where I interface, for example, in loot, and you have the slide in your microscope is connected to your computer, and it's a there is a there is a uh telepathology interface, and somebody is looking at the same not in North America. Most of the time, what they do is that they have the pathology rule, yeah. Where you have pathologists coming in and out, about five of them at a time, and the the the the slide is projected. Yeah, everybody have it in front of them. You also have it at your hand, yeah. And then you you you conclude on diagnosis. It is it is a more precise diagnosis. Yeah, and you know what we are beginning to notice from that effort is that some of the single cells that we do not see as important because most of the time, when you are when you are looking at um solid tumor or liquid tumor, for example, most of the time, if you are looking at a emerald slide, for example, you are just looking at the lymphocytes, you are looking at the shape of those lymphocytes, but there are some fragmented slides that I mean cells that were not of interest to us before. Yeah, but with the power of AI, where you have an algorithm with multiple imaging, AI is able to identify that these particles are only available in this cluster of patients, it's not available in NOMA, yeah, which you can never recognize with just eye imaging system, yeah. And that is the advantage of what you are talking about. So it's not big equipment per se. Yeah, yeah, it's not big equipment per se. But you know, I must say that probably one thing that is going to be a challenge is that in this part of the world you will see you will personalize our practices. Some people may feel that you are enclosing in the area of speciality. Meanwhile, it is giving them an opportunity to do the work better, yeah, yeah. And I think uh just like uh one of the panelists says, we need we all need to work together to reset our thinking. Yeah, our thinking, we need to reset our thinking. We must get rid of selfishness, we must get rid of benefit first, and let the humanity come before all that.

SPEAKER_01 16:00

Yeah, yeah.

SPEAKER_00 16:01

Money will come, recognition will come, yeah, but humanity first, how do we impact our whole society? Yeah, now if they have 85% success rate in the treatment of AML in in uh Germany, for example, and it's still several percent in Africa, in Nigeria, that is a bad news. Yeah, and we should not be comfortable with that. Yeah, so whatever it takes for us to collaborate, whatever is it takes for us to partner, especially with current innovation and technology that is going on, we should take advantage of it.

SPEAKER_02 16:31

Yeah, perfect. Thank you so much, Professor. This was so illuminating. Again, your keynote speech. I really hope they recorded it so that we can put it up everywhere. But very, very insightful. Really appreciate it. Thank you. Thank you. Thank you. Bye.