The Root Of The Science Podcast
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The Root Of The Science Podcast
EP 158: Dr Okechinyere Achilonu, Biostatistics as the Backbone of Health Research in Africa
What happens when passion meets purpose in the world of medical data? Dr. Okechinyere Achilonu takes us through her journey in the evolving landscape of biostatistics in Africa.
She reveals how this often-overlooked field serves as the backbone of health research across the continent.
Born in Nigeria, Dr Okechi is currently a lecturer and biostatistician at the University of Witwatersrand in South Africa. She also shares the impact of the Sub-Saharan Africa Advanced Consortium for Biostatistics (SACAB) on her career.
Speaking about data and research, have you heard about Jenni AI, a research assistant that can write, cite and edit? Try it for any academic research related work and notice the difference!
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So when I talk about the versatility of the course, you know like who will say that biostatistics is the backbone of health research. So it means that here, say, for example, in health sciences, we have a lot of studies going on and in all those studies you will see biostatisticians, you know, being part of the work. They are like the backbone of all the research happening in health sciences. So if they, those young researchers, are passionate about understanding what is going on in all those field of studies in health sciences, or want to be at the forefront of supporting health or improving health, or they want to, you know, be part of them, you know solving health problems or contributing to data-driven and solution right. So biostatistics, I will tell them that it is the best field of study for them. Hello everyone and welcome back to another episode of the Roots of the Science podcast. Today we are speaking all things medical biostatistics. Now, medical biostatistics is a science of handling database uncertainties in health and medicine. It deals with collecting, analyzing and interpreting health-related data to support decisions in the medical research and practices. It's very important because it helps doctors and researchers understand patterns and differences and the risks in health outcomes using real-world data from patients, treatments and diseases.
Speaker 1:Today, on this episode, I'm very excited because we're joined by Dr Okechi Nyeri Achilonu. She is a biostatistician and a lecturer at the University of Witt-Bartestrand in Johannesburg, south Africa. Dr Okechi holds a PhD in biostatistics and a master's in statistics and actuarial science from the same institution. Her work focuses on applying statistical and machine learning methods to clinical and epidemiological data. She develops analytical frameworks to support predictive and personalized medicine, especially in areas like cancer and kidney. She is also an alumni of the Sub-Saharan Africa Advanced Consortium for Biostatistics, otherwise known as SACAB. We're going to hear more about Dr Okechi's journey, how she got into this field, dr Okechi's journey, how she got into this field, and also we're going to hear more about this consortium, which she is a fellow for. Find out about all of this and so much more.
Speaker 1:Let's go. Good morning, okechi. Welcome to the show. Hey, thank you so much, annie, for having me here. It's been a pleasure for having me here. It's been a pleasure. Yeah, I am so excited to chat to you today and for our listeners to get to know more about you.
Speaker 1:So, first things first, let's take it back to the beginning. For our listeners who are unaware of who you are, could you briefly introduce yourself for our listeners? Okay, my name is Dr Uke Chinyeri Atsholono. I am from Nigeria, currently based here in Johannesburg, south Africa, where I work as a lecturer and also a biostatistician at the University of the Big Otters, south Africa. I teach and mentor students in epidemiology and biostatistics, that is, in the School of Public Health, and I also use, you know, work on research that uses data to answer big questions, you know, such as who is at risk of developing a certain disease, who is at risk of maybe having unfavorable conditions. You know, such as who is at risk of developing a certain disease, who is at risk of maybe having unfavorable conditions you know, such as recurrence or death. It could be parker management and treatment of all those diseases to be improved. So, yeah, I would say what drives me in this field is the power of data to tell a new story that can change lives. You know, like we usually say, like behind every data set, there is a patient, there is a community or there is a health problem to be solved. So that alone keeps me going. That alone keeps me going. It's a passion for me and also a privilege to be in a space or in a field that uses science and data. So, okechi, you painted that wonderful picture of your journey and you can even hear the passion in your various roles. So I want us to go to the beginning.
Speaker 1:Tell me about how you actually got into this field of biostatistics, because I know that you mentioned you did your master's, as well as your PhD, at the same university, wits Waterstrand, otherwise known as Wits University. Yeah, I actually did my master's in the School of Statistics and Natural Science at the University of Victoria before moving to the School of Public Health, vicks University, also to pursue my PhD in biostatistics, and this shift happened because I had an interest in applying statistics in health. So that is where I moved from these points to another point. No, that's beautiful, because I think it's starting to make sense in my head, because I know what statistics is and I'm sure, most of our listeners but the idea of biostatistics maybe people don't fully understand what that is. So, in your journey of pursuing your PhD in biostatistics, can you tell us what's that taught you about the evolving role of biostatistics against the backdrop of Africa's health landscape?
Speaker 1:Okay, so it is an interesting field and for me, I would say that this field has taught me to be adaptive, to be innovative and also to, like you know, open and to change, so that I will not be in my research so I will say, um, that, um, you know why I'm pointing out to an adaptive, innovative and being open to change is because, um, this field, you know, has evolved and is also evolving, such as healthcare sector or medical research. Is evolving Because in the past, we usually use our conventional statistical approach for our data analysis, but in this transformative era, we have migrated into integrating advanced technologies such as artificial intelligence, machine learning, natural language processing and image recognition in our data analysis. And this is so because, like I said, health and care research or medical research, has evolved because the world is moving towards personalized medicine and they no longer capture information about the patients at micro level. They get to have a lot of information from these patients when they are researching on the particular disease or whatever research people are doing. So they get to get information such as the unstructured information, patient age and gender and they also get to get what we call unstructured information and that is like a pathology report and doctor's note, medical images report and doctor's note, you know, medical images, and we also have a semi-structured format of those data, so they also get to capture. I'm sure you've heard about genomic, so all this information are currently captured. About the patient, because of what I said, we are moving towards personalized medicine and that is trying to tell treatments based on patient-specific characteristics. So when we put all this together that is when you hear about big data it's actually real because of the volume or the variety we see in the data. So this is our conventional or traditional statistical approach may not be sufficient to analyze such data sets. That's where we have migrated into, using advanced technology in order to uncover patterns and to analyse the data, integrate all those templates and information and make it definitive and tradition to support medical decision. So if you are not innovative, if you are not open to change, as a biopestician, you will be left behind and then you may not be able. When youlastician, you know you will be left behind and then you may not be able. You know when you have opportunities, you should be able, you know to use those opportunities. So this field has taught me, like I said, to be open to change, to be innovative, you know, and also active. So, thank you, just a quick pause in this episode.
Speaker 1:One thing that Dr Okechi said that really stuck with me is that as researchers, especially in technical fields like biostatistics, one needs to stay open to change and embrace tools that help us evolve. As a PhD researcher myself, I felt that shift too. Myself I felt that shift too, especially in how we write, process data and communicate our work and, honestly, a tool that's helped me adapt is Genie AI, especially in this fast-moving academic world. Now, genie AI isn't your typical writing tool. It's, in fact, especially built specifically for academics and researchers, and I've used it to help me draft and refine papers, generate accurate citations that are linked to Google Scholar, paraphrase complex ideas and brainstorm new ones. When I'm stuck, what I love is that it doesn't replace my voice, rather it supports it. It's like having a quiet research assistant who works with you at the speed of your thoughts. If you are in the middle of your thesis, prepping for submission or juggling multiple papers, like I am, jenny AI can really make a difference. Sign up at jennyai. Now let's get back into today's episode, thank you. Thank you so much. You know that's quite revolutionary about how far reaching this field is and, like you said, we are moving into this age of artificial intelligence and technology and it's pretty exciting that you are at that precipice. You are in that space and people like you who are working in this field are so vital in the way of how we think of health and how policies are also implemented. So it's such a pretty exciting space and particularly, it's also happening not in the west, but it's happening right here, um, in africa, which makes it even more, um, exciting.
Speaker 1:You were selected for the suck up fellowship, which is such a huge milestone. So how did you come across this opportunity? And, um, how was the application process like for you, somebody who is, you know, in this biostatistics field and is interested of pursuing a similar opportunity? Yeah, so that's a good one and it was discussing. So, annie, I will tell you that I didn't know about them prior to coming to the School of Public Health. So all I wanted when I came to the School of Public Health was to get my PhD to be a subject and also to get my PhD. So I was not after any scholarship because I had already planned to set home myself. So I got to know about them.
Speaker 1:One day I was discussing with my proposed supervisor, who also happened to be my supervisor, who also happens to be my supervisor, professor Eustatius Mosenge. He is currently deputy director of SACA and also a professor at the School of Public Health, sylvester University. So I was discussing my proposal for what we call the concept note with him and Professor Chewa Tobias. Tobias Chewa worked by us. Professor Chewa is the current director of SACA, so I was introduced to him and he was encouraging and supportive. He suggested that I can apply for the Glassdoor Smith Client Call with Quality Escape Call and Scholarship on the circuit right, because one of my objectives, you know, fit in very well in one of their goals. So and I was told that the call is a global call and is also competitive. So because of that I ended up not submitting that week. I have to like.
Speaker 1:I went back with my concept and I talked about it like refining it, you know, because I've heard about the competition and also it's a global call. It means that anywhere, wherever you are, you can apply. So I worked on the concept launch to a level that I feel like okay, I think I'm happy to have it in. So I submitted and also I will be honest, I didn't know about the selection criteria, because I'm still new, I don't even know the selection criteria, or because I'm still new, I don't even know the supervisor. I was not, you know, aware of whatever that happened after my submission. And also I will tell you that I totally zero my mind because I've never been funded before. So I don't want to hope on something you know that may not come out. You know well, you know you don't want to just feel bad about it because you're not selected, so like I forgot about it.
Speaker 1:But now one day I had, I had I got an email from one of their members congratulating me that I've been accepted. You know, for the GSK scholarship, yeah, you, I was overjoyed. You know, the most interesting aspect of this is what they listed that they are going to. You know, give to me like the support. You know the site name was Oxum and they said they're going to pay my fees and they gave me a laptop. And they said they were going to pay my fees and they would give me a laptop. They would give me textbooks and they also, you know, give me flight tickets and even train me. You know, like a lot was listed.
Speaker 1:I'll tell you I was not a specialist, I've already saved my money, but looking at that, I would say that I was blessed by SACA and that alone gave me extra energy to work. Within two years, I was able to address all of my objectives. That they say. And when, and like passion is supported by resources, the possibilities are like boundless. So saccharum was a blessing, like I am grateful. Yeah, amazing, what a wonderful story. And, like you said, that passion being supported by resources is so important.
Speaker 1:Um, and especially um organizations like suck up to support, um, up-and-coming researchers in a particular field. Uh, because, I mean, I'm a post-grad as well and you know, you, you it's difficult to think about your research if you feel like your basic needs are not being met. So the fact that you, you're provided all of these amazing things and you did mention that it was over and above what you even expected, so so I want to talk a little bit about that. So what kind of mentorship or training or collaborations did the program expose you that really helped you in terms of honing your skills or just change your perspective overall? Yeah, you know, I mean SACAB, I would say, gave me more than just academic training. Like it gave me a lot, like the foundations and the tools that I needed during my PhD, and also what that is still keeping me on in my research, right.
Speaker 1:So in the first year of my PhD, sacab hosted a machine learning training and you know, here at the School of Public Health at this university, and you know the person they invited, you know someone at the university medical center Utrecht in the Netherlands. So, and this person happened to be one of my supervisors Wow, you know. And also he was let me just put it that way he was also a SAHAP member and he was late professor Rene Edikemans. So late professor Rene Edikemans came. So Professor Rene Edikemans came to South Africa to train us. You know he didn't just come like a normal trainee we get when we want to take up a kind of learning training. It focuses more on the foundations, the tools, the toy data set to do the training. But here he came with his students' research, right. So there we were not just learning the tools, we were seeing what PhD students are doing over there.
Speaker 1:So I learned a lot in that room because it's more like an international standard that he gave us. So per each research, you know we were able to, you know, formulate. He showed us the research questions, he formulated the objectives he was addressing and he also taught us how to, you know, interpret our results. That training alone gave me the foundation and the tools that I needed in all of my objectives that have to do with machine learning. So when I say to you I finished off my objective within two years because of the kind of training I got from them, and I also want to point out the support and also the encouragement I got from my primary supervisor, professor Ispecius Musenge. He also was very supportive Prior to coming to the School of Public Health. I see myself as someone that had a lot of energy when it came to work, but meeting with him I realized that I had a long way to go, because he will push you. He pushes you to a point that the best in you will come out. I am grateful about that.
Speaker 1:And also, saca posted also a conference right, and that conference was very informative, though it was during the COVID, but it was very informative. Like there, I learned a lot. You know what people are doing, the scope of their PhD work and you know the technicality in their work, and I also presented my work. During the presentation I got a lot of feedback. People critic the work and also give you directions and suggestions on what to do. So that a lot helped me. I learned a lot in that conference and that helped me also to compare and shape my work.
Speaker 1:So it's also part of their criteria if you got their scholarship, they will want you to facilitate workshops. They want you to support statistical research at the faculty. Like I will tell you that, um, it was time consuming but it was it right, it was it. And because, like you have to give them like two to three days in a week, you know you go there, then you see people come with their problems, you know, and then you give statistical support. And I will say to you that I learned a lot, you know, on the SATCAP, because if they didn't do that, like a lot of statistical techniques I learned in my own country. It was based on theory and they also go into mathematical statistics and sciences. It was also pure theory, but here under SACAP I saw people. I was able to use those techniques to support statistical you know research. Like we learned a lot.
Speaker 1:We also have, like you know, fellows, you know that are working on different projects. So then we were, you know, able, even if we are not working on the same. We know that you are not alone right on the SACAP, so you have a way of starting back to basics that can then anyone working on their individual project. Sacap gave me a lot. I can think outside the box and a whole lot happened on the SACAP, thank you. Like I can think outside the box, and a whole lot happened on the site, thank you.
Speaker 1:It sounds like it was such a rich fellowship, you know, and it had such practical implementations into your life as a researcher and, I'm sure, even now in your positions as a lecturer when you finished your own research. So I'm so glad that you got to experience this and I'm, and I hope, um, someone who is listening, um, and it's like, wow, I want to, I want, I want to pursue, uh this particular fellowship, even though, like you said, that you were not aware of this. Um, goodness to your supervisor who exposed you to such opportunity. But I hope now we can expose many people and they can look into potentially um pursuing uh something similar like you did. Um, I want us to maybe then change the direction of this conversation a little bit and then start zooming in on of this, zooming out rather and start speaking opinion.
Speaker 1:What are some of the challenges do you think African researchers face working in the space of health data and how can how they're able to navigate it? Or how do institutions like SACAB support young researchers who are coming up to overcome some of these challenges? Okay, that's another good question and also worth discussing, because this is like what we usually face and some of us are irritated because of these challenges. So I will tell you that one big one I would think of is access to data sets, and another point would be incompleteness of data sets. Even if you have the access, you can be incomplete. And also, we should also think of the skills needed to handle. Even if you have access to the data, do you have the skills to analyze it? And we can also think about the limited infrastructure. So these four things are one of our major problems we are facing in Africa as biostatisticians, and I want to say how a consortium like SACAP can step in in all those Like when we talk about access to data, you may have ideas of what you want to do, but you don't have access to those data sets.
Speaker 1:Maybe a consortium like SACAP can venture into conducting primary studies and also housing a repository where people can archive their datasets. So whoever wants to conduct a similar study can have access to those datasets and use it in their analysis. So let me skip to incompleteness and skills. Right, you may have access to data set, like I said, but they may not be complete. You need to compute it and you also need skills to analyze those data sets. So if you don't have those skills, you can't do anything right, especially those advanced statistical techniques like our ML, machine learning or spatial or natural language processing. So for children like Saka can also step in with respect to training people on those skills, I know Saka will also be hosting a machine know towards the end of the year, around October or November. So these are like what is needed, you know, for people to come in, sit down and learn. You know skills and when you have your data set, you cannot be limited. You can be able to analyze it.
Speaker 1:So the last one, like I said, the point that I would be limited is infrastructure. You know, like I experienced this also during my PhD, like when we talk about server or cluster, so housing, like server, cluster, I will be okay, because some of us run analysis right, especially when we do not have high performance computers so you see yourself running analysis for like days. Right For such people like SACAP you know stepping into, you know house and you know server clusters in one of their institutions I would tell you it can help people to gain access and facilitate their work and be able to finish up on time than having um. What I can point out, not that for certain like can help and and by association in africa with respect to the challenges we are facing. Yeah, thank you. Thank you, um.
Speaker 1:You speak on some very important issues and things that I actually didn't think of. Um. I think particularly the idea of resources and access to data, because these are so huge to the crux of your work. You need the data and able to run the analysis and you need you would hopefully need high performance computer because you run such huge data. So it's not something that your typical typical, I don't know um computer or laptop can handle. So these challenges are are actually, uh, very key and I'm glad that you had the support, um, and again, I think it really stresses the importance for this consortium, because what of the people who don't have this? This is also the issue of where it leaves a lot of um african researchers behind um, as some of the other people who are in the space, who are working with or where this is not even an issue, this is, they don't even think of such things. So I'm glad that. Have you had this type of support? And, like you said, to be able to finish your objectives in two years, you had to have all that infrastructure and you had to have all that technical support, because sometimes these are some of the reasons why people take a long time to complete their studies.
Speaker 1:As we start to wrap up, I wanted to ask you, um, for someone who is like a young african scientist and they might not be aware of the potential of this particular field of biostatistics, what would you say to them to say you know what? Come to this field so that they can consider it? Because I'm speaking to myself um, I did stats of like in statistics in second year of my undergrad and I will tell you okay, gee, I was so happy that I left that field, but I mean now, with my work and whatnot, analyzing the data, it all comes back down to that as well. So please speak to a younger me and somebody else who might be in this field. So, thank you very much. That's a great question.
Speaker 1:So I will tell them about the versatility of biostatistics, about the creative opportunities and the foundational skills. So when I talk about the versatility of the course, you know like who will say that biostatistics is the backbone of health and research. So it means that here, say, for example, in health sciences, we have a lot of studies going on and in all those studies you will see bioscientists, you know, being part of the work, like they are like the backbone of all the research happening in health sciences. So if they, those young researchers, are passionate about understanding what is going on in all those field of studies in health sciences or want to be at the forefront of them you know supporting health or improving health, or they want to, you know, be part of them, you know solving health problems or contributing to data-driven solutions, right, so biostatistics, I would tell them that it's the best field of study for them. And also, when I talk about these lucrative opportunities, right, we have here, you know, here in Africa, we are moving towards the data grading solutions and I will tell you that we are not like much in this field, because I remember where I was at home, people usually, you know, focus on time series, econometrics or uh, operational research.
Speaker 1:We didn't have people focusing on buyer statistics. So we are not that much and the buyer statistics is a field that is very replaceable and you can never be jobless. That's one thing I know about this. You can never be jobless, jobs right, and you can even be in one job and establish your own personal private company for statistical support. So you can never be jobless.
Speaker 1:If you come in here and also when I talk about the foundation skills, you will hear people in this transformative era talking about data science, data science, like. Everybody wants to be data scientist, but that foundation, which is based on biostatistics, is lacking, because I have seen people in data science trying to solve problems so when the results are not correct, they can't even query it because they do not understand the foundation. They do not know what the output should look like. So I will tell them that if they want to become like data scientists, they should first get some training in biostatistics or before for a buyer's position first. So I'm glad I'm here. It worked, you know, coming on board because they have a lot to give in Africa. So you will never be jobless. It's very lucrative, you have a lot of opportunities if you are a buyer's position, wow, okay, I think I'm sold'm sold, I'm convinced. It's a pity I've already chosen my field of study, but I hope for someone else.
Speaker 1:Who's listening? Who's listening? Um, they can, they can consider these wonderful um things that you said. Uh, the final question um, like I said, from the beginning we can hear your passion for this field. We can hear how much you enjoy it and how much it's shaped um who you are professionally and I'm also assuming, uh, personally. So I just wanted to ask what excites you about the future of biostatistics, particularly here in Africa. All right, thank you so much, annie. That's a great question.
Speaker 1:So what excites me most about the future of biostatistics in Africa is the growing movement of biostatistics in Africa. You know the momentum we are building in Africa, like we are no longer consumers of the foreign research, we are becoming producers of the like locally data-driven solutions. So I will say or confirm this, because while I was doing my PhD, like I struggled to find research here in Africa done by Africans or bioscientists in Africa. So I ended up like citing a lot of foreign work. But you know like these days I see like a lot of work done in Africa, right by you know Africa, by us as teachers. So I'm kind of impressed and that is what excites me most. So I would say that I have faith, like great faith, in Africa, like the continent we know is very rich when we talk about genetic diversity, and also there is a pressing need to address public health challenges. So this growing movement of higher statistics shows that for me, that the future is promising and we have a lot to do and we can go outside and learn. But I see the momentum. We are really growing and providing our own research. So that is what excites me.
Speaker 1:Thank you, fantastic, exciting times ahead in Africa in this field, and also done by Africans. So I'm pretty excited to have more conversations with other people who are in this field, and also done by Africans. So I'm pretty excited to have more conversations with other people who are in this field of research. Okay, chi, it's been so lovely chatting with you today and hearing about your journey and also the type of work that you do and also the type of work that's also being done by SACAB as well. So thank you for your time and coming to chat with me today. Thank you, ami, it's a pleasure, and to everybody else who is listening, thank you for tuning in to another episode of the Roots of the Science podcast. Until next time, goodbye.
