About You & the Internship
Could you introduce yourself (name, background, area of study or expertise)?
My name is Muhinyia Ndegwa. I hold a bachelor’s and a master’s in computer science with an interest in health data science. Growing up, I dreamed of being a medical doctor. I vividly remember telling my friends I’d be a cardiologist and one day discover a cure for diabetes – a lofty ambition for a kid, perhaps, but it ignited a lifelong fascination with health and medicine. While my academic journey led me to computer science, that initial spark never faded. Now, as a computer scientist specialising in AI, I feel I’m living that long-lost dream, applying my AI skills to impact health service delivery. It’s truly the best of both worlds!
What attracted you to the Health Data Science Black Internship Programme?
The HDRUK Black Internship Programme was far more than a chance to gain experience – it was a chance to become part of a supportive, long-lasting community. When I applied, I was drawn to the fact that the programme doesn’t just end after the placement; it provides mentorship, networking opportunities, and access to an alumni forum that continues to open doors long into the future. Unlike most programmes, HDRUK also guarantees applicants an interview with a host organisation, meaning every candidate gets a fair shot at showcasing their potential.
What made you want to work with the NIHR Innovation Observatory specifically?
While the host organisations for the internship were at the discretion of HDRUK, who matched candidates to suitable partners for interviewing, I can confidently say that if I had been given a direct choice, I would have chosen the NIHR Innovation Observatory without hesitation.
Upon learning about my placement, I discovered that the Innovation Observatory is at the forefront of horizon scanning – an area I didn’t know existed before, but now deeply appreciate. This crucial work plays an essential role in identifying emerging healthcare innovations, providing vital intelligence that helps policymakers and practitioners make data-driven decisions that impact healthcare delivery. The prospect of applying my skills to speed up insights for healthcare decision-making aligned perfectly with my desire to use technology to transform lives and fulfil my long-held passion for contributing to health. It felt like a truly ideal fit.
The Project
Can you describe the project you worked on during your internship?
My project involved building a pipeline tool to support information analysts in classifying, ranking, and extracting data from medical documents. This tool was designed to streamline the laborious process of literature review for horizon scanning.
What was the aim of the project, and why is it important in health data science?
The primary aim of my project was multifaceted: to significantly reduce the workload for information analysts, ensure faster document screening, and accelerate the entire horizon scanning process. In essence, by automating and streamlining these tasks, we pave the way for faster insights, which in turn lead to quicker decisions. In the long run, this translates directly into improving health service delivery and patient outcomes.
This is important in health data science because horizon scanning – the proactive identification of emerging health technologies, treatments, and threats – is a critical but often labour-intensive process. The tool leverages LLMs to make this process more efficient, accurate, and scalable, ensuring that healthcare decision-makers have the most up-to-date information at their fingertips.
What were your main tasks and responsibilities?
One of the most empowering aspects of this internship was the level of ownership I was given. I was responsible for the entire development lifecycle of the project, from conception to deployment. With the fantastic support and guidance of my supervisor, I had the autonomy to determine the direction the project would take, making key architectural and implementation decisions. This meant everything from designing the system architecture to writing the code, testing, and ultimately deploying the solution.
Did you work with any specific tools, datasets, or methods that stood out to you?
Yes – I worked with large language models (LLMs), particularly GPT, and deployed the system on AWS. I also used Docker for containerisation and built the user interface using Streamlit. These tools not only brought the project to life but also gave me hands-on experience with technologies that are highly relevant in data science.
The Experience
What skills or knowledge have you gained from your time here?
From a technical perspective, I sharpened my skills in cloud technologies, containerisation, and building practical AI-driven solutions. One of my key lessons was understanding the value of building a working solution first over endless optimisation – sometimes impact matters more than perfection. Perhaps most importantly, I learned about the horizon scanning process. Before this internship, I didn’t know it existed; now I appreciate how vital it is in preparing health systems to respond to future challenges.
Were there any moments you found particularly challenging, and how did you overcome them?
Indeed, my internship coincided with one of the most difficult periods of my life. Three weeks into the program, I suffered a tremendous blow with the loss of a very dear, close relative. It was truly traumatising, and for a time, clarity completely evaded me. I honestly considered dropping out. However, I soon realised that I needed to keep my mind engaged, to immerse myself in the project as a way of distracting my thoughts. It wasn’t easy, but focusing on the work, pushing through the technical challenges, and channelling my energy into building something meaningful became my coping mechanism. I’m incredibly proud that I managed to see it through.
What was your favourite part of the internship?
There were so many memorable moments:
- Seeing the pipeline run end-to-end for the first time.
- Deploying it successfully and realising it worked in practice.
- Learning new tricks from my supervisor whenever I was stuck.
But the highlight was presenting my work to the entire IO team. The messages of congratulations that followed – “You did all that in just six weeks?!” – were an unforgettable mic-drop moment.
How did your experience match (or differ from) your expectations?
Coming into the internship, I had some apprehension. I worried I might be assigned a purely theoretical or “safe” project, perhaps just to keep me engaged. However, my experience at NIHR Innovation Observatory profoundly exceeded my expectations. The fact that I was entrusted with a real, impactful project that had tangible implications meant everything to me. Making an impact, even in my small way, was my greatest desire, and the IO delivered exactly that. It’s truly inspiring to see how my work can contribute to vital processes like horizon scanning.
Looking Ahead
How has this internship influenced your career aspirations or academic focus?
This internship has significantly broadened my perspective on the possibilities of AI in impacting healthcare. Before, my thinking might have been more focused on training complex models for intricate tasks, like those helping radiologists analyse. While those areas are vital, this experience taught me to recognise the immense value in addressing the “low-hanging fruits” – the immediate, practical applications of AI that can dramatically improve efficiency and decision-making within healthcare systems. This has fundamentally shifted my aspirations towards exploring these diverse and impactful applications of health data science.
What advice would you give to someone considering applying for this programme?
My advice is simple – go for it! Immerse yourself fully, embrace and face every challenge head-on as a valuable learning experience, and enjoy the entire process.
Any words of thanks or reflections you’d like to share about the NIHR Innovation Observatory and your colleagues?
I am profoundly grateful to the entire team at the NIHR Innovation Observatory for making this internship such an impactful experience. Everyone I interacted with brought a positive vibe, which made all the difference. My heartfelt thanks go to my incredible supervisor, Saleh Mohammed, and Karim from the data science team, who guided me expertly through my project and offered invaluable insights and encouragement. A special mention to my mentor, Ross Fairbairn, for his continuous support throughout the internship.
I’m also grateful to the administration team, who ensured the smooth running of my internship – particularly Stephanie Thomas, who patiently addressed my queries and tolerated my unending pestering. Lastly, a big thank you to the team of analysts. Everyone I encountered at IO was fantastic, and together they fostered a truly supportive environment.
I would also like to express my unreserved gratitude to Black Interns Foundation, HDRUK, and NorthFutures, whose combined efforts made this internship possible.
