Anne Powell

Meet the team: Anne Powell, DART Project Manager

October 22, 2021

Anne is the DART Project Manager and has over 15 years of experience in managing projects supporting research systems in Africa, Asia and Latin America, specifically through university consortia.

What is your job and what does it involved?

I’m the DART Project Manager. DART is an AI (Artificial Intelligence) project working to build algorithms that will more accurately predict lung cancer with the aim of early diagnosis, better treatment, greater survival rates. 

What I do as project manager is co-ordinate the work of scientists, academics, clinicians, and industrial partners. A lot of my time is therefore spent in organising meetings, making sure that what needs to be done is done.

I’m also responsible for the budget of the project which involves a fair amount of work with the finance team at Oxford University as well as with the work packages on what they can spend. 

If you want to know what a typical week may look like for me, this week I’ve:

  • attended the quarterly review meeting for the project 
  • created slides for a presentation and made sure each work package is represented 
  • revised our project protocol 
  • been preparing process documents forecasting regarding finance and the spending
  • and having legal discussions around a sub-project agreement. 

What do you enjoy most about working with NCIMI? 

One of the things I enjoy the most is the variety. 

It’s brilliant to be working on a different area from my previous experience, where we’re laying the groundwork for this exciting new project. 

I get to speak to so many different people during my day, all working in varied jobs with different expertise. I really enjoy working with the NCIMI team, who all have different strengths and all contribute to the team achievements. It’s a great project to be involved with, where everyone is going in the same direction and where we can all count on each other’s strengths. 

I absolutely love the huge potential that DART has. I think it’s fantastic that we might be able to treat people more rapidly, more effectively and deal with a lot of concerns that people have about lung cancer through developing machine learning. 

This will take away some pressure and reduce the number of invasive procedures needed if we can get rid of biopsies by improving the reading of screening – it will be amazing. So, it’s a great project to be working on, with great people. 

What are the greatest challenges within your role?

I work with very, very busy people, many of whom are also balancing clinical roles.
We’re working with lung health which means we’ve been very affected by COVID-19 and the effect this has had on the risk of respiratory diseases. 

Setting up meetings with people can be challenging, as can navigating my way through systems, and working with both Oxford University and the NHS. They’re very large systems that have very good systems in place but you have to know what you’re doing. 

What are the key issues for healthcare and AI right now, and in the future? 

The main issue I’m seeing is that for the healthcare practitioners to actually make use of AI they’re going to need to have the time to do it, the interest to learn new systems, and for the systems to be sufficiently user friendly. So, it feels to me that what we need to do is put together, AI algorithms and software in such a way that it’s accessible to the practitioners. And I think at the moment we’ve got a little bit of a divide that we need to cross between great AI algorithms or the data that’s there, and the practitioners who are very busy people, and don’t necessarily have time to learn new systems even though, ultimately, these are going to save time.

What do you think the future of healthcare AI is? 

I think it’s going to become more and more accurate.

I’m seeing that they’re getting incredibly detailed images, that even though I’m not a radiologist, I can tell it often fantastic images, so it’s getting more and more accurate. 

I’m intrigued that a lot of radiologists are very happy that machines can read the images better than they can. So, I think that’s going to be huge for the future of healthcare, but also it means its clinicians and practitioners are freed up to have the more important face to face time with the patients. AI will become more accurate and it will alter the way that people are able to spend their time.

What do you like to do in your spare time? 

I have two cats, Mickey and Maisie who are adorable and usually keep me company while working from home. I love being outdoors and gardening, and I do a lot of walking. I read a fair amount and I love needlework.
I’ve been involved with a couple of charities including one where we’re trying to make a difference to local communities in Tanzania helping to build skills and employment for young people.