Transforming the way we do clinical trials with data science and AI

写的:

蕾妮Iacona

Vice President of Biometrics, 肿瘤学 R&D

费萨尔汗

Head of AI and Analytics, Data Science and AI, R&D

Randomised clinical trials are currently the method of choice for assessing a potential medicine, before it can be approved for doctors to prescribe. However, published data shows they have become more expensive and complex over time. 事实上, clinical trials currently account for 60 percent of the cost and 70 percent of the time it takes to bring a potential new drug to market.1

Each delay in a clinical trial could impact our ability to get potential new medicines in front of regulators and ultimately to the patients who need them.

That is why we are investing in the application of data science and Artificial Intelligence (AI) to help us recruit for and design better clinical trials, as well as analyse and interpret the huge quantities of data in our trials and beyond.

在本期播客中2, alongside our former colleague James Matcham, we discuss how we apply data science and AI to clinical trials; for example, to help us ask the right scientific questions and learn more about how people on the clinical trials are responding to the potential medicine.



数据科学 and AI careers at AstraZeneca

At AstraZeneca, we’re bringing the right people together (e.g. 数据科学家, bioinformaticians, data engineers and machine learning experts) to ensure we are collecting, organising and using the right data, 以最好的方式.

We take data seriously – the speed and scale of investment behind what we’re doing shows the importance we place on data science and AI, and the huge ambition that we have to take it to the next level.

Learn more and search open positions at: careers.澳门葡京网赌游戏.com/data-science-and-ai


参考文献。

1. Clinical Development Success Rates, 2006-2015. BIO, BioMed tracker, Amplion, 2016

2. Music from http://filmmusic.io, "Wallpaper" by Kevin MacLeod (http://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)


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