London, UK – On 21st May, CIOs from across the UK gathered for the CIONET UK community event, "The Big Transformer". A highlight of the day was a fireside chat with Cindy Hoots, Chief Digital Officer & Chief Information Officer at AstraZeneca, who shared insights into the pharmaceutical giant's transformative journey with AI-driven innovation. The discussion, hosted by Craig Walker, delved into how AstraZeneca is leveraging AI to revolutionise drug discovery, optimise manufacturing, and even improve global healthcare access. Approximately 150 CIOs were in attendance,
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A: AI has truly revolutionised the pharmaceutical industry, particularly in Research and Development. At AstraZeneca, we've integrated AI into our R&D processes, fundamentally reimagining how drugs are developed. Traditionally, drug discovery involved sifting through vast amounts of data, a process that was incredibly time-consuming and resource-intensive. AI has transformed this by rapidly analysing complex datasets and identifying patterns that human researchers might take years to notice. For instance, AI algorithms can predict how drugs will interact with biological targets, allowing us to identify promising candidates much earlier in the pipeline.
One of our most significant achievements involves using AI to simulate molecular behaviour. This capability enables us to quickly refine compounds, optimising them for efficacy and safety even before they reach the lab. This not only accelerates our pace of innovation but also significantly reduces costs, which is a compelling value proposition for any R&D-centric organisation.
Q: Beyond accelerating discovery, how is AI helping your scientists gain a deeper understanding of disease biology?
A: AI empowers our scientists to advance their understanding of disease biology and pinpoint new drivers of diseases we aim to treat, prevent, and potentially, one day, cure. For example, our scientists utilise knowledge graphs—networks of contextualised scientific data such as genes, proteins, diseases, and compounds, along with their inter-relationships. These graphs enable us to make better decisions earlier in the R&D process, reducing both effort and material usage in laboratories. We employ advanced machine learning and AI approaches like GraphML and transformers to gain novel insights into target discovery, biomarker identification, patient stratification, and drug response. This AI-guided approach has already proven beneficial, particularly with our initial disease models focused on drug resistance based on knowledge graphs. We've even enhanced these capabilities with a generative AI interface, allowing scientists to query trusted information in plain language and generate and summarise data easily.
Q: It's clear AI is pivotal in early-stage R&D. How does it then assist in determining the right molecule to create once a disease target is identified?
A: Once a disease target is identified, AI actively assists our scientists in determining which molecule to create. We augment traditional drug design with sophisticated computational methods that predict which molecules to make next and how to produce them efficiently. This approach shortens the optimisation cycles traditionally required, enabling us to advance most of our small molecule chemistry projects and design antibodies more effectively.
Q: Personalised medicine is a significant area of focus. How are AI tools contributing to advancements in this field at AstraZeneca?
A: In personalised medicine, AI tools, validated by human expertise, are opening up new avenues for precision insights. AI plays a pivotal role in various applications, whether it's assessing cough recordings, analysing lung tissue samples, or identifying suitable clinical trial participants. Our data scientists develop machine learning algorithms that blend diverse datasets, including clinical trial and real-world data, to uncover patterns in disease progression and patient responses. These findings are crucial in refining clinical trial designs.
AI-powered tools also enable us to utilise medical imaging as a rich data source, offering profound insights into how individual genetic compositions affect treatment responses. For instance, our experts use AI in tumour image analysis to optimise the accuracy of assessing tumour volumes from CT scans. While this process is currently manual, the AI-driven approach aims to expedite how radiologists inform clinicians about treatment effects on tumours, ultimately guiding better therapeutic decisions.
Q: Beyond R&D, AstraZeneca has earned Lighthouse status for two of its plants from the World Economic Forum, thanks to AI. Can you tell us more about AI's role in your manufacturing processes?
A: Shifting gears to manufacturing, AI truly enhances every facet of our production process. Imagine a facility where AI-driven predictive maintenance ensures every piece of machinery operates at optimal efficiency, or where real-time data analytics minimise waste and improve yield – that's the reality at AstraZeneca. For example, by predicting equipment failures before they occur, we significantly reduce downtime and maintain the continuous flow of production.
“In addition, AI is helping us monitor quality control. By analysing production data in real-time, we maintain stringent quality standards, ensuring that each product meets our high standards before it reaches patients."
Beyond efficiency, our AI initiatives also contribute to sustainability. By optimising resource usage, we're making strides towards our environmental goals, reducing energy consumption and minimising waste. As CIOs, we should always be examining how AI can help us achieve operational excellence while also contributing to the sustainability goals of our organisations.
Q: AstraZeneca is also involved in Quire.AI, an initiative part of the World Economic Forum's EDISON Alliance program. Could you elaborate on this?
A: Quire.AI is a specific initiative we are closely involved in, and it's part of our commitment to improving access to healthcare through digital solutions, particularly in emerging markets. Together with AI-based solutions developer Qure.ai, we have successfully completed 5 million AI-enabled chest X-rays across more than 20 countries in Asia, the Middle East, Africa, and Latin America. This programme is significantly improving lung cancer screening and driving early intervention by using an algorithm and AI-based tool to analyse patient chest X-rays for indications of lung cancer. So far, we have identified lung nodules at high risk for cancer in nearly 50,000 people , who have been referred for further testing and possible diagnosis, potentially leading to earlier intervention and improved outcomes.
"This initiative exemplifies how technology, when paired with strategic partnerships, can create substantial societal impact."
Our journey with Quire.AI underscores the value of aligning technological initiatives with broader social goals. For CIOs looking to venture into emerging markets, the key lesson from our experience is the impactful synergy that can be achieved through collaboration with local governments and stakeholders.
Q: Finally, Cindy, what's your message to fellow CIOs regarding continuous evolution in technology?
A: As leaders in technology, we must embrace constant evolution. Our world is ever-changing, and staying static is not an option. At AstraZeneca, our culture thrives on innovation. We foster an environment where our IT teams are encouraged to explore, experiment, and lead initiatives that push the boundaries of what's possible. This culture of innovation is crucial for maintaining our edge and setting benchmarks in technology leadership. It's about envisioning future needs and preparing the wider business for them. It also means being agile—responding swiftly to emerging trends and integrating new technologies seamlessly into existing systems. For CIOs, the lesson is to value agility and foresight. Cultivate teams that are not afraid to challenge the status quo and are eager to learn and implement new skills. AI is no longer just a tool for IT or data scientists; Gen AI has made AI accessible to the masses. As CIOs, we need to guide our businesses in how best to embrace and leverage such tools for the benefit of every division, every process, and every employee.
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