Unlocking Health Data's Potential: The AI Revolution in Healthcare
In the rapidly evolving landscape of healthcare, the integration of AI is not just an enhancement but a revolution, particularly in the management and utilisation of health data. To explore the transformative power of AI in unlocking the true value of vast health data reserves, Pharma IQ is excited to share the insights of Zhana Kuncheva, Director of bioXcelerate AI. As we delve into this insightful discussion, we invite our readers to consider the broader implications of these advancements in the pharmaceutical and healthcare industries.
How AI Can Be the Key to Unlocking the True Value of Health Data: Insights from Zhana Kuncheva, Director of bioXcelerate AI
Over the past quarter of a century, the volume of personal data collected globally has skyrocketed. Today, more than 30% of this information is generated by the healthcare industry. The UK Biobank is the world’s leading biomedical database, containing genetic and health details from half a million UK volunteers. Since starting in 2006, it has provided researchers worldwide with key insights to support breakthroughs in the diagnosis and treatment of diseases. But, as new sequencing and biomedical technologies emerge, and even more information is generated, the sheer volume of data is beyond anything we’ve seen before.
Currently, the Biobank holds as much as 11 petabytes of - to put this into context, just one petabyte equates to 1 million gigabytes - and this figure is expected to spiral to more than 40 petabytes by 2025.
Having access to accurate data has already resulted in ground-breaking advancements in healthcare which have the potential to positively transform the way we live. On one hand, brands such as Apple and Fitbit are empowering users to track and manage their fitness levels through wearable devices that feature state-of-the-art data technology, thus encouraging healthier lifestyles. On the other hand, data and health records are used to identify emerging population patterns, so government bodies can implement strategic plans that enhance the health and wellbeing of communities. During the pandemic, for example, data from the UK Biobank helped the government to better understand how lifestyle and inherited factors impacted the way patients were affected by COVID-19.
The list of ways health data can provide value is almost endless, and we are only just beginning to realise the positive advancements in healthcare that will soon be achievable thanks to harnessing the potential value of this data.
Advancements in machine learning and computational technologies have been successfully analysing big data for a decade now, but the rapidly growing volume of data, combined with the multi-layered complexity of data types, has already started challenging some of the classical approaches. Due to methodological and computational restrictions, scientists and researchers have still not unlocked all the potential value of collected data, but are starting to glimpse some of the possibilities.
In the past few years, however, AI-inspired tools have come to the forefront, allowing vast swathes of data to be processed far more quickly and with high levels of accuracy. These new AI tools are already having a fundamental impact on the pace of drug discovery and development. For example, AlphaFold is now regularly used to accurately predict the 3D models of protein structure, dramatically reducing the time for molecular design. By embedding similar advanced machine-learning algorithms, medical researchers can sieve through data banks to reveal biochemical processes linked to the disease causal pathway, providing the information they need to find effective drug targets to cure diseases and alleviate symptoms.
Our own tool, PleioGraph, speeds up data analysis by 100 times, saving time and resources by efficiently identifying genes and proteins as candidate drug targets. It also provides precise insights into disease causal pathways, improving understanding of complex biochemical mechanisms. By using advanced statistical analysis and cutting-edge machine learning, we’ve been able to reduce the risk of false leads and costly errors and increase the chance of successful clinical trials.
As well as accelerating the drug discovery process, AI can vastly improve the quality of patient care by producing comprehensive early diagnostic tools, reducing diagnosis times that can take several years, and providing a more in-depth analysis of drug and treatment performance. All of these factors come together to better inform future decisions. This will bring us one step closer to a wide-spread precision medicine approach where patients benefit from individualised treatment plans which tailor their healthcare to their unique genetic needs. In addition, the healthcare system will also benefit from better risk prediction, allowing a more focused and effective approach to preventative medicine.
It is important to note however, that achieving these positive outcomes will rely heavily on a combination of complete, accurate data and fast, precise, and interpretable AI-tools that build the trust between clinicians, patients, and AI-driven decisions. And with our growing, and aging, population bringing disease diagnoses to an all-time high, this solution is needed now more than ever.
Data can be incredibly powerful but, without the ability to analyse it, it’s essentially just numbers. In allowing us to dissect large quantities of data and really put it to good use, AI-inspired tools are already showing promising results in the field of healthcare. While we already have a glimpse of the true value held within the treasure trove of health data we’ve collected over the years, harnessing the full potential of these predictive approaches can still do much more to support a well-prepared government, highly skilled and supported medical staff, and a healthier society.
Exploring Further: Additional Insights
bioXcelerate AI is a division of Optima Partners. Pharma IQ recently interviewed the Managing Director of Optima Partners to find out more about their research with Biogen and the University of Edinburgh on how AI has the power to transform disease prediction.
Zhana's insights offer a glimpse into the potential future of drug discovery and development shaped by the application of AI in healthcare. For those interested in exploring this topic further, we recommend downloading our Pharma IQ White Paper on ‘Maximising ROI in Drug Discovery: Practical AI Applications and Strategies,” which delves into how AI technologies are enhancing return on investment in pharmaceutical research.
Maximising Drug Discovery ROI with AI White Paper:
Pharma IQ Interview with Chris Foley, Managing Director, Optima Partners
Join Us to Learn More
Eager to dive deeper and learn how to overcome integration challenges from real-world case studies?
Join industry leaders and experts at the AI Pharma & Healthcare Event, where you can gain firsthand insights into successful AI integration strategies. This is your opportunity to learn from the successes and challenges faced by others and to network with professionals who are at the forefront of AI technology in the pharmaceutical industry.
📅Event Details
Event: AI Pharma & Healthcare Summit
Dates: 24-26 September 2024
Location: Amsterdam Marriott Hotel
Event Website: AI Pharma & Healthcare Summit