AI for Good: Merging biology and AI – the future of health care

We are facing a crossroads in health care. With an aging population and globalization facilitating the spread of disease, significant challenges have emerged. However, technologies such as artificial intelligence (AI) and biological models are providing more answers.

By combining the complex elements of human biology with the computational power of AI, we can pave a path to the future of medicine. We can build a healthier world with quicker, low­er-cost drug discovery and development that leads to more effective treatment. AI can also help us prevent pandemic outbreaks.

A ’backtobiology’ approach

In order to build the foundation for a new para­digm of treatment, we must use both the robust­ness of biological models and the cutting-edge innovation of emerging AI technologies. Medicine must take a ’back to biology’ approach to address the current medical landscape, par­ticularly in drug discovery.

The current process of drug dis­covery needs to be more efficient, and the drug discovery industry overall is an industry long overdue for disruption. Under the traditional pharma process, it takes around $2+ billion and 10–15 years to develop a drug. We need a more sustainable solution to drug development that involves higher success rates.

Merging biology and AI can offer a new approach to drug discovery and development that can reduce costs and development time. Biological insight delivers preci­sion, but AI provides speed and eliminates uncertainty by analysing trillions of data points per tissue sample in a matter of days; some­thing impossible for humans alone.

By comparing massive amounts of data, including individual patient health data to the greater popula­tion health data, we can develop prescriptive analytics that can determine what treatments will work best for each patient, and deliver on the promise of precision medicine. Applied in clinical development, this can lead to improved drug trials and increased success rates. Additionally, using analytics can also reduce development costs and bring new-in-class therapeutics to the patients in a time-ef­ficient manner.















Preventing pandemic outbreaks with AI

In addition to AI proving new treatments for today’s most insidious diseases, AI can predict, model, and slow the spread of disease in a pan­demic outbreak. Throughout history, pandemic outbreaks have devastated populations from the bubonic plague to the 1918 Spanish flu, and more recently, Bird flu, Ebola and SARS.

These modern outbreaks, spurred on by glo­balization, trade and travel, have led to the increased spread of viruses more than at any point in history. Treating outbreaks at this scale and speed is difficult given the unpredictable nature of viruses, which include natural muta­tions and resistance to existing medicines.

When a pandemic outbreak occurs, time is of the essence — and this is where AI has the potential to give us the tools we need to prevent the next global event. AI approaches, such as Bayesian analytics, have been used in health care, finance, and commerce, streamlining deci­sion-making for the optimal endpoint.

RELATED: AI for Good Global Summit

The first line of defense that AI tools will give us is the ability to predict and model potential outbreaks. By monitoring patient populations and medical data, AI can recognize patterns of pharmaceutical intervention to treat historical symptoms. These patterns could point to at-risk locations and also help identify the migration of a pending outbreak. This would allow agencies, such as the Centers for Disease Control and Prevention (CDC) to investigate and monitor those areas historically and in real-time to model the cause and effect relationships that could mitigate the progression of a pandemic, as well as its natural path within the population.

The second line of defense will be to utilize AI in the same way it’s used now by global trade companies to manage their shipping routes. The same approach that helps you get an ama­zon package from China efficiently can be used to forecast an outbreak.

AI can build causative relationships between travel data and population medical reports to help map out and predict the spread of a disease. Using this data, AI could prescribe ways to alter travel routes to help contain or slow the spread of a disease. At the same time, AI can help government agencies like the Defense Advanced Research Projects Agency’s (DARPA) Pandemic Prevention Platform (P3) to plan more rapid and efficient responses. With limited resources and time, these agencies need to be primed to deploy the right supplies and person­nel to the optimal locations at precisely the right time.

The use of AI to rapidly learn from large data­sets has a wide range of applications from drug development to fighting future pandemics. Like any technology or tool, once we understand its potential and multitude of applications, it can be used in great effect to benefit our world and save lives.

RELATED: AI for Good: How advanced crop intelligence can help solve food production challenges

By Niven R. Narain

Co-Founder, President and CEO, BERG




Want more thought leadership on the opportunities and risks of AI?

Go in-depth with our special edition of ITU News Magazine.

%d bloggers like this: