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New Enko Board Member Noor Shaker on AI’s Promise in Ag

March 31, 2022
New Enko Board Member Noor Shaker on AI’s promise in Ag
By Jacqueline Heard, CEO and founder
 
It’s an honor to welcome AI expert Noor Shaker as the newest member of Enko’s Board of Directors. In a career spanning academia and industry, Noor has applied AI across disciplines ranging from games to drug discovery. She is Senior Vice President & General Manager at X-Chem, which acquired her startup Glamorous AI last year.
 
While new to the agricultural space, Noor has spent years working with artificial intelligence for drug discovery. We recently sat down to talk about the promise of AI across industries and what intrigues her about its potential in ag. Below is a condensed and edited version of our conversation. 
 
You’ve focused on applications of AI across many different industries. Tell me a bit more about your career.
 
After starting out as a computer scientist and earning a Master’s degree in AI, I was lucky to get into one of the best centers in Europe that focuses on AI in games, at IT University of Copenhagen. I stayed in academia for quite a while—through a PhD and postdoc—until becoming an Assistant Professor in AI and machine learning. It was a fun and productive journey!
 
Around that time, my mother passed away from lung cancer. That changed everything. I started thinking about my impact as a researcher, and ultimately decided to move into industry so I could focus on applying my research to have a broader impact and reach more people. This led me to drug discovery: using AI to improve the discovery of new medicines. 
 
What did you find most exciting about making the leap from academia to industry?
 
I made the switch for two reasons. First, the pace of progress is much faster in industry. Second is the multidisciplinary nature of industry. As researchers, we tend to focus on one area and dive deep. To build something truly innovative in industry, you have to work across different disciplines and apply research in several domains.
 
This is what intrigues me about Enko – the opportunity to apply something that I’ve spent a long time learning about to a totally new area. I’d been familiar with agricultural applications of AI in genomics, but less so with chemicals. It’s exciting to contribute to a new paradigm in how we apply AI.
 
We often talk about parallels between drug discovery and crop protection. What are some of the differences you’ve observed so far? 
 
The human drug discovery and testing process is very well established. In ag, it seems like there are fewer well defined paradigms and regulations. For example, consumers don’t always know what their food is treated with. What chemicals were tested on it? Are they safe to consume? These questions aren’t really asked about human therapeutics. Drugs have to be clearly labeled and well tested, with known side effects.
 
In ag, I expect a huge shift around transparency and safety profiles. I like that Enko is thinking so early in the discovery process not just about how a product will work on a specific crop, but also its safety profile for humans and the environment. Tools like DNA-encoded libraries (DEL) will help us build these safer, more sustainable products. Enko is on the right path to deliver that innovation.
 
You noted in your WIRED Health address that there are 10^60 drug-like chemicals available for exploration – does that same math apply to the agricultural space? If not, is it very different?
 
It’s likely even larger in ag. The 10^60 drug-like chemicals are the ones humans could take without negative side effects. In ag, we can use other chemicals that humans don’t directly consume (ones that we spray but later wash away).
 
This larger chemical space is exciting, and it sheds light on the importance of AI. In drug discovery, we use AI because we can’t enumerate the applicable chemicals. The chemical space is hard—maybe impossible—to search and navigate without it. You need to bias it toward those that will work for specific applications. That’s even more true in ag.
 
When you think broadly about the potential of AI and ML, what does the future look like?
 
I see the next few years as transformative. In five to ten years, we’ll see what we’re working on now as ancient history.
 
I’m most excited about AI’s potential to augment human abilities. We know that our approaches to problem solving are limited. AI can help us think differently, and more broadly. Beyond just optimizing how quickly or efficiently we work, this creative aspect of AI fascinates me. 
 
That applies to ag: DEL provides a larger, more diverse chemical space to explore and helps us broaden our approach. Can we increase this chemical space even more? Bring a chemistry to market that no one thought to test before? AI can help us do that.