"AI gives scientists superpowers — but also super responsibilities"

We hear a lot about “omics” nowadays in health research. What are they and why are they so important?

OREN TZFADIA: Instead of studying one gene or pathway at a time, we look at the entire organism. This approach is called omics. A gene is a piece of DNA that contains the information to be translated to RNA and then to make a specific protein. These proteins control and regulate how the body works. When a gene is altered or mutated, it can have an effect on how a protein functions. Genetic testing helps identify whether certain genes are responsible for disease development and treatment outcome. 

Advances in technology now allow us to sequence all genes (genome), monitor RNA levels (transcriptome) and analyze all proteins (proteome). Think of it as moving from listening to a single musician to hearing a whole orchestra. This gives us a complete picture of the biological processes at play. 

Omics has become a buzzword because we finally have the technology and analytical tools to generate and analyze massive datasets. AI and computing power allow advancement to conduct multi-layered studies, which is revolutionizing biology research. It gives us the ability to make discoveries that weren’t possible before.

And how do you use AI and new technologies for this?

OREN: We’re feeding all the information we have – published papers, experimental data and other relevant data - into an AI model. We think AI might help find the connections between drug-resistant strains and the antibiotics that we can’t see directly. Maybe it can help us understand why drug resistance occurs.

AI also helps us work much faster and get results more quickly. For instance, determining whether a sample is drug-resistant usually takes six or seven weeks, because we have to grow the mycobacteria. With AI, we can take continuous pictures of the bacteria under a microscope. The model analyzes the growth patterns, and after only a few hours, resistance can already be detected - long before it’s visible to the naked eye. That’s a great example of how AI technology can boost our research.

Of course, it is always essential to keep humans in the loop to verify AI’s output. We need to remember: AI gives us superpowers, but it also gives us super responsibilities.

Do you see limitations of these new technologies?

OREN: Yes, omics and AI aren’t magic bullets, they have to be combined with strong local partnerships in the Global South. They can help us ask better questions, find smarter solutions and bring precision medicine to where it’s needed most. Technology alone won’t fix weak systems - for example, in low- and middle-income countries. The real innovation is pairing new tools with equity, local ownership and sustainable integration.

If technology is parachuted into or imposed on local systems, it’s like giving someone a Ferrari without fuel - what can they do with it? That’s why we co-develop bioinformatics training and data platforms with local scientists, so they can independently use omics and guide their own public health policies.