Scents play a central role in nature, as olfactory interactions are the language of life. In a new research project of the UvA Molecular and Materials Design Technology hub, scientists will use machine learning to predict what types of olfactory molecules interact with insect olfactory receptors. This information is important to develop safe-by-design molecules that do not interfere with insect olfaction. Scents play a central role in the lives of living beings, from locating food and mates to sensing and avoiding danger. Insects use many different types of scents, such as sex, trail, alarm and aggregation pheromones, as well as plant odors to locate their host plants.

Advances in neural sensing technology are making it possible to observe the olfactory process in great detail. In this paper, we conceptualize smell from a Data Science and AI perspective, that relates the properties of odorants to how they are sensed and analyzed in the olfactory system from the nose to the brain. Drawing distinctions to color vision, we argue that smell presents unique measurement challenges, including the complexity of stimuli, the high dimensionality of the sensory apparatus, as well as what constitutes ground truth. In the face of these challenges, we argue for the centrality of odorant-receptor interactions in developing a theory of olfaction. Such a theory is likely to find widespread industrial applications, and enhance our understanding of smell, and in the longer-term, how it relates to other senses and language. As an initial use case of the data, we present results using machine learning-based classification of neural responses to odors as they are recorded in the mouse olfactory bulb with calcium imaging.

Did you ever try to measure a smell?

But now scientists and entrepreneurs are redoubling their efforts to recreate the sense of smell in compact devices that detect and analyze odors similar to the way cameras now recognize our faces and microphones our words. In pursuit of these high-tech devices–which could use odors to detect disease like cancer or Covid-19, locate hidden explosives or decipher our moods and behaviors--some companies are leveraging advances in synthetic biology and genetic engineering. Others are harnessing advances in artificial intelligence. "It's absolutely a growing field," says Andreas Mershin, an odor-sensor researcher at the Massachusetts Institute of Technology. He calls the field an "unexplored goldmine."

A tea bag is an extraordinary thing. Each small sachet contains a mix of leaves from different producers and different places. Hundreds of factors can affect the flavour of each leaf, from the amount of sunlight and rainfall to the type of soil it was grown in, how it was plucked and how it was dried. Yet when you drink a cup of your favourite brew, you expect it to taste exactly like the last one. Tetley, a British teamaker, boasts that its basic blend has had the same distinctive taste since the company was set up in 1822.

Times have changed, so you no longer have to endure an orifices check, a needle in your vein, and a week of waiting for your blood test results. Instead, the nurse welcomes you with, "The doctor will sniff you now," and takes you into an airtight chamber wired up to a massive computer. As you rest, the volatile molecules you exhale or emit from your body and skin slowly drift into the complex artificial intelligence apparatus, colloquially known as Deep Nose. Behind the scene, Deep Nose's massive electronic brain starts crunching through the molecules, comparing them to its enormous olfactory database. Once it's got a noseful, the AI matches your odors to the medical conditions that cause them and generates a printout of your health.

You might say the brain is our most photogenic organ. We are, thanks to modern neuroimaging, living amid an explosion of brain data. Just consider: We can zoom into the brain's connectivity to the most minute, molecular level. We can trace individual cells as well as entire cell populations. We can turn neurons on and off just like a light switch.