Pain, Personalised Medicine & the Future of Neuroscience Research

Pain, Personalised Medicine & the Future of Neuroscience Research

Neuroscience is an ever-changing field, moving forward at a rapid pace as new discoveries, tools, and technologies continue to transform our understanding of the brain. The future of the field is as fascinating as it is unknown, full of possibilities that could revolutionise how we treat mental health and neurological conditions. Early career researchers have plenty of opportunities to explore, innovate, and make their mark. So what drives a young neuroscientist’s curiosity about the brain, and how do they see the future of neuroscience evolving with the advancement of AI?

Ameen Alajeely is a 22-year-old PhD student in neuropharmaceutical science at the University of Toronto, Canada. He completed an undergraduate degree in neuroscience before receiving a research grant from the Branch Out Foundation, which supports scientists working on alternative treatments for neurological and psychiatric conditions.

His current research focuses on behavioural modification as a method of treating chronic pain, and we spoke to him about his journey into neuroscience, his thoughts on AI and personalised medicine, and where he sees the future of brain research.

Hi Ameen, can you tell us a bit about your journey into neuroscience? What first inspired you to study the brain?

I think that I’ve always been fascinated by the question of why people act the way they do. How do we take in sensory information—like colours, tastes and sounds—and turn that into an experience? I’ve always been curious to learn about the mechanisms behind the way we experience the world. That curiosity led me into cognitive neuroscience, where I studied the sensory systems that shape how we interact with the world. Over the past few years, I’ve explored different areas, from molecular neuroscience to behavioural studies on trauma.

So as a cognitive neuroscientist, we study sensory systems. Now, in my PhD, I’m focusing on pain, specifically how our touch system and spinal cord adapt when we’re in pain, and how those systems can be modified to change pain perception. A lot of my work also looks at neuroplasticity, which is the brain’s ability to change its behaviour in response to new stimuli.

Can you tell us more about your research? What are you working on at the moment?

Our lab is currently exploring certain drugs as novel pain relief techniques. Specifically, MDMA and related compounds and their potential to assist the recovery process of a chronic pain disorder. As well as molecular measurements, we are also looking at behavioural responses.

The idea is that some drugs, known as entactogens, can encourage social behaviours—things like empathy, bonding, and connection. In our experiments with mice, these behaviours seem to play a role in recovery from chronic pain, so we’re asking if encouraging natural behaviours like social touch can actually help relieve pain.

The exciting part is that the drug isn’t the cure on its own; it’s the drug's modification of behaviour that drives the change. The idea is that simply by encouraging this social behaviour, we help them naturally recover from chronic pain. Our long-term goal is to see if we can modify molecules like MDMA to capture the positive effects without the risk of addiction or long-term side effects. Some research suggests that increasing serotonin activity can reduce the dopamine reward surge and so could lower the abuse potential while keeping the therapeutic benefits. In addition to this, unlike SSRIs, which often require daily use, we’re exploring whether very infrequent doses could be enough to spark lasting change.

Where do tools like DREADDs and other techniques fit into your work?

To really understand what’s happening, we need ways to stimulate specific parts of the nervous system and observe how behaviour changes. Tools like DREADDs (Designer Receptors Exclusively Activated by Designer Drugs) let us do that. They give us precise control over neural circuits, so we can see which pathways are involved in pain, social behaviour, or recovery.

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What excites you most about the future of brain research?

The pace of neuroscience feels like it’s accelerating every year. That’s partly thanks to advances in AI and molecular techniques, but also because the tools we rely on are becoming more accessible. Affordable, reproducible reagents mean researchers can spend less time worrying about costs or inconsistencies and more time focusing on discovery. That accessibility means we can now manipulate incredibly small components of the brain and observe interactions at a level of detail that was unthinkable a few decades ago. As these tools continue to improve, I believe our ability to diagnose and treat mental illness will be completely transformed. If new therapies are implemented carefully, we have the potential to help millions of people.

AI is another area that’s reshaping brain research. Here in Toronto, which is sometimes called the birthplace of modern AI thanks to pioneers like Geoffrey Hinton, we’re seeing AI applied in fascinating ways. In my own field, for example, we use AI to track subtle behavioural changes in mice. It allows us to distinguish incredibly fine changes, such as whether an animal is experiencing pain or not, which would be nearly impossible for a human observer to pick up. Across my faculty, particularly in the pharmaceutical sciences department, AI is also being used to generate new drug candidates. The speed is astronomical compared to traditional methods. Drug candidates can now be generated by an algorithm in hours, as opposed to months or years by scientists. Instead of manually conceiving one or two possible molecules, we can explore dozens of viable candidates almost instantly. That kind of speed is opening whole new frontiers for drug discovery and neuroscience research.

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Do you see personalised medicine playing a role in the future of neuroscience?

Absolutely. Personalised medicine is one of the most exciting frontiers in neuroscience. It’s something that would have been almost unimaginable without the level of data collection, AI, and molecular understanding we now have. For a long time, mental health treatments have often relied on a ‘one-size-fits-all’ approach. For example, two people with anxiety or depression might both be prescribed the same SSRI at the same dose, even though their genetics, lifestyle, and brain chemistry could be completely different.

The promise of personalised therapy is that treatments could be tailored to the individual: the right drug, at the right dose, for the right person. That level of precision just makes sense biologically, and I think it has the potential to revolutionise how we treat mental illness. With the AI systems being developed today, I can see personalised medicine becoming a reality within the next few decades.

What are the biggest challenges facing neuroscientists right now?

One of the biggest challenges for neuroscientists right now is funding. In North America, we’ve seen significant cuts to research budgets in recent years. That directly affects what we can do in the lab, because many of the reagents and molecules we rely on to study human biology are expensive. When the most advanced techniques are out of reach, research doesn’t stop, but it slows down. We often must fall back on older approaches that take more time, require more labour, and in some cases mean using more animals to get the same amount of data.

Take the study of neurotransmitter systems as an example. New techniques now allow us to observe neurons firing in real time and watch how neurotransmitters are released at different sites. These methods give us an unprecedented window into brain activity, but they’re costly. If labs can’t afford them, they’re left with less precise methods that make progress slower. Scientists are passionate and will always find ways to push forward, but affordability does shape the pace of discovery.

Reproducibility is another big challenge. In neuroscience, once a new technique becomes the ‘gold standard,’ it can almost monopolise credibility in the field. If you don’t use that specific method, your work may not be trusted as much, even if your results are solid. But when those methods are expensive, it creates a barrier. Different techniques also come with their own reproducibility issues, so maintaining standards is difficult. That’s why affordable, reliable tools are so important: they make it possible for more labs to contribute trustworthy data, rather than progress being limited to a few well-funded labs.

More from neuroscientists on the Hello Bio blog

If you’d like to read more about neuroscientists and their research, take a look at these articles on the Hello Bio blog:

• Career Spotlights: Lecturer in Neuroscience
• Why We Need ‘Credibility in Neuroscience’
• Interviews with Scientists: Nick Souter
• Interviews with Scientists: Jose A. Morales-Garcia
• Interviews with Scientists: Rachel Sellick
• Ten Inspiring Neuroscientists to Follow on LinkedIn
• 15 Neuroscientists Share Their Memories of BNA2025