Dialing in a Molecular Foundation for Plant-Based Medicine

Psychedelics have shown promise as treatments in clinical settings, but there remains work to be done to develop the next generation of psychedelic and plant-based medicines. 

That’s a problem that Montreal-based Opportune Therapeutics is working to solve for the psychedelic and plant-based medicine segment. The company, which has a background in pharmaceutical and biotech, is using machine learning to develop safe and effective plant inspired therapeutics for specific health problems, a method that’s 40% faster and 60% cheaper than traditional solutions.

Opportune hopes to build on the clinical success of psychedelic compounds by developing tools to discover new medical applications, improve efficacy and reduce unwanted side effects of those compounds. Its platform uses machine learning to predict how different plant-derived compounds will interact with the human body and what each can treat.

To learn more about the company’s proprietary algorithm and what it means for medical psychedelics, we recently spoke with Opportune CEO Dr. Will Krawszik. His comments are below.

Dr. Will Krawszik: We’re a computational company that’s using molecular level machine learning to transform psychedelic-based research, which effectively will speed up drug discovery.

WK: Were operating at a slightly higher level. We’ve studied the molecular interactions of classical psychedelics and we’ve learned from that. We’re measuring different parameters associated with these classical psychedelics to help us discover or design novel psychedelics. So, think of it as Psychedelics V2. 

WK: Absolutely. We’re 100% focused on the therapeutic potential of these compounds. It’s not that I don’t really see any application for recreational use, all of that could be down the line, but our real focus is on the medicinal application. We want to help design or discover other psychedelic drugs inspired by the likes of psilocybin or LSD and those that are being commercialized at the moment so that we can retain the therapeutic potential of these compounds whilst simultaneously removing any unwanted side effects. The result is to push out new drugs to treat existing disorders more effectively and also new disorders in the future.

WK: It’s the same as what the classical producers are focused on. Anything linked to some form of trauma or addiction is the immediate focus. There could be other disorders that we’d want to consider, including brain injuries or strokes down the line, but for now we’re looking at trauma and addiction. That’s the main application for what we’re doing.

WK: I’ll speak to myself first. I’m an entrepreneur who has founded two companies in this space. The first one [Moleculomics] had more of an academic focus whereas Opportune has a focus on commercialization – Initially we were helping pharma and biotech companies improve their R&D processes, deploying our computational tools to help them discover drugs or design drugs quicker, but now we use our tools for our own drug discovery purposes.

About a year ago we made a pivot toward the cannabis space, when we realized that our tools could be used to help identify the therapeutic application for all of the different components of cannabis. Then we developed tools not only for identifying how they would work, but how combinations of compounds would function so we could look at the synergies between the cannabinoids and terpenes.

More recently in 2020, we decided to translate what we’d done and adapt the tools that we developed for cannabis to psychedelics and apply them toward this industry.

Our lead developer, Patricia Morales, has been working with me for the last three years – from the work that we did in the early days in terms of contract research work for pharma and biotech companies, through cannabis and now psychedelics. She’s a perfect blend of an expert in computational drug discovery and machine learning.  

Andrew Griffin is our chief scientific officer and is ex AstraZeneca, one of the largest pharmaceutical players in market. He has a lot of experience in taking a drug from concept all the way through the FDA approval process and through to the market. He’s really relevant because he is an expert in neurological conditions and an expert in computational approaches to drug discovery.

That’s the core team. And then we are supported by a host of scientific advisors that help us on different aspects, whether it’s the computational work that we’re doing as well as the route to market and through the FDA approval process. We also have a relationship with McGill University that’s taking the output of our process – the drugs that we’ve identified – and validating them in their laboratory using some proprietary technology that they have.

WK: I don’t claim that our computational approach will ever substitute for real-life testing, but this tool is really useful for helping to prioritize which compounds, which conditions or disease states you want to consider, and which receptors you need to look at. We are working closely with the likes of McGill University to integrate the output from their lab as a feedback loop to improve our machine learning algorithms. It’s a way to help improve R&D efficacy.

WK: Well, we spent about a year developing the cannabis application and we got support from the Canadian government’s National Research Council for that. When we decided to adapt that work to psychedelics we found that, since we’re effectively doing the same thing for the second time over, we can move really, really quickly this time. We’ve already implemented our solution for the classic psychedelic receptors and we already have a pipeline of different drugs that we’re investigating to take forward to the FDA approval phase. So, we have a preliminary pipeline of drugs that we’re looking at and we’re currently raising financing for our seed round. That gives you a picture of where we are.

WK: Absolutely. There’s a lot of work to be done still, but one of the main things that drew me to this sector was the potential for impact and growth. When you think about everyone that’s been impacted by either trauma or addiction issues directly or indirectly in their lifetime, general mental health issues are affecting millions of people and especially prevalent in the younger generation.

But I think that there’s still a lot of work to be done into how these drugs are actually implemented. Obviously, there’s a huge psychotherapy and general therapy component to this, so I don’t think we’re quite at mass market adoption yet. What we’re working on, and especially the second-generation psychedelics that we’re working on, we hope will help make that more appealing to the mass market.

That’s opposed to psilocybin treatment as it is today as an example, where the patient needs to be under direct supervision for six to eight hours. If that treatment time could be cut to a fraction of that but still offer the same output, then the therapist could turn around many more patients in the same amount of time. Those are the variables that we need to consider.

Then there are adverse reactions. Psychedelic drugs can cause some adverse reactions, whether they’re related to serious concerns like how the heart operates to more minor things like headaches or nausea. There’s still a lot of work to be done to make these adoptable by the mass market.

WK: I’d say that also, although the therapeutic potential of cannabis is extremely good, but as molecules, they’re not that potent, especially not when you compare them to the likes of LSD. So the potential that we have for psychedelics is much greater because these are extremely potent molecules that can really get inside the brain and change a patient’s set ways of thinking really enhance the neuro-plasticity that people talk about. That’s why we got involved in this space – because we can really make a difference to a lot of patients who need help.

For more information about Opportune and the work the company is doing to improve psychedelic research, visit Opportune-tx.ca.