San Diego, Calif. – The BIO Convention always highlights new regulatory developments, cutting edge technologies and the best new companies that are going change the face of healthcare in the near future, and 2024’s conference did not disappoint. The first of a series of CheckOrphan articles highlighting companies changing the future starts with 123Genetix and its revolutionary aiHuman platform, DeepNEU.
Artificial intelligence and machine learning (AI/ML) is a global focus. Whether we actively use it to help our lives and jobs daily, or have not started using it, we are all passively surrounded by AI/ML every time we use the internet, our cell phones and most email providers.
In these situations, the companies are collecting data about us, and then selling it to other companies and marketers who can then send us content and advertising that is supposedly more targeted to us.
DeepNEU – the Journey
However, the pharmaceutical and biotech industries are taking a different approach, and none highlights this change of paradigm better than Dr. Wayne Danter’s approach with DeepNEU – the first aiHuman platform for drug discovery, drug development, and drug clinical development – that “simulates what will happen with a product in humans with about 95 percent confidence,” explains Dr. Danter.
DeepNEU has been a project in the making for Dr. Danter.
“It is really the pinnacle of my work that first started as an undergrad computational chemist. A key building block was becoming a certified cardiologist, which gave me an in-depth understanding of how all the organs in the body interact through our circulatory system, and I found that to be essential in developing DeepNEU. Having run clinical trials also helped me build DeepNEU.”
“But developing DeepNEU didn’t happen overnight. I developed my first AI/ML platforms at the University of Western Ontario, where I was an Associate Professor of Medicine of Cardiology.”
These first platforms were bought by a Canadian company, and the success fed Dr. Danter’s desire to go further with a second platform that would allow for multiple drug target interactions. That company and platform were named COTI.
“COTI was a great steppingstone in my career. I ventured away from my praxis and university life and formed a company with drugs produced from our AI/ML platform that produced positive clinical results and culminated in an IPO.”
However, multiple drug interactions were not enough for Dr. Danter. The more he read and interacted with the pioneers of AI/ML in all fields in the early 2010s, the more convinced he became that he could build an aiHuman platform.
After much planning and initial concepts, Dr. Danter took his prototype – which even Dr. Danter admits was more of a concept at the time – to the board of COTI, and they readily dismissed the likelihood of being able to produce such a platform, and further contended that it would detract from moving their lead assets through their ongoing clinical trials.
Looking back, Dr. Danter readily concedes that the board was correct in wanting to focus on their lead assets and not allowing for possible distractions, but an internal drive led him to resign as CEO to pursue DeepNEU.
DeepNEU – A True Game-changer
After 7 years of work, several validations with companies using DeepNEU, and 10 journal publications, Dr. Danter is proud to assert that DeepNEU simulates what will happen in humans with 95% confidence. When pressed as to how he knows that he is somewhat protective as a Michelin chef would of house recipes.
However, Dr. Danter was open about using DNA, RNA, protein, peptide and metabolome databases, PubMed (with a machine learning filter to remove “junk” publications), organoid modelling data and vetted calibration techniques that rely on data from hundreds of approved products with many years of safety and efficacy data.
“I have had investors and people, who now work with me, who did due diligence on DeepNEU and became convinced of its power. I have had top mathematicians and algorithm experts also test the platform, and each time the feedback was that DeepNEU is built on the latest and best algorithms.”
It is one thing to have a vetted algorithm, but it is a much larger claim to advertise that you have an aiHuman platform.
“Yes, the proof is in the pudding, right?” agreed Dr. Danter.
“And we definitely have the proof to demonstrate to investors and companies that want to use our platform.”
“With an oncology company we work with, they had already tested several preclinical assets in animal models, and we found that the most effective product was the one their testing also determined, however, we found that it would have a strong safety signal, and that their second most effective asset was a much safer product.”
Thus, DeepNEU ensured that the company did not spend 5-7 years and over $50 million only to have their asset fail in a phase III trial due to safety concerns.
“What is the value of that?”
Removing a large risk of failure is key, but DeepNEU also shortens timelines for companies as well. This is now reality in the US, since Congress passed legislature in 2021 requiring FDA to allow companies to use AI/ML generated data to satisfy preclinical development requirements that companies rely on to file an IND.
Commenting on this, Dr. Danter explained, “Most results from animal model testing translate to humans with a 50% success rate on average, which is why so many products fail. Even more concerning is that most animals used do not address safety in humans. With DeepNEU, the translation to humans is 95% on average, and we can ensure safety as well.”
DeepNEU – Tomorrow’s Reality, Today
Due to DeepNEU’s track record and the US laws, Dr. Danter is working with companies to help them move their time from discovery to filing an IND to one month.
“This is a reality right now.”
The company would still need to develop a clinical trial protocol, establish manufacturing for their product, establish clinical trial sites and prepare an IND for filing – all of which can take as long as 12 months.
“Normally the time from discovery to IND takes between 3-5 years, and to be able to reduce that to 12 months or less is substantial, when you consider the reduced costs and preservation of IP.”
By ensuring a product has 2-3 more years of patent protection, when it is approved for sale is very significant, considering most products generate hundreds of millions in revenues each year, and some produce billions annually in sales.
When asked if 123Genetix is a service provider, Dr. Danter was quick to respond, “No, we focus on developing treatments for rare diseases. We are willing to license the platform to service providers and companies for all indications.”
When asked about larger indications such as diabetes, cardiovascular, and pain, Dr. Danter was quick to explain, “We have had several good conversations with companies that want us to generate products for large indications through partnerships. We want everyone to benefit from DeepNEU, however, our focus is on rare diseases.”
When pressed as to a weak point of DeepNEU, Dr. Danter admitted, “Simulating cell therapies is a part of the platform that still needs development. Cells often have so many things they can do, which makes cell therapy so powerful.”
“However, we don’t know exactly when cells execute each task and in which order. We have the outcome, which is the most important part, but working with other companies and as more information about cells is published, DeepNEU will approach 95% confidence with cell therapies as well.”
When asked what the future holds for DeepNEU, Dr. Danter was quick to answer, “We can run virtual trials with thousands of people, all ethnicities, genetic variants, and more. And we can run trials that 10 years in length to thoroughly assess safety.”
The goal is to work with regulatory agencies to make this a reality within the next 3-4 years.
Contact
Robert Derham
+1 (415) 335 8283