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Q&A: AION Labs’ new startup aims to streamline drug discovery



This week Israel-based AION Labs, an AI-powered drug discovery partnership between global tech and pharmaceutical companies such as AstraZeneca, Merck, Pfizer, Teva, Israel Biotech Fund and Amazon Web Services, announced announced a new startup called OMEC.AI.

OMEC.AI aims to build an AI-powered computing platform that can help researchers assess a drug candidate’s clinical trial readiness, identify potential safety responsibilities, and recommend tests to close any identified gaps.

Gill sat down with MobiHealthNews discuss OMEC.AI, how it kicks off, and the data it will use in its AI calculations to meet its intended outcomes.

MobiHealthNews: Can you tell me about OMEC.AI and its goals?

Carry: Our entire venture creation model is built around three pillars. The first pillar always starts with a big challenge, if it is solved it will really have an impact on the patients and of course a very strong viable company that is addressing a much needed opportunity. for industry.

Second, we search for the best scientists and founders who can tackle that challenge with a lengthy and arduous in-depth review process.

Third, we set them up as a new startup with funding, then systematically mentor them for their success and support them by providing them with data and everything else they needed. for them to succeed.

All of that is done not only by the AION Labs team, but also by our partners in a code development model where everyone works together from day one to help build the company. this and make it a success in four years.

In this case, OMEC.AI has three facilitators from our partners: Pfizer, AstraZeneca and Merck (Merck of Germany, EMD Serono). Those three are direct investors in OMEC.AI and will have equity in the company, but no IP rights. Each appointed champions in their R&D organization to help them and systematically work with them to develop the technology, and was involved in defining challenges and options. candidates.

OMEC.AI is addressing how we go about deciding which drugs should go into clinical trials, which is perhaps the most important decision in the pharmaceutical R&D process. Once you decide which drug candidate to bet on as a pharmaceutical or biotech executive, it will be a hundreds of millions of dollars investment process that you never stop. again unless science fails.

So really what our partners want to do is use artificial intelligence to be able to create a technology platform that helps them make better decisions and ultimately reduce attrition rates and make these drugs safer and more effective for patients.

The challenge is, how do we get all this data Accurate data is generated in conjunction with other data sources and create an AI-based platform that can test the drug and tell you what’s the chance of its success in the pre-human clinical trial phase? And right now, that process is done essentially manually with very little tech-savvy.

Ultimately, we know that the vast majority fail to gain market approval because they have failed at some point in the process. So there is clearly an unmet need and something that digital and computational technologies will be able to address if you bring in the right people to do it. And that’s what we’ve been looking for.

MHN: Who are the people you have found to form this group and what problems will they be looking to solve?

Carry: They are two artificial intelligence veterans who have worked at the forefront of AI technology in the auto industry, mainly. They worked at Mobileye, an autonomous driving company based in Israel, but was sold to Intel for $15 billion.

So they come to us with a technological approach that can create a platform that can integrate data and in a very ambitious way that will be high risk but also high reward. And our partners liked their approach – the R&D partners met with them.

So the three companies AstraZeneca, Pfizer and Merck along with Amazon Web Services will also support them. So they will have those four companies, either as investors or backers and in the case of Amazon, partnering with them to be able to develop the technology. We also received a grant from [Israeli] government to support them. So they get a $2 million grant, essentially, as a pre-seed round. And they started operating this month.

MHN: You mentioned it’s high risk but high reward. Can you tell me what some of those risks might be?

Carry: Well, it hasn’t been proven that you can [do this]. So far, there isn’t a single technology that can do what they’re trying to do. So that’s the risk. Can we really create an AI platform with data that can be accessed for final testing of every drug before it goes into clinical trials? To be able to tell for pharmaceuticals, investors or whoever will be users whether this drug has a high probability of success or a high possibility of toxicity? That’s what they will try to do. It hasn’t been done yet. So by definition, it’s high risk.

MHN: AI is only really good when information is fed into it. The cool thing is that you have Merck, AstraZeneca, Pfizer and others involved in the project. Does the data come from each of these companies? Is there selective data being used?

Carry: So all companies have committed to providing the data they need to do whatever they need based on what they have. It’s not like Pfizer would say, okay, take all our historical data without careful selection. Partners are willing to share their data with the startup.

They are committed to doing that and they want to do it to help them develop their technology. But they don’t want to share with each other, and they are not allowed to share with each other, because that would be anti-competitive by definition. So we’re creating a platform to enable them to share that data in a linked way that’s consistent with all best practices.

MHN: In the end, what do you hope this program will lead to? What do you hope this company can solve?

Carry: What we are trying to achieve at AION Labs in general, and then specifically for this company, is to create amazing independently developed AI-based startups for the biotech sector. so that we can help scientists and researchers – not to replace them, but to actually empower them by bringing new technological capabilities, so they can optimize the whole process drug discovery and development.



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