Turbocharging Phenotypic Screening with AI to Target mRNA Biology

by Andrii Buvailo, PhD          Interview

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While the pharmaceutical world is investigating biologics or mRNA-based therapies, Yochi Slonim, Israeli technology and biotech entrepreneur and public speaker on the subject of startup building and positioning, is sticking to the classics -- small molecules -- but his strategy comes with a twist.

Yochi is not a classically trained pharmaceutical scientist. His background is in software, where he has created and sold start-ups that were acquired by large corporations like HP, UGS, and BMC. Yochi took his expertise in software/artificial intelligence (AI) and co-founded Anima Biotech in 2014 to help create a novel way to identify mRNA-targeting drugs and their mechanisms of action.

Anima’s platform – called mRNA Lightning – has been the subject of recent partnerships with Takeda and Eli Lilly, amounting to more than $1.12 billion. mRNA Lightning overcomes the common barriers in traditional drug design, having the potential to elucidate new therapies for previously “undruggable” diseases. 

Small-molecule drug design works by fitting a novel molecule to a receptor’s binding pocket, matching and complementing distinguishing features of the targeted receptor.  For some rare and difficult-to-treat diseases, the binding pocket is ambiguous with relatively non-descript characteristics. Other diseases like Idiopathic Pulmonary Fibrosis involve an overproduction of a ubiquitous and essential protein, collagen, in only one organ. Giving a small molecule that shuts down or interferes with collagen production would result in off-target effects on collagen throughout the body, a seemingly worse alternative than the disease itself.

Anima Biotech has gone one step above targeting the protein; their small molecules target the mRNA transcript used to make it. Through leveraging artificial intelligence and phenotypic screening in live biology, the company can identify multiple small molecules that can turn up or turn down protein production with the selectivity and specificity of working on one organ system. Not only that but the drugs’ mechanisms of action are elucidated. Anima's technology produces “multiple shots on goal” in tandem with the knowledge of how these molecules work in live cells.

Below is our interview with Yochi, where he is telling a story of his journey into biotech, explaining the scientific rationale behind Anima’s focus on mRNA biology and describing how their AI-driven platform is capable of cracking biology secrets in a high-throughput way. 


Andrii: You developed your career as a successful serial entrepreneur in the area of information technologies with several multimillion-dollar exits, and then… biology? Biotech is undoubtedly among the most demanding industries for entrepreneurship, with much more significant overall business risk due to the complexity and poor predictability of biology systems (on top of all other “traditional” challenges startups face in any industry). Obviously, this wasn’t a spontaneous decision -- what was the catalyst, a life event, or a revelation that made you switch industries like that? 


Yochi: My journey towards the biotech industry was not the standard one, which connects to the very essence of what we do at Anima, a company at the intersection of biology and software. 

I was in the software industry for more than 20 years before co-founding Anima, and during that time, I created three companies that went through substantial exits. The first company, Mercury Interactive, became the world leader in automated software testing. We took the company public after four years and reached revenues of more than $1B annually. It was then acquired by HP for $4.5B and became their software division. After Mercury, I led the Products and Marketing division of Tecnomatix, a publicly traded NASDAQ company. I managed an organization of 500 people comprising four divisions and generated revenues of $100M until the company was acquired by UGS for $230M.

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Topics: Novel Therapeutics   

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