In the field of drug discovery, one must always begin with the target, right? Not if you ask Cellarity, a quickly emerging biotech company revolutionizing the drug development space.
Rather than the traditional target centric approach to drug discovery, Cellarity works at the level of the cell to understand how disease impacts cell behavior via a target agnostic approach that can help illuminate the most complex diseases science has not yet been able to crack.
“For decades, drug discovery has been about reducing diseases down to a single molecular target that we can drug to influence the course of a given disease,” explained Cellarity CEO Fabrice Chouraqui, who is also a CEO-Partner at Flagship Pioneering. “This approach has produced a significant number of breakthrough treatments, but the target-centric assumptions that we make in vitro or in vivo do not often translate into human. Human biology is far more complex than any single target could ever predict, which is one reason why right now many drugs fail in clinical development. Our approach is different.”
Founded in 2019 and already rising to the top of lists such as BioSpace’s own Top Life Sciences Startups to Watch in 2021, Cellarity believes there is a better way—one based on the computational modeling of cell behavior.
Cellarity’s unique platform generates unprecedented biological insights by combining unique expertise in network biology, high-resolution data, and machine learning. The result is a new understanding of the cell’s trajectory from health to disease and how cells relate to one another in tissues. This in turn opens up a world of opportunities for the discovery of novel therapeutics, particularly for complex diseases.
“Diseases are complex and often not linked to a single target in a single cell in a single system,” said Chouraqui. “Conditions like T cell exhaustion, metabolic disease, complex neurodegenerative diseases like Alzheimer’s—there’s a reason we haven’t made a lot of progress in these areas. So we asked ourselves if there was a way to work at a higher level—the level of the cell—to really harness the complexity of human biology.”
Because Cellarity’s pioneering approach does not start with a single molecular target, its scientists are able to uncover a much more diverse set of compounds that can be deeply characterized to understand how they work on both known and previously unknown targets. Indeed, the company’s algorithms, data assets and approach were inspired by systems biology.
“In the early 2000s, systems biology proposed that by looking at biology as a ‘whole’, we would be able to better understand the interplay between its ‘parts’, specifically genes, proteins and pathways in the context of disease and health,” said Cellarity Chief Digital and Data Officer Milind Kamkolkar. “However, due to a lack of well-integrated high-resolution data and sophisticated computational power, the industry had no choice but to study biology’s parts in the absence of its networks.”
A lot has changed since then. In the past five years alone, phenotypic drug discovery has evolved as an alternative to the single-target approach, thanks to advances in high-throughput imaging technology and machine learning. Yet the gap between a drug’s success in vitro and an efficacious drug in patients remains immense.
Cellarity’s solution: Unlike single molecules, single target or phenotypic representations of cellular programs, Cellarity directly targets cellular programs critical to disease, leveraging a platform that systematically addresses the problems of translation beyond simplifying target discovery, toxicity, adverse effects, and drug design.
One key part of the approach is the way Cellarity predicts drugs and their properties by tying them to computationally engineered representations of cell behavior called Cellarity Maps.
“Cellarity Maps give us a much higher-resolution picture of the cellular components of a tissue and really allow us to understand the mechanism of action that one would want to reverse to go from a state of disease to a state of health,” said Chouraqui.
Chouraqui believes that there is no limit to where this cell-centric approach can take Cellarity and the field of medicine. His assertion is backed up by the cadre of investors that recently put up $123 million in series B financing.
“Our investors recognized that Cellarity stood out in the field of drug discovery,” said Saif Rathore, MD PhD, Cellarity’s VP and Head of Strategy and Partnerships. “We are the only company taking a target-agnostic approach that evaluates cell behavior changes and works through product optimization, whereas others in the field are primarily working on optimizing different parts of the target centric molecular or phenotypic drug discovery processes.”
To execute its vision, Cellarity has assembled a team of diverse, world class talent. “We have brought together international leaders from pharma, graduates of Flagship Pioneering academic programs, physicians, scientists, and pedigrees that span the spectrum from the Broad Institute to McKinsey.” said Rathore.
The outcome: the pioneering biotech already has 7 drug discovery programs underway across 10 therapeutic areas including the high-value fields of hematology, immuno-oncology, metabolism, and respiratory.
“All diseases stem from a disorder at the cellular level,” said Chouraqui. “This cell-centric approach can be applied to virtually every single disease. We are progressing programs in diverse therapeutic areas to show the depth of our platform, starting with diseases for which there is a well-understood and direct correlation between a change in cell behavior and the etiology of the disease.”
Chouraqui’s vision for the platform transcends the company. In a few years’ time, he sees Cellarity with unparalleled predictive power in different drug modalities and a deep exploratory pipeline with multiple clinical proofs of concept in different disease areas.
“Our platform has the potential to change how the world approaches the discovery of medicines” said Chouraqui.
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Source: https://www.biospace.com/article/cellarity-transforming-drug-development-at-the-confluence-of-biology-and-machine-learning/
