Unleashing the power of single-cell technologies – Drug Target Review

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5 July 2023
Drug Target Review’s Taylor Mixides interviews Cellarity’s CEO Fabrice Chouraqui about applying Artificial Intelligence (AI) and Machine Learning (ML) to evolving single-cell technologies.
Drug Target Review’s Taylor Mixides interviews Cellarity’s CEO Fabrice Chouraqui about applying Artificial Intelligence (AI) and Machine Learning (ML) to evolving single-cell technologies.
Cells are the units of life, yet they also drive disease. By applying AI/ML to the evolving gamut of single-cell technologies, we can better understand how cells transition from a state of health to disease. Cellarity’s CEO Fabrice Chouraqui explains how the intersection of these technologies offers the opportunity to understand biological systems from the perspective of the cell, rather than through the proxy of a single target or single pathway, as has been traditional for medicine and pharmaceutical development. This new approach to drug discovery uncovers novel biology, even in diseases with no known targets.

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Cellarity’s platform is an entirely new approach to drug discovery. Focusing on the cell allows us to see biological systems in full, and not through the proxy of a single target. Our AI models utilise data at single cell resolution to identify cell state transitions that drive disease and to identify compounds that can revert these disease state transitions. Our approach allows us to uncover novel actionable biology, even in diseases with no known targets, and design non-intuitive chemistry. Also, since the cell is a much fuller representation of disease, our platform is designed to drive much higher clinical success.
We apply our cell centric platform to discover novel small molecules that target the cellular mechanisms of disease. For instance, for many chronic diseases, which are the leading cause of disability and health care costs in the US, we do not know the underlying molecular pathology. Many of these complex diseases are not driven by a single target or genetic driver and have therefore defied our current drug discovery paradigms. In contrast, because they are driven by complex regulatory changes, they are a great fit for the Cellarity platform. (figure 1)
Previously, the ability to target the whole cell was limited as the technology did not exist, but with the emergence of new technologies like single cell sequencing, we can now utilise the whole cell to uncover novel biology. Since this technology is so new, as is our ability to analyse the large amount of data volumes with computation, this means we are creating the data and analytical methods from scratch, which is one of the key challenges we face in the continued development of our platform.
Without AI/ML, our ability to learn from the vast amount of data that single-cell technology produces would be severely limited. At Cellarity, our platform utilises proprietary AI models trained on over 30-million single cell transcriptomes allowing us to uncover novel biology. The AI allows us to see patterns in the data that we would not have otherwise been able to see and provides an unbiased analysis, all of which helps us create non-intuitive drug candidates in a vast array of diseases.
AI is not necessarily the limitation but rather the data inputs that are required. Depending on the biological questions that need to be addressed, sourcing high quality samples, and generating and analysing the right data types is essential.
There are many diseases, such as NASH, that have multiple known targets but no successful treatments. For other diseases, there are known targets, but they are not druggable. Cellarity’s approach can be applied to virtually any disease linked to dysfunctional cellular biology. The cell is a much fuller representation of disease, allowing us to see biological systems more holistically and not through the proxy of a single target or pathway and therefore, we can identify novel actionable biology even in areas where there is a lack of known targets.
In sickle-cell disease, we generated a single-cell map of haematopoiesis and identified cell behaviors tied to the production of a protective form of haemoglobin. We then used our AI systems to predict small molecules that directly induce these cell behaviors. These compounds achieved remarkable results, with efficacy exceeding standard of care and equivalent to gene therapy in vitro. Examples like this show how our platform can revolutionise the treatment of sickle-cell disease and other conditions by addressing the root causes of disease at the cellular level.
As previously mentioned, our platform is fueled by new technologies and analytical methods which had not previously been developed. Knowing there is still much for the community to learn, we have now twice released novel, open-sourced, single-cell datasets and invited the ML communities to develop new algorithms that can help the community at-large learn the rules of cell behavior. Also, last year, we organised the first Single Cell and AI in Medicine Symposium, and in May 2023, hosted it for a second time, because we saw the need for a forum for scientists to discuss the state of innovation at the intersection of single-cell analysis, AI, and biology and how this field is impacting drug discovery and the progress of medical science.
Author Bio:
Fabrice Chouraqui, PharmD
Fabrice Chouraqui is the CEO of Cellarity and CEO-Partner, Flagship Pioneering. Before joining Flagship Pioneering in 2020, Fabrice was President of the U.S. pharmaceuticals business for Novartis, where he oversaw all business areas, including U.S. Clinical Development and Medical Affairs. Fabrice is an experienced global pharmaceutical executive with a passion for driving the progress of medical sciences and bringing innovation to patients and has led the launch of breakthrough treatments in a number of areas, including oncology, immunology, neuroscience, and cardiovascular.
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