This week on Data in Biotech, we are joined by Parul Bordia Doshi, Chief Data Officer at Cellarity, a company that is leveraging data science to challenge traditional approaches to drug discovery.
Parul kicks off the conversation by explaining Cellarity’s mission and how it is using generative AI and single-cell multiomics to design therapies that target the entire cellular system, rather than focusing on single molecular targets.
She gives insight into the functionality of Cellarity Maps, the company’s cutting-edge visualization tool that maps the progression of disease states and bridges the gap between biologists and computational scientists.
Along with host Ross Katz, Parul walks through some of the big challenges facing Chief Data Officers, particularly for biotech organizations with data-centric propositions.
She emphasizes the importance of robust data frameworks for validating and standardizing complex data sets, and looks at some of the practical approaches that ensure data scientists can derive the maximum amount of value from all available data.
They discuss what data science teams look like within Cellarity, including the unique way the company incorporates human intervention into its processes.
Parul also emphasizes the benefits that come through hiring multilingual, multidisciplinary teams and putting a strong focus on collaboration.
Finally, we get Parul’s take on the future of data science for drug discovery, plus a look at Cellarity’s ongoing collaboration with Novo Nordisk on the development of novel therapeutics.
Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in the life sciences.
Chapter Markers
[1:45] Introduction to Parul, her career journey, and Cellarity’s approach to drug discovery.
[5:47] The life cycle of data at Cellarity from collection to how it is used by the organization.
[7:45] How the Cellarity Maps visualization tool is used to show the progression of disease states
[9:05] The role of a Chief Data Officer in aligning an organization’s data strategy with its company mission.
[11:46] The benefits of collaboration and multidisciplinary, cross-functional teams to drive innovation.
[14:53] Cellarity's end-to-end discovery process; including how it uses generative AI, contrastive learning techniques, and visualization tools.
[19:42] The role of humans vs the role of machines in scientific processes.
[23:05] Developing and validating models, including goal setting, benchmarking, and the need for collaboration between data teams and ML scientists.
[30:58] Generating and managing massive amounts of data, ensuring quality, and maximizing the value extracted.
[37:08] The future of data science for drug discovery, including Cellarity’s collaboration with Novo Nordisk to discover and develop a novel treatment for MASH.
