Managing tumor heterogeneity: Proteona and AI Singapore partner to improve cell therapies and IO treatments through single cell analysis of tumors and CAR T cells
Innovative AI-driven genomic and proteomic analysis platform for improving cell therapy and immuno-oncology
SINGAPORE, 30 August 2019 - Proteona Pte. Ltd. has announced its participation in AI Singapore’s 100 Experiments (100E) programme to develop AI tools for single cell multi-omics data analysis. The project is being conducted in collaboration with Prof Wong Limsoon, Kwan Im Thong Hood Cho Temple Chair Professor from the National University of Singapore (NUS) School of Computing, a leading expert in bioinformatics and computational biology. Together with Proteona bioinformaticians and data scientists, the team aims to solve key challenges in single cell data analysis using artificial intelligence tools.
A key obstacle of single cell data analysis is combining datasets from different sources such as different patient samples and obtaining robust cell clustering and cell-type annotation. Single cell analysis often leads to the discovery of novel cell populations with features that had not been previously observed. Clinical samples, such as tumor biopsies, are known to be very heterogeneous, making cell type identification very challenging. Moreover, single-cell analysis is prone to noise and batch-effects that make comparisons across experiments difficult.
As a result of these challenges, cell clustering and cell annotation usually requires extensive manual intervention. This is time consuming, requires specialized knowledge and expertise, and is prone to human error and bias.
“Batch effects are prevalent in -omics data. This is particularly pronounced in single-cell measurements. Profiles from one batch are not directly compatible with that from another batch.” says Prof Limsoon Wong, NUS School of Computing. “The AI-driven components here will facilitate a more convenient and explicit identification of the specific protein complexes and biological circuits relevant to cell-types and states.”
With this collaboration, the team will further develop their robust computational workflows for knowledge-driven analysis, with an AI-based system trained using Proteona’s in-house annotated datasets. Proteona’s ESCAPE™ RNA-Seq technology and services simultaneously measures both proteomic and transcriptional expression at single-cell resolution. The developed AI-analysis will leverage this unique modality to enable deeper insights into single-cell biology.
“An immediate outcome of this collaboration will be a tool to improve the quality of results presented to our customers. It will save them time in annotating known cell types and correcting for batch effects. This platform is also used internally as a way for building our database of cell types and cell states which is then used for better annotating our customer’s data. We will also use these tools for our internal programs in biomarker discovery and diagnostic development,” says Dr Andreas Schmidt, CEO of Proteona.
“We see the merging of biotechnology and data-driven IT as one of the biggest value drivers in the health industry. With Proteona`s single cell proteogenomic data platform the company is in a unique position to impact health decisions for therapy development and the clinic,” explains Chou Fang Soong, General Partner Pix Vine Capital, one of Proteona´s investors.
With founders Prof Gene Yeo of UCSD, Prof Jonathan Scolnick of NUS and Deputy Director
of the Molecular Engineering Laboratory, A*STAR, Dr. Shawn Hoon, Proteona has strong
roots in cutting edge academic discoveries around the world. The Proteona - AI Singapore
consortium actively seeks additional partners from the cell therapy and hematology-oncology
communities to contribute to their international single cell analysis initiative.
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Dr. Andreas Schmidt
Proteona is a precision medicine company in Singapore, Germany, and the US that is pioneering the use of single cell multi-omics to improve clinical outcomes in cancer. Using a combination of innovative single cell assays and AI-assisted bioinformatics, Proteona enables pharmaceutical companies, biotech partners, and clinicians to integrate single cell level precision into their clinical projects. Proteona continues to develop comprehensive, disease-specific single cell databases combining gene expression, protein expression, and mutation information derived from each individual cells as well as drug response data for each sample. Proteona has been selected as a “One to Watch” by Nature Research Spinoff Award and a Winner of Falling Walls Ventures Breakthrough of the Year 2020. Proteona is a spin-off from the National University of Singapore (NUS) and the Agency for Science, Technology and Research (A*STAR).
About AI Singapore
AI Singapore (AISG) is a national programme launched by the National Research Foundation Singapore (NRF) to catalyse, synergise and boost Singapore’s artificial intelligence (AI) capabilities to power our future, digital economy.
AISG brings together all Singapore-based research institutions1 and the vibrant ecosystem of AI start-ups and companies developing AI products to perform use-inspired research, grow the knowledge, create the tools, and develop the talent to power Singapore’s AI efforts.
AISG is driven by a government-wide partnership comprising NRF, the Smart Nation and Digital Government Office (SNDGO), the Economic Development Board (EDB), the Infocomm Media Development Authority (IMDA), SGInnovate, and the Integrated Health Information Systems (IHiS).
For more information on AI Singapore, please visit https://www.aisingapore.org/
1 Nanyang Technological University, National University of Singapore, Singapore Management University, Singapore University of Technology and Design, Singapore Institute of Technology, Singapore University of Social Sciences, Agency for Science, Technology and Research (A*STAR) and other Singapore-based public funded research institutions