Indivumed and CELLphenomics Announce Partnership for Improved Cancer Patient Care
European Union-Funded Project to Result in Novel Treatment Approaches for Several Solid Tumor Types
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“Leveraging our multi-omics database and AI-driven oncology analytics is what allows us to decipher the complex mechanisms of cancer in order to drive the development of precision oncology,” said Prof. Dr. Hartmut Juhl, CEO and Founder of Indivumed. “By partnering with CELLphenomics, we will be able to quickly validate therapeutically relevant targets to identify new treatment approaches and accelerate cancer drug development in the future.”
The partnership announcement comes after Indivumed was awarded €4.3 million by the European Union Structural Fund ERDF to accelerate drug development and personalize treatments for cancer. CELLphenomics was selected by Indivumed as a partner due to the company’s technological capabilities and scientific expertise. Initially, the partnership will focus on cancer types with the greatest current medical need.
“Indivumed’s comprehensive database and advanced AI capabilities are critical for identifying therapeutically relevant targets,” said Dr. Christian Regenbrecht, CEO of CELLphenomics. “Combining these targets with CELLphenomics patient-derived models and in-vitro assays will enable reliable conclusions to be drawn about the treatability of the tumor and its functional causes of therapeutic success and failure.”
Based on the highly standardized cancer biospecimen collections through Indivumed’s Clinical Network, capturing the molecular reality of each patient’s disease is key to the project. Having generated the most comprehensive and deepest multi-omic dataset for cancer biology worldwide, Indivumed will leverage advanced analytical techniques to extract biological insights from this complex data. Indivumed’s analytical platform, nRavel®, will identify, characterize, and prioritize potential targets for the selected tumor types. The patient-based cellular models provided by CELLphenomics will now be derived from the same tumors. This means that the whole process – from tissue and data collection to identification and validation – will utilize the same data and tissue.
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