Open call for cell-based medicine project ideas

This topic calls for technology oriented project ideas aiming to develop further and/or integrate single-cell (multi-)omics and imaging technologies with artificial intelligence and in particular machine learning technologies for R&D applications and potentially clinical use at a later stage. Technology development priorities required for implementing cell-based interceptive medicine are in particular the ones identified by the LifeTime Initiative (see chapter 3 of the LifeTime Strategic Research Agenda: sections Priorities for Developing Next-generation Single-cell Multi-omics and Imaging Technologies p46-49 and Computational Analytics p57-61).

Examples of technology developments which could be proposed under this topic: sensitive, high-resolution imaging- and sequencing-based spatial (multi-)omics technologies, perturbation screens and lineage tracing coupled with single-cell (multi-)omics, multiplexing strategies to increase single-cell analysis high throughput, computational methodologies for data integration of multiple modalities, analytic computational approaches to reveal molecular features and subpopulations hidden behind noise, and ultimately discover links between cell types, phenotypes, and states and their molecular networks

This topic calls for project ideas aiming at developing the next-generation of patient-derived experimental disease models (organoids, human-on-a-chip, advanced animal models containing human genes and cells) and novel predictive computational models of disease. Developing these key technologies in various areas such as the one identified by the LifeTime Initiative (see chapter 3 of the LifeTime Strategic Research Agenda: section Priorities for Developing Next-generation Patient-derived Experimental Disease Models p67-70) will provide experimental models that reflect human biology and pathophysiology as closely as possible. These can then be used to understand disease molecular mechanisms at the cellular level and iteratively test AI and machine learning-based computational models that predict outcomes or most effective treatments for an individual patient.

Examples of technology developments which could be proposed under this topic:
increasing cellular, structural and functional complexity of organoids (vascularisation, innervation,immune compartment, etc.), organoid integration to study tissue-tissue and organ-organ interactions, standardisation, automation, scaling and benchmarking of organoid propagation and banking, generating computational predictive models based on patients’ cellular trajectories

This topic calls for project ideas aiming at integrating and applying combination(s) of single-cell, AI technologies and patient derived disease models to identify biomarkers and develop precise diagnostics on the basis of mechanistic, cell-based understanding of disease.

Examples of technology applications which could be proposed under this topic:
Identification of diagnostic, prognostic, or predictive biomarkers by AI-assisted single-cell analysis in minimally invasive liquid biopsy, development of next generation screening for early disease detection and/or therapy monitoring

This topic calls for project ideas aiming at integrating and applying combination(s) of single-cell, AI technologies and patient derived disease models for the discovery of more reliable drug targets and/or the development of cellular therapies (cell-, gene-, RNA-therapy, etc.)

Examples of technology applications which could be proposed under this topic:
AI-supported spatial omics technologies to localize diseased cells in tissues and precisely describe cell functionalities thereby establishing causality for molecular mechanisms and identification of new therapeutic targets, development of new cell-specific therapeutic concepts such as sequential immunotherapy or cell-therapy to modulate specific cell types or deliver targeted modifications

This topic calls for project ideas aiming at developing software-based AI tools that can assist physicians, nurses, patients, or other care-givers in clinical decision-making.

Examples of technology applications which could be proposed under this topic:
Novel diagnostics software products (e.g. integrated omics-, imaging and network analysis) for the identification of the best therapy for the individual patient; digital pathology with explainable AI applied to spatially resolved single-cell data in combination with medical imaging data

This topic calls for technology development and application projects which do not fit in one of the above categories.

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