Abstracts & Speakers

SESSION I: DATA ANNOTATION AND FUNCTIONAL ONTOLOGIES

Towards controlling and imaging stem cell differentiation one cell at a time in organoids.

In this presentation, we will explore the role of spatially distributed growth factors in directing stem cell differentiation and tissue organization. I will introduce an experimental strategy that employs 3D colloidal scaffolds biofunctionalized with growth factors and embedded within spheroids of human stem cells. These scaffolds act as artificial organizing centers, guiding the spatial architecture of cardiac and liver organoids. I will demonstrate how the localization of these artificial centers influences the intrinsic secretion and deposition of tissue-specific extracellular matrix, which in turn directs cell differentiation and morphogenesis through the self-organized formation of local microniches. I will present results showing how this approach enables the in vitro recapitulation of periportal area development in the human liver and promotes the guided elongation of millimeter-scale bile ducts. Finally, I will discuss the potential of these colloidal scaffolds to support the assembly and spatial integration of multi-organ assembloids.

Advanced behaviour phenotyping for neurogenetic and preclinical studies in the laboratory mouse.

Behavior is the ultimate output of the nervous system, yet linking altered behavior to altered neural circuit function, and ultimately to altered genetics, remains challenging. The Kumar Lab uses advanced behavior analysis across multiple biological domains to build tools and statistical models for high-throughput, objective, and precise phenotyping in mice. We developed the JAX Animal Behavior System (JABS), an open-source integrated hardware and software platform that uses deep learning to extract rich phenotypic measures—including locomotor activity, grooming, stride-level gait and posture, nocifensive behavior, body mass, and biological frailty—from video recordings in a standard open field apparatus. We have also led the development of JAX Envision, a commercial home cage monitoring system, that enables continuous observation of multiple mice for weeks to months. Our work spans neuroscience, gerontology, rare diseases, and oncology. I will discuss our findings across these domains and the future development of our methods, including the application of genome-wide association and cross-species genetic mapping to connect computationally derived mouse phenotypes to human disease. I will also discuss our efforts in the democratization of machine learning and computer vision methods, lowering the barrier to entry for advanced behavioral phenotyping in the research community.

SESSION II: DATABASES AS ENGINES OF FUNCTIONAL GENOMICS

IMPC as a foundational dataset for understanding human disease

This presentation will explore how the IMPC data is created, improved and validated by experts, mapped to human rare and complex disease and how the IMPC data and materials are used in exploring human disease and pre-competitive drug discovery. It will consider future modes of access for IMPC and and the global and long term impact of the data resource.

Functional Annotation of the Mouse Non-Coding Genome for Understanding Human Diseases

Clinical genetics has revealed that approximately 60% of rare human diseases remain undiagnosed and cannot be explained solely by variants in protein-coding sequences. Moreover, genome-wide association studies (GWAS) of common diseases have indicated that over 90% of disease-associated variants are found in non-coding regions. These findings highlight cis-regulatory elements (CREs) as a critical yet underexplored layer in disease biology. However, modeling such variants in mice is particularly challenging due to their abundance and complexity of gene regulatory mechanisms.

Recent large-scale consortia have now catalogued millions of candidate CREs across mammalian genomes in a cell-type-specific manner. Although it is difficult to predict their impacts on gene regulation and phenotypic outcomes, advances in emerging technologies and large-scale datasets provide an opportunity to refine the identification of key CREs and address this challenge.

In this talk, I will introduce an ongoing International Mouse Phenotyping Consortium (IMPC) initiative led by RIKEN BRC to address this challenge: (i) systematic prioritization of candidate CREs, (ii) genome editing in mice to model non-coding variants, and (iii) establishment of interdisciplinary working groups to integrate genomics, epigenomics, and phenotyping expertise. By moving beyond coding sequences, the IMPC has the unique opportunity to define the functional and phenotypic impact of non-coding variants at scale.

SESSION III: MECHANISTIC IN SILICO DISEASE MODELING AND PREDICTIVE MEDICINE

AI in Human Genetics: Enhancing Discovery and Mapping Disease Mechanisms

I will discuss opportunities for artificial intelligence in human genetics to connect disease-associated genetic variation with cell- and tissue-level phenotypes and inform interpretable models of human disease. I will first introduce HistoGWAS, a framework that integrates histology foundation models for automated morphological phenotyping with scalable variance-component methods to perform genome-wide association studies of latent tissue imaging features. Coupled with generative modeling, HistoGWAS enables visual interpretation of how specific genetic variants influence tissue architecture. I will then discuss extensions of these concepts to other imaging and genomic modalities—for example, fine-tuning retinal foundation models to enhance discovery and interpretation of retinal disease loci, or identifying causal cell types and states using single-cell data. Finally, I will present opportunities to bridge sequence-based and population-level models, highlighting a Bayesian framework that integrates pathogenicity scores from sequence language models to improve discovery power in rare-variant association studies. Together, these approaches illustrate how AI-driven analysis of large-scale biological data can move the field beyond statistical association toward interpretable and predictive models of disease biology.

SESSION IV: ANIMAL MODELS TO DIGITAL HUMAN DISEASES

Multiscale modeling of Hippocampal CA1 networks

Understanding hippocampal function requires modeling approaches that span multiple scales of biological organization. In this talk, I will present work from our laboratory ranging from the detailed characterization of single-cell properties to the reconstruction of large-scale networks, and further to the analysis of signal propagation along the hippocampal circuit. I will also show how this multiscale framework can be extended to translational applications, offering new insights into both healthy hippocampal processing and neurological dysfunction.

SESSION V: ETHICAL, REGULATORY AND REPRODUCIBILITY CHALLENGES

Supporting NAMs innovation: why standardisation and validation matter!

New Approach Methodologies (NAMs) are transforming the landscape of scientific research, regulatory science, and safety assessment by offering alternatives to traditional animal-based testing. These methods, which include organ-on-chip, 3D bioprinting, high-content screening and computational models, promise improved human relevance, scalability, and ethical acceptability. However, the translation from technological and scientific innovation to industrial and regulatory use needs to be supported by two closely related activities: standardisation and validation. This talk will focus on the principles and processes that are on the basis of validation and standardization, on current advancements of NAMs used for chemical safety and medicinal development, and on best practices and tools that should be used by scientists and developers of NAMs.