ZURICH 18 DECEMBER 2022. Apricot Therapeutics signed its first proof-of-concept partnership agreement to generate a unique dataset for the characterization of novel compounds that target previously thought undruggable proteins involved in cancer.
SEOUL 25-27 OCTOBER 2022. The Samsung Global Research Symposium on "Advanced Bioimaging: New Discovery in Life Sciences" is held by the Samsung Science and Technology Foundation, which was founded by Samsung Electronics in 2013, and is the first and largest private funding organization for basic research in Korea. It supports pioneering projects that attempt to define new problems or to solve highly challenging problems
so that the fundamental knowledge gained may lead to technological innovations for the future world.
At the symposium, Lucas presents his group's pioneering work on how signaling activities and their responses to drugs can be accurately predicted in single cells using multi-scale multiplex imaging and machine learning.
Event website: http://samsungstf-grs.science
SEATTLE 17-20 October 2022. The Allen Institute for Cell Science hosts the seventh annual CytoData meeting. Established in 2016, the annual CytoData meeting brings together experts from across the world to address the challenges in cell imaging and analysis. This year’s theme was “Data analysis and deep learning strategies for image-based profiling in cell biology.” Quantitative image analysis is an emerging field that is developing at a rapid pace, and new tools and methods can help accelerate the analysis, yet democratization and standardization is needed to keep at pace. We aim to feature new tools, applications of tools, and new discoveries to bring the image-based profiling community together.
At the meeting, Lucas presents their recent breakthrough study published in Science on how the responses of individual cells to drugs can be accurately predicted in single cells using multi-scale multiplex imaging and machine learning.
Event website: https://alleninstitute.org/what-we-do/cell-science/events-training/cytodata-symposium-2022/
ZURICH 14 July 2022. In a landmark study published in the journal Science, Lucas Pelkmans and members of his group reveal how the signaling activity of individual human cells can be accurately predicted by the subcellular, cellular, and multicellular state of these cells using machine learning approaches. This variability was long thought to be largely stochastic or unpredictable, and demonstrates that spatial context across scales contains a large amount of hidden information to predict single-cell activities. The study also shows that spatial context across scales determines the highly heterogeneous responses of cells to treatment with two drugs used in clinical trials, namely Avutometinib (a first-in-class dual MEK/RAF inhibitor that allosterically inhibits BRAFV600E, CRAF, MEK, and BRAF) and MK-2206 (an orally active allosteric AKT inhibitor). This enabled for the first time a data-driven prediction of the whole spectrum of single-cell responses to these two drugs.