Alpha Cell
Alpha Cell is SciLifeLab’s effort to create predictive models that explain how human cells function, adapt and transition in disease.
By integrating cutting-edge life science technologies and advanced computation, the program turns cellular complexity into experimentally validated knowledge and understanding of cells in health and disease.
About
Life science is moving from a largely descriptive data collecting discipline to one driven by quantitative molecular data. This vast and complex data landscape provides the foundation to use artificial intelligence (AI) to predict living systems, and then molecularly engineer them – either to prevent cellular dysfunction in disease or steer the cell back to normal function. With sufficient explanatory prediction power, it should also be possible to engineer cells into therapeutic tools.
SciLifeLab is at the forefront of this data and AI transformation. Through its strategic research program Alpha Cell, SciLifeLab will take advantage of the convergence of advanced AI, large inventories of molecular data and disruptive imaging technologies to map cells at unprecedented molecular scale. These molecular maps will lay the foundation for predictive AI cells models.
The new research ecosystem will invest in and leverage SciLifeLab infrastructure and includes recruitments at all levels. Alpha Cell data and models will be managed using FAIR data principles.
The program is made possible through generous support from the Knut and Alice Wallenberg Foundation.
The program is planned over five strategic phases:
1. Human Protein Atlas
Build a foundational model of protein distribution.
The program begins by leveraging the Human Protein Atlas (HPA) data to create a foundational generative AI model to predict the metabolic functions of human cells. This phase serves as a proof-of-concept, using high-quality cellular and subcellular multi-omic data to identify which molecular information is most predictive of cell behavior and where critical biological data gaps still exist.
2. Space
Build a molecular resolution 3D reference data set for the human cell and generate a foundational spatial AI cell model.
The second phase introduces a spatial dimension by building a 3D molecular-resolution data set using the latest advances in light and electron microscopy. The data will be generated from the same cell types included in the HPA, providing the opportunity to arrive at a hybrid spatial AI model integrating multi-modal spatial and molecular data.
3. Time
Build a single molecule precision temporal reference data set for the human cell and generate a foundational temporal AI cell model.
Recognizing that current protein data is largely static, phase 3 focuses on capturing the “fourth dimension”: time. This stage involves developing time-resolved, quantitative imaging methods to observe the transitions between different functional states in living cells. Detailed spatial and temporal information will be used to build a foundational temporal AI cell model.
4. Future
Build a molecular-space-time foundation AI cell model to predict future cell states.
In this phase, the aim is to develop the model into a 4D integrated system that predicts future cell states. This process will be highly iterative; the model will be used to identify what new data modalities are required to make the most accurate predictions for human cell health and disease.
5. Control
Translational application of Alpha Cell to predict the key molecular handles that gives us control to maintain health and recognize and prevent disease.
The final phase shifts from prediction to intervention or control. The mature model will be applied to recognize and control the earliest molecular shifts toward pathology, allowing for cellular transitions to be caught before disease takes hold. Ultimately, this enables rational cell engineering: the ability to steer diseased cells back to a healthy path or design artificial human cells as curative agents.
Program Organization
Alpha Cell is led by Coordinating Principal Investigators Jan Ellenberg, Director of SciLifeLab and Mathias Ulhen, Director of the Human Protein Atlas.
The program is managed by Caroline Gallant (science), Isolde Palombo (coordination), Carina Gustafsson (controller).
Advisory Board
The Alpha Cell Advisory Board provides scientific and strategic guidance to the Coordinating PIs.
| Gunnar von Heijne | Professor of Biochemistry at Stockholm University |
| Göran Sandberg | Knut and Alice Wallenberg Foundation |
| Ilaria Testa | Professor of Applied Physics at KTH Royal Institute of Technology and SciLifeLab |
| Anders Ynnerman | Professor at Linköping University and Director of Visualiseringscenter C in Norrköping |
| Siv Andersson | Professor of Molecular Evolution at Uppsala University and affiliated with the Knut and Alice Wallenberg Foundation |
| Johan Elf | Professor of Physical Biology at Uppsala University and SciLifeLab Group Leader |
| Carolina Wählby | Professor at the Department of Information Technology at Uppsala University and SciLifeLab Group Leader |
Funding
The program is made possible through generous support from the Knut and Alice Wallenberg Foundation.
More information: press release (November 7, 2024)
Interest in knowing more or getting involved? Contact alphacell@scilifelab.se