The pandemic has revealed how much work there is to do in advancing and protecting human health. More than 2.5M people died after infection with SARS-CoV-2 and millions more suffer from its long-term effects. The costs to individuals, families and society are immeasurable.

But the pandemic has also revealed what a difference a scientific breakthrough can make. The scientific and pharmaceutical communities developed revolutionary mRNA vaccines on timescales 10 times faster than was previously thought possible. This advance is saving millions of lives and preventing millions of lost person-years of disability and distress.

We need a new platform – a ‘tissue time machine’ – that can profile tissue states and predict transitions between states (‘Delta Tissue’ or ‘ΔT’). The platform would provide quantitative, multi-scale, multi-modal information sufficient to build integrated prediction models of key cell and tissue states and transitions. If we are successful, we’ll be able to intervene in diseases earlier and with approaches that are targeted to the individual. We’ll also have an improved understanding of the mechanisms that drive disease, which, in turn, will provide more opportunities for intervention. If we succeed, we’ll begin to eradicate the stubbornly challenging diseases that cause so much suffering around the world.

Such a platform is now possible if we combine the latest cell and tissue profiling technologies with recent advances in machine learning and other computational methods. With this foundation, we can now imagine the tissue time machine, which assembles a rational set of profiling modalities, integrates their outputs and builds predictive models of tissue states and transitions.

 To demonstrate and validate the ‘tissue time machine’, we have chosen to develop, test, and validate our platform in biomedical contexts that are as broad as possible: an infectious disease, tuberculosis (TB), and two different cancers, triple-negative breast cancer (TNBC) and glioblastoma multiforme (GBM). Each represents a current, unmet biomedical challenge and features a complex, dynamic set of cell and tissue states and transitions. See the full program announcement for more information. Advances across models and measures should inform each other to improve and validate predictive markers, environmental influences and optimize the key ingredients necessary for promoting healthy network development. It is not necessary to form a large consortium or team to do this. Synergies and integrated system demonstrations will be facilitated by Wellcome Leap on an annual basis as we make progress together towards the program goals.

We are soliciting abstracts and proposals for work over 3 years (with a potential additional one-year option). Proposers should clearly relate their work to one or more Platform Goals and indicate which of the Program Demonstration Areas (PDAs) they will participate in. Additional PDAs can be proposed, but all performers must validate their work against at least one of the specified PDAs.

Deadline for Abstracts: May 17, 2021. Duke Faculty interested in applying should contact vera.luck@duke.edu before proceeding.