Computational Tools for Accelerating Regenerative Medicine
Cell therapy has arisen as a leading approach to tackle tissue regeneration. It involves the direct transplantation of cells to compensate for those lost. In some cases, it is possible to extract healthy cells of interest from the patient or donor and grow them ex vivo for transplantation; however, in most cases, growing cells in sufficient quantities for transplantation is difficult because our cells do not have enough growth capacity, a challenge shared across all cell therapies.
The combination of high-resolution data, computational power and novel algorithms in computational biology, is enabling the development of more efficient cell reprogramming methods, as well as support the development of in vivo cell transdifferentiation and transform current cell therapies toward shorter, safer, and more robust strategies.
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