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Ten future challenges for synthetic biology.

Olivia GallupHia MingTom Ellis
Published in: Engineering biology (2021)
After 2 decades of growth and success, synthetic biology has now become a mature field that is driving significant innovation in the bioeconomy and pushing the boundaries of the biomedical sciences and biotechnology. So what comes next? In this article, 10 technological advances are discussed that are expected and hoped to come from the next generation of research and investment in synthetic biology; from ambitious projects to make synthetic life, cell simulators and custom genomes, through to new methods of engineering biology that use automation, deep learning and control of evolution. The non-exhaustive list is meant to inspire those joining the field and looks forward to how synthetic biology may evolve over the coming decades.
Keyphrases
  • deep learning
  • machine learning
  • artificial intelligence
  • quality improvement
  • oxidative stress
  • convolutional neural network