Old solutions to modern problems

1
Old solutions to modern problems

• Natural systems have been evolving for a long
  time
• Millions of years of evolution creates many
  solutions to a problem and lets them compete to
  find the best ones
• Good engineering solutions
• Biological systems can solve many of the
  engineering problems we want to solve
• In many cases, these natural solutions are very
  good
• Performance near fundamental physical limits
• Very power efficient
• Very resource efficient
• In other cases, we can make natural solutions
  better
• Cells can be engineered/connected to respond to
  desired targets in different ways

2
But we must face biological complexity

• We can do lots of things with one cell
• Poke it
• Replace nucleus
• Move it around
• Apply stimuli
• But cells live and operate in complex
  environments!
• Other cells
• Spatial gradients
• Modifications to environment (active)

3
Grand Challenge Increasing N

• Most existing instruments measure either single
  cells sequentially and slowly or many cells in
  aggregate
• To realize the scientific promise, technologies
  and techniques are needed to handle many cells
  simultaneously
• Coordinate
• Control
• Monitor
• By taking advantage of something akin to Moores
  law for biology it is possible to create the
  technological and scientific basis for studying
  complex cellular interactions that form the basis
  for much of biology

4
Cell-based biochemical detection

• Olfactory Sensing
• Monitor electrical activity of olfactory receptor
  cells
• Pathogen Detection
• Monitor cells in real time
• Correlate signatures across time pathways for
  low false positive detection
• Biomedical Applications
• Nanoparticle toxicity screening
• Medical microbots for cancer diagnosis / therapy

5
Grand Challenge Efficiency

• Biological systems often operate at theoretical
  performance limits under extreme resource
  constraints
• Performance can be increased by devoting more
  resources (such as size, power, cost, time)
• The ultimate challenge is to increase performance
  while minimizing resources
• Biology does this well!
• Lessons to be learned
• Fabrication Most engineered systems are
  extremely resource intensive.
• Low power operation Lots of progress made, more
  to come.
• Adaptation/feedback Ubiquitous in biology,
  allows performance despite uncertainties/changes
  in system, environment, task

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Natures nearly optimal