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 Pamela Abshire

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) Pamela Abshire

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 Moore’s 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 Pamela Abshire

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 Pamela Abshire

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 Pamela Abshire

6. photon shot noise rhodopsin thermal noise biochemical cascade optics signal conductance + + photons photons voltage current + + membrane impedance membrane channels membrane thermal noise stochastic channel noise Nature’s nearly optimal Pamela Abshire