As the current coronavirus crisis evolves, the key question will eventually shift from how we should we manage this pandemic to how can we be better prepared for the inevitable next one. What tools can we develop to make us more agile and effective when a virus strikes again?
One way to analyze dynamic biological systems such as the dissemination of a virus, its mutation rate, and its effect on the human body is through so-called “natural computing.”
Natural computing as a field covers three broad categories where the algorithmic treatment of information (computation) is paired with the natural world:
1. Computational processes observed in the natural realm
A classic example of such processes is the integration of information (both chemical and electrical) accomplished by neurons in the nervous system. At its core, the way a virus attacks an organism and the manner in which the host seeks to respond can be viewed as a battle of information processing techniques: from the highjacking of the machinery by a virus to reproduce and express virulent factors to the coordinate response (in the best of cases) of the host immune system to get rid of it.
2. Human-designed computing inspired by nature
An example of this category is evolutionary computation for which an initial set of candidate solutions is generated and iteratively updated algorithmically to mimic the sequence of mutation and selection first described by Darwin. This field is believed to be leading the way to create autonomous machines that can adapt to their environments. In the case of the fight against a virus, a key element in developing an effective vaccine is to identify the correct epitope to target. One way to achieve this is through epitope discovery and synthetic vaccine design:
With the knowledge of the primary sequence of the protein antigen, the epitopes can be identified by cloning the domains or smaller peptides of the protein separately and experimentally determining which one is more immunogenic, or alternatively, by screening the whole protein sequence using in silico predictions programs.
3. Employment of natural materials for computation
DNA and RNA are increasingly commonly used to store information.
One of the key difficulties of thinking about challenges like coronavirus is that, as Donella Meadows writes, “Systems happen all at once. They are connected not just in one direction, but in many directions simultaneously.” This multi-directionality means that traditional linear logic is ill-suited to understanding and managing complex cell biology, or interdependent supply chains for that matter. Studying the forms of natural computing noted in the first category above can provide insight into computational structures that were “developed” from the ground up to be effective in systems-based interactions. Applying these lessons to human-designed solutions to particular problems may provide better tools for responding our next crisis. And using the substrate of our species can allow this knowledge to persist for generations ahead.
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The Fast Grants program is providing quick funding for COVID-19 related scientific research. The funding is being provided by committed individuals including John Collison, Paul Graham, Reid Hoffman, and others. Learn more here.
The Digitalis Commons Dart Grant program provides quick, targeted grants up to $3,000 to develop public goods for better health. Apply here.
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