Abstract
“… we are creating the primordial ooze from which new systems of discovery science will emerge.”
As an organization focused on the application of science to the automation of science, ALA seeks to create an autocatalytic ecosystem where technology providers and technology users compete and collaborate. In some sense, we are creating the primordial ooze from which new systems of discovery science will emerge. It is our emphasis on informatics, tying together automation systems with the data that they generate, that distinguishes the field of laboratory automation from traditional methods of hypothesis-driven science and the more recent discovery science.
The analysis of complex, multi-component data from screening runs, microarray data, proteomic mass spectrometry data, flow cytometry, etc. requires new tools. Indeed, the idea of applying clustering algorithms or generating fitness-landscapes with real data is a relatively new phenomenon in the history of science! This is about more than optimization; there is an accelerating feedback loop in which the scientist intervenes to view the results at higher levels of abstraction and tune the experiments to explore particular phenomena in more depth.
Just as evolutionary biologists consider the prerequisites for the Cambrian explosion of life 550 million years ago, and as economists contemplate the explosion in market economies over the last thousand years, we are establishing the prerequisites for an explosive growth of automation of scientific discovery. Definition of standards for hardware (e.g., microtitre plate formats) and software (e.g., AnIML, ELN, LIMS) serve as the DNA for our evolving requirements in discovery science. Any complex adaptive system requires hierarchical organization based on robust, yet variable, building blocks. From this perspective, we may now be in a pre-Cambrian era in which these building-block standards are just emerging. Thus, while the laboratory automation scientist works on the science at high levels of abstraction, the laboratory automation engineer must focus on the nuts-and-bolts materials science, chemical compatibility, and reagent quality issues, as well as the mechanical, optical, electrical, and software components with great attention to detail.
How far can we push autonomous operations in the laboratory? Liquid handling is now quite autonomous of human hands as is transfer of plates from station to station. What new technologies, methodologies, and standards are now emerging and what can ALA do to facilitate this emergent behavior? When will we see the day that scientists specify an HTS run, and the entire run is performed without a human touching anything—scientists just look at the results on a computer screen with 3-D goggles and manipulate the data like Neo in the film The Matrix?
If you have ideas about the science-of-doing-science, please volunteer for ALA committees that impact this evolution, provide feedback to ALA board members, or just go start the company or introduce the new product that fills a new niche in the evolutionary landscape!
Sincerely,
