Automation in biotechnology: a student’s perspective

Automation is a common buzzword in both intellectual discussion and chats in local pubs — whether its discussing the latest AI gossip or almost anything in the Musk-Testla sphere of conversation. The word seems to be a on the lips of every futurist, engineer and economist and reflects the preliminary stages that must be taken by humanity to truly conceptualise automation and uncover the many threats and the many more benefits associated with the technology.

High throughput, minimal human error, efficiency, economic viability and reproducibility. These are words that are commonplace in the literature and writing I have encountered in the bio-engineering degree I am currently taking. The factors can be viewed individually as singular factors that can potentially by addressed and improved by automation. Biotechnology is a sector that is full of natural and human error, limited success from an experimental perspective, and a notably low amount of laboratory reproducibility — with 70% of experiments unable to reproduced in a 1576 experiment-wide study by Nature. Human error, and in turn the ‘crisis’ in the lab-based science world currently being presented by low reproducibility, is a historical problem that could be effectively eliminated by automation — in turn increasing the efficiency and turnover of discoveries which increases the economic viability of a process. If viewed from a business viewpoint, automation cannot come quickly enough.

Robotic automation equipment. Credit: Coghlin Companies

The experiments that have been assigned to me over the course of my degree are of a surprisingly algorithmic nature — leading me to see this set of instructions as something anyone, or anything, could perform providing that they have the correct chemicals/microbial culture available, know how to use laboratory apparatus, and maintain sterile conditions. Simple, algorithmic instructions are something that computers can do with ease and, providing a computer has the tools for an experiment, there are no obvious visible barriers (apart for the current cost of these systems) to automating the lab work I have encountered over the last few years. I envisage that future students should be learning the mechanics and programming these machines so that, when it comes to doing this same experiment or analytical technique 1 year after initially learning the protocol, students can recall the programs they’ve written. This will undoubtably stand as advantageous to students as they can count on the reliable reproducibility of machines instead of trying to remember how many times they shook the test tube in a experiment laced with human error to the extent where the results obtained in the study deem the investigation inviable — something I know far too well from experience. This program-based method of experiment in biotechnology will also improve error identification in a team’s lab work as it can be easily viewed inside the program exactly what was done, in what order, to a high level of precision providing the apparatus is in working order.

The automation I have outlined so far, if implemented, will improve relationships in the scientific community as the experimental process becomes a lot more transparent and interpretable. If every article that one reads as a part of the research process came with a subsidiary file that contained the precise methodology of the experiments carried out in the form of a page of script (which could easily be compressed into a more interpretable format), collaboration would be far more effective. Teams could create a an experiment based on other studies by what would be effectively “copying and pasting” parts of experiments to construct an experiments to the parameters and variables outlined by their assignments. If the results of team’s studies are connected to the experimental data, one could theoretically simulate the newly fabricated experiments using and cross-referencing the data in the studies that “copied and pasted” to create the new experiment.

Though inevitable technological advancement within the biotechnology sector, the ideas that I have presented, or ones similar to these ideas, or ideas completely different to mine can and will become a reality. The fact that people are thinking about the futurist direction that biotechnology is likely to take is extremely important as some of the vital prerequisites to adoption of new technology have already been conceptualised. I believe that thinking and dreaming about the future this sector can only benefit the industry and humanity as a whole. After all, the people dreaming now will most likely be the innovators responsible for effective and successful technological evolution within this exciting sector.