India is well placed to innovate on existing openensource opportunities
Bioinformatician & Curriculum Developer, University of Edinburgh, UK, currently working in collaboration with the Gujarat Biotechnology University, Gandhinagar
Automation in the lab is a hot topic in the life science sector. Conventional thinking points to two options: either spend large sums on proprietary equipment or subscription model software which usually offer more options than are really required, or wait for equipment and automation to become affordable, which may take decades.
A third way is possible: Using open-source resources to do it yourself. The challenge to any scientist or lab with a restricted budget is not one of being unable to automate, but a lack of awareness of how simple some of these automation pipelines can be to implement. It has been estimated that up to 89 per cent of recent published life science investigations have at least one method that can be automated. Many of these do not need the purchase of proprietary software and equipment.
When time is spent in exploring open-source options, labs often find how quickly their daily routine could be accelerated through open-source software. Through learning of simple programming
the vendors and demand hands-on expertise before investing in a digital solution.
In addition, research institutes across India can help the scientific community by establishing centres of excellence (COEs), in collaboration with the industry, for encouraging and simplifying the adoption of new technology.
“Increased automation is inevitable in labs, as it is in manufacturing, indeed in all walks of life. While the initial cost and maintenance are limiting factors, they must be balanced against increased productivity, precision and accuracy. Automation takes human errors out of the equation, a critical need in the life sciences. Partnerships with suppliers of computer hardware and software can help mitigate costs and enhance functionality”, points out Dr R. Nagarajan, skills powerful data analysis pipelines can be created. Inexpensive controllers such as Raspberry Pi or Arduino allow for equipment to run independently, link and manage data, and allow experiments to run remotely and semi-autonomously. These are not fancy or high-tech solutions, but a synthesis of existing open source and low-cost products. More advanced, but no more complex, options include the Opentrons modular robotics suite, which when paired with technologies such as OpenWorkstation, offers a bespoke and flexible automated lab for less than $7000.
Investigating and testing these takes some time. But once done, the savings in time, labour, and material wastage all result in more efficient labs that can produce high quality, precise, and reliable data faster. The costs are also much more manageable, being a one-time expense rather than a subscriptionbased service cost. Automation can be driven by the bespoke needs of a laboratory, and through collaborations and customisation be scaled to keep pace with global competitors.
Where to start? The threshold to adopt automation may appear high, but if employees have already been trained in and applied it to real-life laboratory challenges during their training, adoption is much easier. Research and technology-driven higher education institutions seeking research collaborations with industry are spaces where such innovation can be developed and put to both academic and commercial use. Importantly, they train your future employees in application and optimisation of automation for solutions to your challenges. India is well placed to nurture these collaborations and innovate on existing open-source opportunities.
Professor & Head, Department of Chemical Engineering, Indian Institute of Technology (IIT), Madras.
Thus digitisation is not only transforming the industry and academia, it is also changing the people within it. Data scientists, engineers, and experts in AI and ML are now in high demand. Even those working within clinical roles must now have a working knowledge of the scope and purpose of key digital tools.
This calls for the establishment of skilled courses for people who are looking to pursue or grow their career in R&D. They must be literate in the latest technology and prepared to commit to lifelong learning to keep pace with change.