Digital Transformation of the Laboratory. Группа авторов. Читать онлайн. Newlib. NEWLIB.NET

Автор: Группа авторов
Издательство: John Wiley & Sons Limited
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Жанр произведения: Химия
Год издания: 0
isbn: 9783527825066
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1.1).

Schematic illustration of the complex, multivariate concept of lab transformation.

      1.2.1 People/Culture

      The LotF and the people who work in it will undoubtedly be operating in an R&D world where there is an even greater emphasis on global working and cross‐organization collaboration. Modern science is also becoming more social [3], and the most productive and successful researchers will be familiar with the substance and the methods of each other's work so breaking down even more the barriers to collaboration. These collaborative approaches will foster and encourage individuals' capacity to adopt new research methods as they become available; we saw this with the fast uptake of clustered regularly interspaced short palindromic repeat (CRISPR) technology [4]. “Open science” [5] will grow evermore important to drive scientific discovery. This will be enabled through the increased use of new cryptographic Distributed Ledger Technology (DLT) [6], which will massively reduce the risk of IP being compromised [7]. The LotF will also enable more open, productive, collaborative working through vastly improved communication technology (5G moving to 6G) [8]. The people working in these labs will have a much more open attitude, culture, and mindset, given the influence of technology such as smartphones on their personal lives.

      1.2.2 Process

      The lab processes, or “how” science gets done in the LotF, will be dominated by robotics and automation. But there will be another strong driver which will force lab processes and mindsets to be different in 5–10 years time: sustainability. Experiments will have to be designed to minimize the excessive use of “noxious” materials (e.g. chemical and biological) throughout the process and in the cleanup once the experiment is complete. Similarly, the use of “bad‐for‐the‐planet” plastics (e.g. 96/384/1536‐well plates) will diminish. New processes and techniques will have to be conceived to circumvent what are standard ways of working in the lab of 2020. In support of the sustainability driver, miniaturization of lab processes will grow hugely in importance, especially in research, diagnostic, and testing labs. The current so‐called lab on a chip movement has many examples of process miniaturization [9]. Laboratories and plants that are focused on manufacturing will continue to work at scale, but the ongoing search for more environmentally conscious methods will continue, including climate‐friendly solvents, reagents, and the use of catalysts will grow evermore important [10]. There will also be a greater focus on better plant design. For example, 3D printing [11] could allow for localization of manufacturing processes near to the point of usage.

      In the previous paragraph, we refer to “research, diagnostic, and testing labs” and to manufacturing “plant.” We believe there is a fundamental difference between what we are calling hypothesis‐ and protocol‐driven labs, and this is an important consideration when thinking about the LotF. The former are seen in pure research/discovery and academia. The experiments being undertaken in these labs may be the first of their kind and will evolve as the hypothesis evolves. Such labs will embrace high throughput and miniaturization. Protocol‐driven labs, where pure research is not the main focus, include facilities such as manufacturing, diagnostic, analytical, or gene‐testing labs. These tend to have a lower throughput, though their levels of productivity are growing as automation and higher quality processes enable ever higher throughput. In these labs, reproducibility combined with robust reliability is key. Examples in this latter area include the genomic screening and testing labs [12, 13], which have been growing massively in the past few years. For these labs the already high levels of automation will continue to grow.

Schematic illustration of the virtual and real design-make-test-analyze concept.

      1.2.3 Lab Environment and Design

      1.2.4 Data Management and the “Real Asset”

      It is true of 2020, just as it was 50 years ago and will be in 50 years time, that the primary output of R&D, in whatever industry, is data. The only physical items of any value are perhaps some small amounts of a few samples (and sometimes