Harnessing Lab Digitalization for Sustainable Scientific Progress

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More than ever, greener living is important for individuals but also commercial enterprises. It's no different for labs, as it's an effective way of reducing costs, helping the environment and obtaining respect from others in the industry. After all, sustainability is becoming a major characteristic that role players may consider when evaluating which lab to use.

Sustainability also carries various other benefits for scientific progress. Below you'll find an overview of how lab digitalization is a primary role player in helping facilities become more environmentally friendly.

The Environmental Impact of Traditional Labs

While laboratories are involved with various projects beneficial to people, patients and society at large, outcomes aren't all positive. Traditional labs without a more digitalized system have various characteristics that impact natural resources.

Energy-intensive Processes

Older labs that haven't transitioned to greener practices may use much more energy than modern establishments. From microscopes to ovens and water baths, they all use power and older models aren't as energy efficient as upgraded versions.

Resource-heavy Data Management

Even the management of data can have an environmental impact if traditional labs still use outdated methods. Data management processes that aren't sustainable include:

-        Using IT equipment that's not energy efficient.

-        When old equipment and devices are taken to landfill instead of recycled.

-        Partnering with service providers who can't prove they follow sustainable practices.

-        Having large data centers due to not taking the time to clean up and compress data”this affects carbon emissions and energy consumption related to the lab.


Paper-based Workflows and Waste

In any paper-based work environment, you're impacting the environment by supporting industries that cut down trees and also use other resources like oil, just to produce paper. Paper production also plays a role in air pollution. 

Apart from a big carbon footprint, paper-based systems carry risks:

-        Inaccurate records due to human error

-        Possibility of losing data in fire or due to water damage

-        Lost or stolen documents that cause security concerns

A huge percentage of paper ends up being wasted. Finally, labs not focused on sustainable practices are likely to also have high amounts of single-use plastics on site.


The Role of Lab Digitalization in Sustainability

Luckily, recent years saw a remarkable increase in labs that make digitalization a priority, which can make an establishment's activities much more environmentally friendly. There are various reasons for this, but the tech that enables more sustainable functioning is a huge draw card.


Digital Lab Notebooks and Data Management

An easy solution to having a data management system that's resource heavy is implementing more efficient electronic devices. This can include upgrading to more energy-efficient devices and electronic notebooks.

The lab benefits since there will be lower utility costs but nature also wins in the process. Overall, your data management system won't be as dependent on natural resources anymore.


Paperless Data Recording

The steps towards a greener lab start from the moment you obtain data you need to capture. A device like an electronic lab notebook is designed for this specific application. For example, they have lab-relevant features that enable a smooth workflow. This means higher productivity and the digitalized process is much more accurate than recording data in written form.

Once information is recorded, it can be sent to other points in the lab's network, even role players from other facilities. It's a more accurate and secure system.

In all the steps described above, there's no need to write anything down on paper if you use digital resources like an electronic notebook. It shows how just one device helps a lab step away from the outdated, unsustainable methods of old.


Cloud-based Storage and Collaboration

It's also worth digitalizing all your data so you can then use cloud storage. For the lab it reduces your carbon footprint since you'll need less hardware on site, which in turn means you don't need as much energy and resources to cool the hardware you use.

In terms of the bigger picture, cloud-based storage also enables you to engage with other role players much easier. Interaction can happen without the use of paper and cloud-based collaboration can also take place with minimal energy use.

Data Analytics and AI for Sustainability

Labs can further optimize their goals of reducing their carbon footprint by harnessing the power of AI and analyzing data to identify the best way forward.

Predictive Analytics for Resource Optimization

Using AI and predictive analytics, labs can manage their resources and equipment much better. For example:

-        AI can collect and track performance data of assets like machines and other equipment. Analysis can show when it's necessary to intervene and maintain a certain asset in order to increase its lifespan. Proper maintenance can lead to more energy efficiency AND fewer assets ending up in landfill.

-        With AI and predictive analytics it's much easier to manage inventory and your supply chain. For example, place orders in such a manner that you minimize your carbon footprint related to storing items and transporting them. This is especially relevant for labs that order items that are kept refrigerated while being transported, as this uses a lot of energy while in transit. You can use AI to schedule the lowest number of deliveries per month, without risking not having certain items on hand for lab use. 

Machine Learning for Waste Reduction

In many industries machine learning is used to reduce the chance of human error. This can also be done in certain steps of lab work. As a result, there will be fewer mistakes which leads to fewer resources, such as chemicals, being wasted.

AI-driven Green Chemistry Research

Green chemistry research refers to processes aimed at discovering products and processes for which hazardous substances aren't necessary. For various steps in a product's life cycle”production, utilization and disposal”ideally no dangerous substances should be required or released. This has various positive outcomes, such as limiting harm to the environment and humans.

Towards this goal, AI makes it possible to speed up research, since it can analyze a mass of data much quicker compared to scientists doing it manually.  


There's no question that digitalization has multiple benefits, making it worth the effort and investment. It's also encouraging to know better functionality CAN be paired with green benefits.

Having the right resources like electronic notebooks will help streamline workflows and boost productivity”without harming the environment.

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