Automation, IoT and the future of smarter research environments

Technology and automation can be utilized to drive high quality and effectivity in manufacturing processes, enhancing drug growth by way of knowledge evaluation, course of monitoring, and steady suggestions.

Big data, paperless processes, automation and cloud technologies are driving the laboratory informatics trade ahead, creating smarter research environments which might optimise and guarantee the high quality and integrity of knowledge.

Through the use of automation, and good expertise, R&D specialists can alleviate the burden of many of the time and labour intensive duties similar to handbook knowledge entry and retrieval. Their time can then be used to concentrate on actions that leverage their experience.

Ahead of their participation in the SmartLab Forum 2018, Pharma IQ spoke with Benjamin Schulz, Project Lead , Fraunhofer Institute for Manufacturing Engineering and Automation IPA and Jonas Angstenberger, Head of Process Automation & Data Science, AbbVie as a way to hear their ideas on how automation and related units can help with making certain knowledge integrity and form the future of the R&D setting.

Benefits of automating pharmaceutical research environments

Smarter research environments help with the repeatability of research by decreasing the human issue and human error in the course of and exams. they will additionally dramatically improve the high quality of merchandise by way of the standardisation of methods.

Schulz explains that “the accuracy of automated dispensers is improving, and this reduces the cost of kits and material in the laboratory”. He additionally commented that the volumes wanted for research may be decreased with the elevated use of automation.

However, Angstenberger notes that “automated environments demand a different set of skills”, one thing which is essential to think about throughout implementation and has value implications in phrases retraining or hiring new individuals.

He notes that “there are several papers that state organisations will need a year or even longer to train people in such a scenario”.

Industry 4.0

New instruments and processes are enabling good, decentralised manufacturing, with built-in IT methods and IoT related R&D environments turn into more and more versatile and extremely built-in. This new wave of technological advances will drive ahead the subsequent part of pharmaceutical manufacturing, enabling larger visibility of operations and permitting for agility in processes, bringing connectivity of gear, individuals, providers, and provide chains.

With the development of automation, there’s extra performance to combine these methods.

“I think IoT devices are very rare in the lab at the moment” Angstenberger explains.

“We are looking at small automation islands such as liquid handling systems”. The implementation of these methods can be closely reliant on a robust IT infrastructure, with elevated numbers of companies transferring in direction of automation, the IT setting is altering. It can be essential that senior administration are conscious of the particular IT setting that’s wanted to deal with automated methods, together with the use of non-public cloud-base software program.

Cost vs Benefits

The definition of IoT may be fluid and due to this fact establishing the value advantages of buying such units is extremely depending on what an organisations considers to be an IoT enabled machine. Irrespective of this, there are a selection of advantages of introducing these units into the research setting and as soon as an organisation has invested in automation, it’s typically a lot safer and extra agile in the research course of.

Angstenberger explains {that a} key profit of related units is that “there are cost implications if there are a higher number of errors when doing things manually, and lower costs if you automate.”

“The whole environment will need to adapt and choose different analytical methods based on results, and this is a huge challenge,” explains Angstenberger. Although this may incur preliminary funding prices, the different is to hold out the processes manually which is able to doubtless imply decrease throughput and a decrease high quality with exponential long-term prices.

Using automation to make sure knowledge integrity

In the previous, handbook knowledge dealing with meant copying the uncooked knowledge recordsdata collectively into one merged file, and “inevitably this manual process incurred a number of mistakes,” says Angstenberger, including that in the starting, “these mistakes are not always recognised and it is nearly impossible check all these processes manually”.

Documentation processes which might normally take two weeks when carried out manually can now be accomplished in ten to fifteen minutes, demonstrating the apparent time advantages of automation.

Schulz explains that “data is automatically collected and directly imported into a server where you can watch and analyse it, and therefore reduce the chance of errors compared to using paper to report data”.

However, he additionally notes that that “one remaining problem with automated data handling is that it’s missing standardisation in the data format”, that means that whereas it’s much more environment friendly to mechanically accumulate the knowledge and import it into the server, there’s nonetheless a problem with metadata as the format is just not standardised.

Schulz echoes Angstenberger’s statements, including that “if the data is just collected and nobody works with it, then the benefits of automation are limited”.

Security dangers with IoT units

Security may be a difficulty with connected IoT devices, notably with regards to storing knowledge on exterior platforms, “most often IoT is associated with importing the data into a worldwide specific cloud, and that’s not necessarily secure,” says Schulz.

The safety of exterior storage is extremely dependant on the cloud infrastructure. Angstenberger notes that “in general, I believe it’s not particularly well accepted to have data stored outside”.

An growing a quantity of firms are utilising in-house cloud storage software program which might scale back safety dangers, though it is very important notice that even with in-house storage, each desktop have to be safe as a way to guarantee the safety of the total community.

Integrating Automated Systems

“In a perfect world everything would be standardised and the risk of siloed systems would be minimal,” says Schulz.

It is vital to ascertain integration requirements in the laboratory, not solely as a result of it’s one thing which is extremely valued by the buyer, but additionally in order that standardisation is ensured between units and there’s standardisation all through the knowledge format. However, to make sure that every thing is working inside an organisation’s automation line, a separate community is required, and due to this fact on this sense firms are remoted and with out outdoors contact, making integration tougher.

Angstenberger explains that communication paths blocked with firewall methods can forestall absolutely built-in automation, “you run into issues with very old-fashioned drivers for outdated environments that have strange communication paths which aren’t particularly functional”. He defined that at AbbVie they understood the must be separate however on the different hand there wanted to be a connection to the outdoors world by way of a firewall. After intensive discussions about the IT infrastructure they’re now trying right into a particular infrastructure that helps automated units.

Future digital transformation

Looking forwards, Schulz believes that “digital transformation will assist people in the lab during the manual steps, tracking the manual steps executed by a person, and automatically generating the protocols”.

It is probably going that automated aiding methods will turn into extra commonplace, as R&D environments require elevated ranges of flexibility which automation alone can not fulfil.

“Moving forwards having a strong network is a basic necessity, if you don’t have a strong network you will not be able to organise your automation workflow” says Angstenberger.

All data on IoT units is communicated by way of the community, so if the community fails or one ingredient breaks down, this could have repercussions for the relaxation of the laboratory. Schulz expressed optimism about future reliance on community strength, commenting “hopefully fail safe systems are something which will be coming soon”.

In extra technologically superior industries similar to the automotive trade, automated methods implement an automatic determination based mostly on predictive analytics algorithms.

In the pharmaceutical trade that is nonetheless a great distance off, however could be a “huge step forwards because you could automate operational decisions in an R&D lab” says Angstenberger.

This is one thing that may very well be launched in a standardised vogue in an automatic situation however it’s not more likely to be launched into labs inside the subsequent few years.

Final Thoughts

Automation and IoT methods can doubtlessly remodel processes inside pharmaceutical manufacturing amenities, serving to to understand main efficiency enchancment. Companies that take the initiative early stand to realize the greatest competitive benefit, making certain that they will function with larger agility, cost-efficiency and compliance.

The SmartLab Forum 2018 will concentrate on the future of IOT and SmartLab Technologies in addition to overcoming LIMS interoperability challenges and knowledge transformation.

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