Lab Manager | Run Your Lab Like a Business

Managing Analytical Workflows

Associate editor Rachel Muenz speaks with research scientists Freya Freestone, MChem, and Helen O'Shea, BSc about data processing, analysis, and managing workflows in the lab.

Rachel Muenz

Rachel Muenz, managing editor for G2 Intelligence, can be reached at

ViewFull Profile.
Learn about ourEditorial Policies.
Register for free to listen to this article
Listen with Speechify

Freya Freestone, MChem (left), has been a scientist at Chiesi UK since graduating from Oxford in 2009, taking on the additional role of Waters’ software systems administrator in 2011. Freya has extensive experience as an innovator with Waters’ Empower 3, NuGenesis 8 SDMS and ELN informatics systems, working magic with her forms to further improve the paperless laboratory.

Helen O’Shea, BSc (right), joined Chiesi’s UK Centre for Drug Delivery Technologies in 2009, specializing in innovative research into therapies for respiratory diseases. In addition to her role as a scientist, Helen was instrumental in the development of the center’s paperless data system, implementing strategies for removing timeconsuming aspects of data processing and analysis from the laboratory workflow.

Get training in Lab Quality and earn CEUs.One of over 25 IACET-accredited courses in the Academy.
Lab Quality Course

Q: What does your lab do?

A: O’Shea: Our lab is a research and innovation center focusing primarily on respiratory drug delivery technologies and formulations [such as those used for asthma treatments]. Chiesi is a family-owned pharmaceutical company based in Parma, Italy, with more than 500 employees in Research and Development at five different sites. Our lab is in the UK, based in Chippenham, and there are 11 of us here.

A: Freestone: A focus of our lab is a fast-paced, low-momentum workflow. We are not a GMP [good manufacturing practice] facility, as the emphasis is on concept generation and early-stage research: having an idea in the morning and putting it into practice in the afternoon.

Q: What are the main analytical technologies you use? What are they used for?

A: Freestone: The most common techniques we use are Waters’ UPLC [ultra performance liquid chromatography], and either a PDA [photodiode array detector] or an SQD [single quadrupole mass detector] for sample quantification of API [active pharmaceutical ingredient] content. We have developed assays for combinations of multiple APIs.

A: O’Shea: Primarily we use UPLC for quantification and carry out very little qualitative testing. Use of the SQD allows us to identify the API by mass, which removes some of the challenges associated with PDA assays. In addition, we use a number of techniques for physical characterization of material: TGA [thermogravimetric analysis], DSC [differential scanning calorimetry] and DVS [dynamic vapor sorption].

Q: What tools do you use to manage your analytical workflows?

A: Freestone: All of our analytical procedures are documented within an ELN [electronic laboratory notebook], from preparation of samples, via experimental details, to analysis of results and comparison with other data. We use Waters’ Empower 3 software for analyzing and reporting UPLC data to quantifying the API content within our samples. The raw data and sample reports are stored within Waters’ NuGenesis 8 SDMS [scientific data management system] software, which allows us to transfer information and extract data without typing or copying anything. We also use this software as an archive. Waters’ NuGenesis 8 ELN is used to create, edit, view, and store all of our projects, protocols, and related data.

A: O’Shea: The ELN replaces the traditional paper notebooks that many labs use. We never write anything down on paper and we have literally no paper in the lab.

A: Freestone: The ELN also incorporates an inventory system, which we use for stock management and solution preparation, as the forms can interact with the inventory to update stock levels. This means we don’t use an external LIMS [laboratory information management system].

Q: What are the key challenges you face in your analytical workflow?

A: O’Shea: Maintaining the pace of our workflow. Our aim is to stay ahead of the game and generate data quickly, analyze it, and make decisions about the next activity. We do that first by avoiding many of the activities that are associated with data management, for example the manual transcription of information when using paper notebooks, and as a consequence, [we avoid] extra checking and signing off.

A: Freestone: I would also add to that the speed and flexibility aspect. We prefer to use a streamlined process for approval of experimental protocols that is as smooth and swift as possible. The aim is to be able to work out what we want to do, and then go in [the lab] and get started straightaway.

A: O’Shea: Something that every lab has to think about is how to maintain the value of data, data retrieval, and the reuse and reinterpretation of data. Having searchable and traceable data was a big consideration for us, particularly when we started in 2009, but it’s obviously ongoing as our data grows every day.

A: Freestone: So, for example, we have the capability to bring up every single experiment that we’ve tried out on a particular batch of inhalers and compare the data from each of those experiments within seconds. Working within the ELN means that our work is automatically date-stamped and signed off using e-signatures, which is particularly important in an innovative environment that may be concerned with the creation and defense of IP [intellectual property].

Q: Aside from the ELN, are there any other ways that you’re dealing with those challenges?

A: O’Shea: The use of state-of-the-art analytical equipment, such as the Waters ACQUITY UPLC systems, means that our analytical methods are far quicker than previous methods, therefore we are generating data at a faster rate. We also have a number of templates for all our routine work that help with the automation of data movement and also with the comparison of old data with new data. If you ask three or four different people to make a form for filling in information, they’ll all do it differently, which can become quite confusing. Standardizing our forms means that data from similar types of experiments are presented in the same way.

Q: What key changes have you experienced in your analytical workflows over the past few years?

A: Freestone: When the laboratory opened in 2009, we primarily focused on research into pressurized metered- dose inhalers. More recently, we began on-site research into dry powder inhalers, which has involved the setup of a second laboratory with a whole range of different experimental capabilities, and the development of the forms for the workflow to go with those.

A: O’Shea: Since then, I think the main change we’ve been through over the past few years is the upgrading of all of our IT systems. When we started in 2009, all our computers were on Windows XP. Of course, we had to upgrade in 2013 to Windows 7, and that involved changing every piece of software that we had.

A: Freestone: That was a big situation because we had to make sure all the software was compatible and that we could still access our historical data and ensure everything was secure and working. We managed to get that done with the help of Waters engineers. The laboratory was down only two days.

A: O’Shea: During the week of the upgrade, we had two systems running so we could revert straight to the backup system if we upgraded everything and it didn’t work, but it all went really smoothly. I think it’s one of the big successes over the past few years.

Q: What advice do you have for other laboratory professionals or managers who are looking at improving their workflows?

A: Freestone: I would say that if you’re trying to look at how workflows can be improved, then talk to the people who actually carry out the task, because something obvious to someone who’s doing it every day might not be obvious to someone who doesn’t do that task or activity.

A: O’Shea: Something that Freya and I found particularly useful when we were setting up various automated workflows for our routine experiments was that we are both scientists with experience carrying out those experiments. We already knew what order to put the different steps in and where we could save time. Freya also recently set up an inventory system within our ELN and she worked really closely with our technicians to do that. They helped her troubleshoot it quite successfully. Training is also very important.

A: Freestone: I found training people on demo versions of the forms that they would be using was really useful because they got hands-on experience in a demo environment, so if anything went wrong, it wouldn’t actually upset anything.