VOLUME 24 MARCH

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56 132 VOLUME 24 MARCH 2020

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G.I.T. Laboratory Journal 1/2020 Due to the attention on data integrity,

focus has shifted towards provision of evidence to reviewers that no improper operations were performed with respect to analytical results. However, this ap proach represents a policy of punishing any practice that appears suspicious, which is a major departure from the ap proach used in previous investiga tions[4]. This approach applies to both chromatography and spectroscopy sys tems, meaning the conventional ap proach cannot be used to ensure appro priate compliance.

Advantages of a Unified

Software Platform

Considering that data integrity compli ance for spectroscopy systems could present a major obstacle for operating analytical laboratories in a regulated en vironment, there is a need for an innova

tive approach to ensuring data integrity that solves such problems.

Reasons for one software platform: ▪ One software to learn

▪ One software to manage ▪ One software to update

Summary

Management of different instrumenta tions like UVVis, FTIR, RF, ICPMS, chro matographic, or TOC equipment etc. with one common software platform enables addressing of compliance issues in a uni vocal way, by having a single log. Harmo nized procedures and immediate trace ability of the data as well as a simple and quick consultation of the event register are highly valuable during inspections or audits. Finally, one software solution is easier to administrate, maintain by ITde partment and handle by operators.

Contact Johannes Hesper Shimadzu Europa GmbH [email protected] References: https://bit.ly/WAS-Hesper Fig. 1: GMP - data integrity requirements

Typical Innovation

Equipment Chromatography Spectroscopy Chromatography and Spectroscopy

Data Acquisition Yes - Yes Yes

Data Management Yes Yes - Yes

Audit Trail Yes - Yes Yes

User Yes - Yes Yes

Security Yes Yes Yes Yes

Time Stamp Yes Yes Yes Yes

Remarks 3x Systems to manage 1x System to manage

Tab. 1: Typical data integrity in laboratories having chromatography and spectroscopy equipment like FTIR, UV-Vis or RF next to LC or GC systems.

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Spectroscopy

19

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G.I.T. Laboratory Journal 1/2020 model is required, adding the new inter

ferents to the data base. These undesir able features can be overcome, however, by going one step further in the number of mathematical dimensions of the mea sured data.

The Mathematical View

From a mathematical perspective, spectra can be viewed as vectors (lists of numbers one below each other). However, more complex data can be measured and pro cessed, and this is when we move to the multiway calibration field. For example, a liquid chromatograph hyphenated to a di ode array detector is able to measure a data table for a given sample, i.e., a data matrix. Its columns are UVvisible spec tra, each of them collected at a different elution time. In an analogous fashion, a gas chromatograph with mass spectral detection can measure a data table whose columns are mass spectra. One could also employ a fluorescence spectrophotometer to measure an excitationemission fluo rescence matrix for each sample. Its col umns are emission spectra, each of them collected at a different excitation wave length. Scanning emission spectra at vari ous excitation wavelengths is today possi ble in a matter of seconds using modern fastscanning spectrofluorimeters. Less popular in industrial laboratories, fluores cence matrix spectroscopy has played a

major role in developing multiway cali bration, and is highly appreciated in sci entific research. In principle, the com plexity and number of data modes (the independent directions of a data array) can be increased, and some developments have been described by processing three and even fourdimensional instrumental data per sample. However, this higher multiway protocols are still in their infan cy regarding their mathematical under standing and potential analytical advan tages.

Fig. 1: Hierarchy of data structures and nomen-clature. For a single sample, univariate data are scalars (zeroth-order), multivariate data are vec-tors (first-order) and beyond, and multiway data are matrices (second-order), three-dimensional arrays (third-order) and additional, not shown, higher-dimensional data. For a sample set, the corresponding data arrays are named as one-, two-, three- and four-way arrays respectively.

Fig. 2: Univariate chromatogram for a mixture of polycyclic aromatic hydrocarbons, carried out accor-ding to the official protocol, and involving fluorescence detection at a single wavelength and solvent gradient. FLT, fluoranthene, PYR, pyrene, CHR, chrysene, BaA, benzo[a]anthracene, BbF, benzo[b ]fluo-ranthene, BeP, benzo[e]pyrene, BjF, benzo[j]fluoranthene, BkF, benzo[k]fluoranthene, BaP, benzo[a ]py-rene, DBA, dibenz[a,h]anthracene, BgP, benzo[g,h,i]perylene, IcP, indeno[1,2,3-cd]pyrene. The blue trace corresponds to the analytes; BeP and BjF are interferents.

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G.I.T. Laboratory Journal 1/2020

The Digital Laboratory

A Short Introduction

J_{Martin Graf-Utzmann}

We all have heard the phrase: digitisation is unstoppable. In a coming series of articles we would like to highlight what we believe to be the most important aspects of digitiza-tion and the associated automadigitiza-tion in the laboratory.

Many people think of automation on an industrial scale. That means a deserted production hall in which robots on the as sembly line assemble metal parts into cars with uncanny speed and precision. In this series of articles, automation starts on a small scale. For me, a script that per forms a repetitive task „at the push of a button“ is already automation. The ma chine takes over a part of the work that is repetitive and ultimately boring for me and therefore errorprone. The computer doesn‘t care how often values have to be written down, added, averaged, or pro cessed in whatever way. In microbiology, for example, counting colonies in a petri dish can be done by an app on a smart phone, in other words, automated. There are solutions already available on the market that make pipetting into microti tre plates visually trackable and with that less errorprone. The system also takes care of the documentation. These are the first steps in transferring a task that does not involve any added value to a machine. Employees can use the time for more in teresting and value adding tasks.

One Size Never Fits All

Of course there is no general solution to satisfy all users in all laboratories. How ever, the market offers solutions that can be implemented in your laboratory right now. For special cases tailormade solu tions can be created in cooperation with the suppliers. The first step is to find out where timeconsuming processes can be sensibly automated and digitalised. The interaction of automation and digitiza tion is what makes this setup so power ful.

But keep in mind that digitization re quires thorough preparation. The pro cesses to be automated must be well un derstood. After all, who benefits if a bad analog process is replaced by a bad digi tal process? It is also essential to involve the people who work in the laboratory in the planning, as they will have to use the new processes. The acceptance of the em ployees is decisive for the success of a

digitisation project. Processes that are au tomated but cause more work elsewhere have little chance to be accepted. On the other hand, if the work becomes more in teresting by leaving out the „boring“ ac tivities, everyone wins.

So - What Can you Expect?

In this issue of G.I.T. Laboratory Journal you will find an article by Dr. Thorsten Teutenberg from IUTA e.V. in Duisburg. Dr. Teutenberg is setting up an automated laboratory with funds from the state of North RhineWestphalia. The name of the project, on which we have reported on several occasions in our magazine, is Fu tureLab NRW. The article offers an insight into the possibilities of collaborative ro botics.

Prof. Dr. habil Kerstin Thurow from the Center for Life Science Automation (celis ca) in Rostock takes a different approach in her article and presents her point of view on the topic of collaboration with ro bots in the laboratory.

The editorial team and I look forward to presenting further insights and points of view in the course of the year within the series of articles. If you would like us to cover a certain aspect of digitization, please feel free to send us an email with the subject line „Digitalisation“ to gitla [email protected].

Contact

Dr. Martin Graf-Utzmann

Editor-in-Chief, G.I.T. Laboratory Journal Wiley-VCH Weinheim, Germany [email protected] Related Articles http://bit.ly/WAS-Robotics

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the device). In addition, the central man agement system should be designed with sufficient flexibility to be able to take over the administration of new types of labora tory components (e.g. intelligent, func tionalized laboratory furniture) and dif ferent types of sensor systems (e.g. for monitoring the room temperature).

Besides the question of higherlevel standards, collaborative robotics will play an important role. Figure 1 shows a first experimental setup for the imple mentation of central automation solu tions. The robot shown in the figure 1 is initially intended to perform simple “pick and place” tasks that are normally car ried out by qualified laboratory person nel. For humans, these are generally simple activities, such as loading an au tosampler for HPLC with the correspond ing sample trays. The transfer of this process to a robot is highly complex, very susceptible to interference and may require indepth programming knowl edge. In order to meet the problem of skilled worker shortage, especially in the area of highly specialized IT profession als, an intuitive software is used for the first time. This allows the configuration and parameterization of basic functions of the robot by “drag & drop” to complex process chains. In this way it is not nec essary for the user to have profound pro gramming knowledge. Instead, the soft ware translates the individual motion sequences as well as the force control of the robot into native program code, so that subsequent editing of the source code by a programmer is always possi ble. This experimental setup is intended to provide information as to whether and to what extent a domain expert (labora tory technician or technical employee) can automate work processes in the lab oratory, without having to rely on corre sponding IT specialists.

What’s Next?

After successful establishment of first workflows and the integration of all de vices, the transfer to a mobile platform is planned. Against this background, IUTA has been a member of the Selfdriving Lab Robots Interest Group since 2019. Members of this group are mainly the large leading pharmaceutical companies. The objective is, among other things, to create a software platform that enables the integration of laboratory devices un der a uniform standard. In this context, the IUTA FutureLab NRW can establish itself as an important link between indus try and science by working on scientific technical issues that cannot yet be imple mented in real operation even in the

largest companies due to, for example, current technical risk.

Acknowledgement

The funding from the State of NRW will be provided using resources from the Euro pean Regional Development Fund (ERDF) 2014 2020 “Investments in growth and employment”.

Affiliation

1_{IUTA, Duisburg, Germany}

Contact Dr. Thorsten Teutenberg IUTA e.V. Duisburg, Deutschland [email protected] Related Articles: http://bit.ly/WAS-Robotics

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Laboratory Automation

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G.I.T. Laboratory Journal 1/2020 space and also allow a more flexible use of

integrated subcomponents such as opti cal readers, centrifuges or analytical mea surement systems (GC, LC, MS) if these are not used in the robot process.

But can cobots really be used in a col laborative way in the laboratory? Hardly likely. The number of processes in which robots and humans work together on one specific task is likely to be very low. It is hardly conceivable that classical laborato ry work such as pipetting, weighing, shak ing, extracting or recording measured val ues will be processed together by humans and robots. Cooperation and coexistence remain as possible forms of cooperation. In the latter, the cobots are used in auto mated systems in which classical industri al robots were used in previous concepts. The overall concept of automation is not changing. Due to the lower costs, automa tion of sample preparation and measure ment technology are now possible in new areas, which did not use automation previ ously due to cost reasons. This makes au tomation of laboratory processes increas ingly interesting and affordable for small and mediumsized companies as well as for research institutions. Here, flexible ful ly automated systems (automation lines) will be the focus of interest in order to be able to process larger numbers of samples at better prices. However, it should be not ed that not all robots are also equipped with suitable control software. Software components can be purchased from exter nal companies or must be developed in house. Depending on the scope of the task, considerable costs may arise.

VOLUME 24 MARCH

56 132 VOLUME 24 MARCH 2020

Advantages of a Unified

Summary

Tab. 1: Typical data integrity in laboratories having chromatography and spectroscopy equipment like FTIR, UV-Vis or RF next to LC or GC systems.

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The Mathematical View

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One Size Never Fits All

Dr. Martin Graf-Utzmann

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What’s Next?

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More Cobots - More Problems?