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Produzieren Sie schon oder kalibrieren Sie noch? – Online-NMR-Spektrometer als Smarte Feldgeräte
(2018)
Der Vortrag zeigt allgemeine Anforderungen an "smarte Feldgeräte" und deren Entwicklung in den vergangenen Jahren. Am Beispiel eines smarten Online-NMR-Sensors, der in einem EU-Projekt von der BAM entwickelt wurde, wird die Umsetzung der Anforderung aufgezeigt. Schließlich werden weitere Technologieanforderungen und Lösungsansätze vorgestellt.
Im Zuge der Digitalisierung der Prozessindustrie werden zunehmend modellbasiere Echtzeitoptimierungsverfahren eingesetzt, sog. „Advanced Process Control“. Mithilfe der sogenannten Modifier-Adaptation ist eine iterative Betriebspunktoptimierung auch mit ungenauen Modellen möglich, sofern zuverlässige Prozessdaten zur Verfügung stehen. Am Beispiel eines smarten Online-NMR-Sensors, der in einem EU-Projekt von der BAM entwickelt wurde, konnte das Konzept in einer modularen Produktionsanlage zur Herstellung eines pharmazeutischen Wirkstoffs erfolgreich getestet werden.
The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control.
The talk introduces a smart online NMR sensor module provided in an explosion proof housing as example. This sensor was developed for an intensified industrial process (pharmaceutical lithiation reaction step) funded by the EU’s Horizon 2020 research and innovation programme (www.consens-spire.eu). Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs.
The talk also generally covers current aspects of high-field and low-field online NMR spectroscopy for reaction monitoring and process control.
There is a need within the NMR community to progress forward in exploring new facets in which we can use analytical techniques to advance our understanding of various systems. One aspect the NMR community hasn’t fully encompassed is the validation process, which also involves setting reference standards, establishing a common language that directly relates to NMR, communication relating to validation, and much more.
This workshopcontribution starts with an overview on international metrology for qNMR spectroscopy. Since NMR is completely described by mathematical equations, the measurement unceartainty can directly be dreived from formula. Examples are presented. These are differentiated between type A and B evaluations. Finally the Expanded Unceartainty is defined. Since the user needs a risk-based unceartainty assessment, different "leagues" for routine, advanced, and high level needs are proposed to make clear, that no all sources of uncertainty have to be taken in considerention at practical levels.
Modular plants using intensified continuous processes represent an appealing concept to produce pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes, and it enables plug-and-produce reconfiguration for fast product changes. To facilitate this flexibility by real-time quality control, we developed a solution that can be adapted quickly to new processes and includes a compact Nuclear Magnetic Resonance (NMR) spectrometer for online quality monitoring as well as a new model-based control approach. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including ro-bust evaluation of sensor data.
Here, we present alternatives for the quantitative determination of the analytes using modular, physically motivated models. These models can be adapted to new substances solely by the use of their corresponding pure component spectra, which can either be derived from experimental spectra as well as from quantum mechanical models or NMR predictors. Modular means that spec-tral models can simply be exchanged together with alternate reagents and products. Beyond that, we comprehensively calibrated an NIR spectrometer based on online NMR process data for the first time within an industrial plant. The integrated solution was developed for a metal organic reac-tion running on a commercial-scale modular pilot plant and it was tested under industrial conditions.
In case study one of the CONSENS project, two aromatic substances were coupled by a lithiation reaction, which is a prominent example in pharmaceutical industry. The two aromatic reactants (Aniline and o-FNB) were mixed with Lithium-base (LiHMDS) in a continuous modular plant to produce the desired product (Li-NDPA) and a salt (LiF). The salt precipitates which leads to the formation of particles. The feed streams were subject to variation to drive the plant to its optimum.
The uploaded data comprises the results from four days during continuous plant operation time. Each day is denoted from day 1-4 and represents the dates 2017-09-26, 2017-09-28, 2017-10-10, 2017-10-17.
In the following the contents of the files are explained.
Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
ISO/IEC 17025 is the worldwide quality standard for testing and calibration laboratories. It is the basis for accreditation by an accreditation body. The current version was published in 2018.
Implementing ISO/IEC 17025 as part of laboratory quality initiatives offers both laboratory and business benefits, such as expanding the potential customer base for testing and/or calibration, increasing the reputation and image of the laboratory at national and international level, continuous improvement of the data quality and the effectiveness of the laboratory or creation of a good basis for most other quality systems in the laboratory sector, such as GxP. The main difference between a proper approach to analysis and a formal accreditation is shown in a targeted documentation, especially on the qualification of the personnel, the test equipment and the validation of the analytical methods.
Using quantitative NMR spectroscopy as an example, it is shown how accreditation can be carried out and what documentation is required. In our case, we have described the procedure in an SOP ("Determination of the quantitative composition of simple mixtures of structurally known compounds with 1H-NMR spectroscopy") and supported it with a modular system of organizational and equipment SOPs. The special feature is that the accredited method is independent for the choice of the analyte and the matrix and therefore it is possible to operate with a single validated method. In our case, we have proposed three quality levels ("leagues") with different levels of analytical effort, which differ in their measurement uncertainty, in order to simplify the workflow and analysis design.
Um die internationale Spitzenposition deutscher Unternehmen der Prozessindustrie auch in Zukunft sicher zu stellen, müssen die Unternehmen ihre Prozesse und Geschäftsabläufe digitalisieren und gemeinsam mit der Forschung innovative neue Methoden, Apparate, Anlagen, Sensoren und Automatisierungstechnik sowie Datenkonzepte entwickeln. All dies erfordert den Aufbau neuer Fähigkeiten, Investition in Talente, interdisziplinäre Kommunikation zwischen verschiedenen Personen und Abteilungen und eine Bereitschaft zur Veränderung.
qNMR - The handbook
(2023)
Quantitative NMR (qNMR) has been around for a long time, but also has great potential to solve future problems in any quantitative analysis. As a primary method, it differs fundamentally from chromatographic methods: it is better described as a quantum mechanical balance. Succesful implementation of qNMR requires certain attention to detail. "qNMR - the handbook" is intended to be a guide for analysts to help understand the fundamental principles of NMR and the significant points relating to its implementation for quantitation. Regulatory considerations of qNMR adoption are explained. NMR fundamentals are explained to provide understanding. Together with many useful examples, the book is a compelling addition to the laboratory's reference library, providing all the tools that any practitioner should know to successfully implement qNMR.
The authors are qNMR pioneers and come from a variety of backgrounds including business, government and academia.