Quality-In(Process)Line (QuIProLi) process intensification for a micro-flow UV-photo synthesis enabled by online UHPLC analysis

Automated High-Pressure Atline Analysis of Photo-High-P,T Vitamin D3 Microfluidic Synthesis

Process analytical technology has become a relevant topic in both industry and academia as a mechanism to control process quality by measuring critical parameters; being mainly applied in pharmaceutical industry. An emerging topic is process monitoring with subsequent process automation in flow chemistry using inline, online and atline analyzers. Flow chemistry often deliberately and favorably uses harsh conditions (termed Novel Process Windows) to achieve process intensification which raises the need for sampling under these conditions. This demands for setting in place a stabilization of the sample before exposing it to the processing. Ignoring this may result in being unable to use inline/online analytics and posing the need for a separation step before quantitative analysis, leaving atline analysis as the only feasible option. That means that sampling and connected operations need also to be automated. This is where this study sets in, and this is enabled by a modified high-performance liquid chromatography (HPLC) autosampler coupled to the photo-high-p,T flow synthesis of vitamin D3. It shows that sampling variables, such as decompression speed, can be even more critical in terms of variability of results than process variables such as concentration, pressure, and temperature. The modification enabled the autosampler fully automated and unattended sampling from the reactor and enabled pressure independent measurements with 89% accuracy, >95% reproducibility, and >96% repeatability, stating decompression speed as the primary responsibility for measurements’ uncertainty.

System optimisation quantitative model of on-line NIR: a case of Glycyrrhiza uralensis Fisch extraction process

INTRODUCTION

The on-line analysis of active pharmaceutical ingredients (APIs) during the extraction process in herbal medicine is a challenge. Establishing a reliable and robust model is a critical procedure for the industrial application of on-line near-infrared (NIR) technology.

OBJECTIVE

To evaluate the advantages of on-line NIR model development using system optimisation strategy, Glycyrrhiza uralensis Fisch was used as a case. The content of liquiritin and glycyrrhizic acid was monitored during pilot scale extraction process of Glycyrrhiza uralensis Fisch in three batches.

METHODS

High-performance liquid chromatography (HPLC) was used as reference method for content determination of liquiritin and glycyrrhizic acid. The quantitative models of on-line NIR were developed by system optimisation of processing trajectory. For comparison, the models were simultaneously developed by stepwise optimisation. Moreover, the modelling parameters obtained through system optimisation and stepwise optimisation were reused in three batches. Root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) were used to assess the model quality.

RESULTS

The average values of RMSEP and RPD of systematic model for liquiritin in three batches were 0.0361, 4.1525 (first batch), 0.0348, 4.7286 (second batch) and 0.0311, 4.9686 (third batch), respectively. In addition, the modelling parameters of systematic model for glycyrrhizic acid in three batches were same, and the average values of RMSEP and RPD were 0.0665 and 5.2751, respectively. The predictive performance and robustness of systematic models for the three batches were better than the comparison models.

CONCLUSION

The work demonstrated that system optimisation quantitative model of on-line NIR could be used to determine the contents of liquiritin and glycyrrhizic acid during Glycyrrhiza uralensis Fisch extraction process.

Process analytical technology (PAT) as a versatile tool for real-time monitoring and kinetic evaluation of photocatalytic reactions

Combining in situ Raman spectroscopy with multivariate data analysis enables the real-time monitoring and kinetic evaluation of photocatalytic reactions. The applicability is demonstrated on the photooxidation of 4-methoxythiophenol.

Laboratory of the future: a modular flow platform with multiple integrated PAT tools for multistep reactions

The coupling of a modular microreactor platform, real-time inline analysis by IR and NMR, and online UPLC, leads to efficient optimization of a multistep organolithium transformation to a given product without the need for human intervention.

Adaptive and automated system-optimization for heterogeneous flow-hydrogenation reactions

The autonomous hydrogenation of carbonyl compounds and N-heterocycles over solid catalysts with H₂ is achieved in 3D parameter space by integrating analytics, control and hardware.

Everything Flows: Continuous Micro-Flow for Pharmaceutical Production

The pre-Socratic philosophers made the first honest attempt, at least in the western world, to describe natural phenomena in a rudimentary scientific manner and to exploit those for technological application [1]. Pythagoras of Samos (570–495 BC) was an Ionian Greek philosopher and the first to actually call himself a “philosopher”. He was credited with many mathematical and scientific discoveries, including the Pythagorean theorem, Pythagorean tuning, the five regular solids, the theory of proportions, and the sphericity of the Earth. The Pythagorean triple is also well-known. Heraclitus of Ephesus (535–475 BC) was famous for his insistence on ever-present change as the fundamental essence of the universe, as stated in the famous saying “panta rhei” —everything flows.