UV/Vis-based process analytical technology to improve monoclonal antibody and host cell protein separation

Process analytical technology(PAT) is gaining more interest in the biomanufacturing industry because of its potential to improve operational control and compliance through real-time quality assurance.Currently, biopharmaceutical producers mainly monitor chromatographic processes with ultraviolet/visible(UV/Vis) absorbance. However, this measurement has a very limited correlation with purity and quantity. The current study aims to determine the concentration of monoclonal antibody(mAb) and host cell proteins(HCPs) using a build-in UV/Vis monitoring during Protein A affinity chromatography and to optimize the separation conditions for high purity of mAb and minimizing the HCPs content. The eluate was analyzed through in-line UV/Vis at 280 and 410 nm, representing mAb and HCPs concentration,respectively. Each 0.1 column volume(CV) fraction of UV/Vis chromatogram peak area were calculated,and different separation conditions were then compared. The optimum conditions of mAb separation were found as 12 CV loading, elution at pH 3.5, and starting the collection at 0.5 CV point, resulting in high m Ab recovery of 95.92% and additional removal of 49.98% of HCP comparing with whole elution pool. This study concluded that UV/Vis-based in-line monitoring at 280 and 410 nm showed a high potential to optimize and real-time control Protein A affinity chromatography for mAb purification from HCPs.

Raman spectroscopy as process analytical tool in downstream processing of biotechnology

Downstream processing or product recovery plays a vital role in the development of bioprocesses.To improve the bioprocess efficiency,some unconventional methods are much required.The continuous manufacturing in downstream processing makes the Process Analytical Technologies(PATs)as an important tool.Monitoring and controlling bioprocess are an essential factor for the principles of PAT and quality by design.Spectroscopic methods can apply to monitor multiple analytes in real-time with less sample processing with significant advancements.Raman spectroscopy is an extensively used technique as an analytical and research tool owing to its modest process form,non-destructive,non-invasive optical molecular spectroscopic imaging with computer-based analysis.Generally,its application is essential for the analysis and characterization of biological samples,and it is easy to operate with minimal sample.The innovation on various types of enhanced Raman spectroscopy was designed to enhance the Raman analytical technique.Raman spectroscopy could couple with chemometrics to provide reliable alternative analysis method of downstream process analysis.Thus,this review aims to provide useful insight on the application of Raman spectroscopy for PAT in downstream processing of biotechnology and Raman data analysis in biological fields.

Online pharmaceutical process analysis of Chinese medicine using a miniature mass spectrometer: Extraction of active ingredients as an example

The automation of traditional Chinese medicine(TCM)pharmaceuticals has driven the development of process analysis from offline to online.Most of common online process analytical technologies are based on spectroscopy,making the identification and quantification of specific ingredients still a challenge.Herein,we developed a quality control(QC)system for monitoring TCM pharmaceuticals based on paper spray ionization miniature mass spectrometry(mini-MS).It enabled real-time online qualitative and quantitative detection of target ingredients in herbal extracts using mini-MS without chromatographic separation for the first time.Dynamic changes of alkaloids in Aconiti Lateralis Radix Praeparata(Fuzi)during decoction were used as examples,and the scientific principle of Fuzi compatibility was also investigated.Finally,the system was verified to work stably at the hourly level for pilot-scale extraction.This mini-MS based online analytical system is expected to be further developed for QC applications in a wider range of pharmaceutical processes.

Process Characterization of the Transesterification of Rapeseed Oil to Biodiesel Using Design of Experiments and Infrared Spectroscopy

For optimization of production processes and product quality,often knowledge of the factors influencing the process outcome is compulsory.Thus,process analytical technology(PAT)that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality.The present study aims at characterizing a well-known industrial process,the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters(FAME)for usage as biodiesel in a continuous micro reactor set-up.To this end,a design of experiment approach is applied,where the effects of two process factors,the molar ratio and the total flow rate of the reactants,are investigated.The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield.The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression.The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis.A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination(R^(2))of 0.9608.Thus,we applied a PAT approach to generate further insight into this established industrial process.

Fluidised bed granulation of two APIs:QbD approach and development of a NIR in-line monitoring method

The study focused on the fluid-bed granulation process of a product with two active pharmaceutical ingredients,intended for coated tablets preparation and further transfer to industrial scale.The work aimed to prove that an accurate control of the critical granulation parameters can level the input material variability and offer a user-friendly process control strategy.Moreover,an in-line Near-Infrared monitoring method was developed,which offered a real time overview of the moisture level along the granulation process,thus a reliable supervision and control process analytical technology(PAT)tool.The experimental design’s results showed that the use of apparently interchangeable active pharmaceutical ingredients(APIs)and filler sorts that comply with pharmacopoeial specifications,lead to different end-product critical attributes.By adapting critical granulation parameters(i.e.binder spray rate and atomising pressure)as a function of material characteristics,led to granules with average sizes comprised in a narrow range of 280–320μm and low nongranulated fraction of under 5%.Therefore,the accurate control of process parameters according to the formulation particularities achieved the maintenance of product within the design space and removed material related variability.To complete the Quality by design(QbD)strategy,despite its limited spectral domain,the microNIR spectrometer was successfully used as a robust PAT monitoring tool that offered a real time overview of the moisture level and allowed the supervision and control of the granulation process.

Granulation process analysis technologies and potential applications in traditional Chinese medicine

Pharmaceutical production is changing from batch production to continuous production,during which granulation is one of the most important unit operations.The quality of mass-produced products is traditionally guaranteed by conducting off-line testing,which cannot meet the demand of continuous production for real-time monitoring of critical process parameters and critical quality attributes(CQAs)of the pharmaceutical granulation technology.Since the U.S.Food and Drug Administration proposed process analytical technology(PAT)in 2004,many PAT tools have been developed to monitor the granulation process and provide information regarding the granulation operation conditions and endpoint determination.In this article,we review the recent research and application of two PAT modes in the granulation process,namely,single CQA and multi-CQA PAT,with the aim to provide references for comprehensively improving the technological level of the pharmaceutical granulation process.Furthermore,the potential applications in traditional Chinese Medicine are discussed.

Study progression in application of process analytical technologies on film coating

Film coating is an important unit operation to produce solid dosage forms,thereby,the monitoring of this process is helpful to find problems in time and improve the quality of coated products.Traditional methods adopted to monitor this process include measurement of coating weight gain,performance of disintegration and dissolution test,etc.However,not only do these methods cause destruction to the samples,but also consume time and energy.There have recently emerged the applications of process analytical technologies(PAT)on film coating,especially some novel spectroscopic and imaging technologies,which have the potential to real-time track the progress in film coating and optimize production efficiency.This article gives an overview on the application of such technologies for film coating,with the goal to provide a reference for the further researches.

In-situ monitoring of saccharides removal of alcohol precipitation using near-infrared spectroscopy

As unsafe components in herbal medicine(HM),saccharides can affect not only the drug appearance and stabilization,but also the drug efficacy and safety.The present study focuses on the in-line monitoring of batch alcohol precipitation processes for saccharide removal using nearinfrared(NIR)spectroscopy.NIR spectra in the 4000–10,000-cm^(-1)wavelength range are acquired in situ using a transflectance probe.These directly acquired spectra allow characterization of the dynamic variation tendency of saccharides during alcohol precipitation.Calibration models based on partial least squares(PLS)regression have been developed for the three saccharide impurities,namely glucose,fructose,and sucrose.Model errors are estimated as the root-meansquare errors of cross-validation(RMSECVs)of internal validation and root-mean-square errors of prediction(RMSEPs)of external validation.The RMSECV values of glucose,fructose,and sucrose were 1.150,1.535,and 3.067 mg·mL^(-1),and the RMSEP values were 0.711,1.547,and 3.740 mg·mL^(-1),respectively.The correlation coeffcients(r)between the NIR predictive and the reference measurement values were all above 0.94.Furthermore,NIR predictions based on the constructed models improved our understanding of sugar removal and helped develop a control strategy for alcohol precipitation.The results demonstrate that,as an alternative process analytical technology(PAT)tool for monitoring batch alcohol precipitation processes,NIR spectroscopy is advantageous for both efficient determination of quality characteristics(fast,in situ,and requiring no toxic reagents)and process stability,and evaluating the repeatability.

Process analytical technologies and self-optimization algorithms in automated pharmaceutical continuous manufacturing

The pharmaceutical industry is now paying increased attention to continuous manufacturing.While the revolution to continuous and automated manufacturing is deepening in most of the top pharma companies in the world,the advancement of automated pharmaceutical continuous manufacturing in China is relatively slow due to some key challenges including the lack of knowledge on the related technologies and shortage of qualified personnels.In this review,emphasis is given to two of the crucial technologies in automated pharmaceutical continuous manufacturing,i.e.,process analytical technology(PAT)and self-optimizing algorithm.Research work published in recent 5 years employing advanced PAT tools and self-optimization algorithms is introduced,which represents the great progress that has been made in automated pharmaceutical continuous manufacturing.

An Automated,Highly Selective Reaction Monitoring Instrument Using Molecular Rotational Resonance Spectroscopy

Online monitoring of chemical reactions by using analytical chemistry tools is a powerful way to maximize control over these processes.In this paper,we demonstrate the use of molecular rotational resonance,an emerging and extraordinarily selective spectroscopic technique,to perform automated reaction monitoring measurements.An interface using a six-port valve with a calibrated sample loop,coupled to a temperature controlled inlet for analyte volatilization,was developed and tested.Two reactions were chosen for initial characterization:an amine-aldehyde condensation reaction to form an imine product and an isotopic exchange reaction of aβ-ketoester with keto-enol tautomerization.The spectrometer was able to provide kinetic information about the reaction and determine reaction completion.In the future,this system can be extended to detect and quantify impurities and characterize reaction selectivity,in addition to the reaction progress.

Real time monitoring of bioreactor mAb IgG3 cell culture process dynamics via Fourier transform infrared spectroscopy： Implications for enabling cell culture process analytical technology

Compared to small molecule process analytical technology （PAT） applications, biotechnology product PAT applications have certain unique challenges and opportunities. Understanding process dynamics of bioreactor cell culture process is essential to establish an appropriate process control strategy for biotechnology product PAT applications. Inline spectroscopic techniques for real time monitoring of bioreactor cell culture process have the distinct potential to develop PAT approaches in manufac- turing biotechnology drug products. However, the use of inline Fourier transform infrared （FTIR） spectroscopic techniques for bioreactor cell culture process monitoring has not been reported. In this work, real time inline FTIR Spectroscopy was applied to a lab scale bioreactor mAb IgG3 cell culture fluid biomolecular dynamic model. The technical feasibility of using FTIR Spectroscopy for real time tracking and monitoring four key cell culture metabolites （including glucose, glutamine, lactate, and ammonia） and protein yield at increasing levels of complexity （simple binary system, fully formulated media, actual bioreactor cell culture process） was evaluated via a stepwise approach. The FTIR fingerprints of the key metabolites were identified. The multivariate partial least squares （PLS） calibration models were established to correlate the process FTIR spectra with the concentrations of key metabolites and protein yield of in-process samples, either individually for each metabolite and protein or globally for all four metabolites simultaneously. Applying the 2＇ld derivative pre-processing algorithm to the FTIR spectra helps to reduce the number of PLS latent variables needed significantly and thus simplify the interpretation of the PLS models. The validated PLS models show promise in predicting the concentration profiles of glucose, glutamine, lactate, and ammonia and protein yield over the course of the bioreactor cell culture process. Therefore, this work demonstrated the technical feasibility of real time monitoring of the bioreactor cell culture process via FTIR spectroscopy. Its implications for enabling cell culture PAT were discussed.

Kinetic study of complicated anti-solvent and cooling crystallization of disodium 5′-ribonucleotide

Disodium 5′-ribonucleotide,which is composed of disodium 5′-inosine(IMP)and disodium 5′-guanosine(GMP),is an important food additive.The lack of kinetic studies of it causes a lack of clarity in understanding the complicated multi-solute crystallization of IMP+GMP in ethanol-water.In this work,process analytical technology tools were used to obtain the thermodynamics and kinetic data from the experiments,the kinetic parameters of anti-solvent and cooling crystallization were investigated.The crystal form of IMP+GMP mixed crystal was determined,which was consistent with the IMP whether crystallized from pure water or ethanol-water.The effects of different anti-solvent addition rates and cooling rates on the metastable zone widths were studied,and the opposite effect on metastable zone width was found.The modified exponential empirical function was developed to correlate nucleation and growth kinetic equations under different conditions.The kinetic data were well fitted with adjusted correlation coefficient(adj-R^(2)>0.7),which is sufficient to provide a valid reference for process design and control.

Deep learning-based on-line image analysis for continuous industrial crystallization processes

In situ microscopic imaging is a useful tool in monitoring crystallization processes,including crystal nucleation,growth,aggregation and breakage,as well as possible polymorphic transition.To convert the qualitative information to be quantitative for the purpose of process optimization and control,accurate analysis of crystal images is essential.However,the accuracy of image segmentation with traditional methods is largely affected by many factors,including solid concentration and image quality.In this study,the deep learning technique using mask region-based convolutional neural network(Mask R-CNN)is investigated for the analysis of on-line images from an industrial crystallizer of 10 m^(3) operated in continuous mode with high solid concentration and overlapped particles.With detailed label points for each crystal and transfer learning technique,two models trained with 70,908 and 7,709 crystals respectively are compared for the effect of training data amount.The former model effectively segments the aggregated and overlapped crystals even at high solid concentrations.Moreover,it performs much better than the latter one and traditional multi-scale method both in terms of precision and recall,revealing the importance of large number of crystals in deep learning.Some geometrical characteristics of segmented crystals are also analyzed,involving equivalent diameter,circularity,and aspect ratio.

A near-infrared spectroscopy-based end-point determination method for the blending process of Dahuang soda tablets

Objectives:This study is aimed to explore the blending process of Dahuang soda tablets.These are composed of two active pharmaceutical ingredients(APIs,emodin and emodin methyl ether)and four kinds of excipients(sodium bicarbonate,starch,sucrose,and magnesium stearate).Also,the objective is to develop a more robust model to determine the blending end-point.Methods:Qualitative and quantitative methods based on near-infrared(NIR)spectroscopy were established to monitor the homogeneity of the powder during the blending process.A calibration set consisting of samples from 15 batches was used to develop two types of calibration models with the partial least squares regression(PLSR)method to explore the influence of density on the model robustness.The principal component analysis-moving block standard deviation(PCA-MBSD)method was used for the end-point determination of the blending with the process spectra.Results:The model with different densities showed better prediction performance and robustness than the model with fixed powder density.In addition,the blending end-points of APIs and excipients were inconsistent because of the differences in the physical properties and chemical contents among the materials of the design batches.For the complex systems of multi-components,using the PCA-MBSD method to determine the blending end-point of each component is difficult.In these conditions,a quantitative method is a more suitable alternative.Conclusions:Our results demonstrated that the effect of density plays an important role in improving the performance of the model,and a robust modeling method has been developed.

Simultaneous characterization of multiple properties of solid and liquid phases in crystallization processes using NIR

Near infrared spectroscopy （NIR） is now probably the most popular process analytical technology （PAT） for pharmaceutical and some other industries. However, unlike mid-IR, NIR is known to have difficulties in monitoring crystallization or precipitation processes because the existence of solids could cause distortion of the spectra. This phenomenon, seen as unfavorable previously, is however an indication that NIR spectra contain rich information about both solids and liquids, giving the possibility of using the same instrument for multiple property characterization. In this study, transflectance NIR calibration data was obtained using solutions and slurries of varied solution concentration, particle size, solid concentration and temperature. The data was used to build calibration models for prediction of the multiple properties of both phases. Predictive models were developed for this challenging application using an approach that combines genetic algorithm （GA） and support vector machine （SVM）. GA is used for wavelength selection and SVM for mode building. The new GA-SVM approach is shown to outperform other methods including GA-PLS （partial least squares） and traditional SVM. NIR is thus successfully applied to monitoring seeded and unseeded cooling crystallization processes of L-glutamic acid.

APPLYING NOVEL ANALYTICAL TECHNOLOGIES TO FACE NATURAL PRODUCTS CHALLENGES

Herbal medicines have been used since ancient times for thetreatment of many diseases and illnesses.Modern chromatographic and spectroscopic techniques have had a tremendous impact on the analysis of herbal medicine to facilitate research as well as enhancement of safety and efficacy of commercial products.Today,with the