Process Analytical Technology Applications Research Articles

Implemention of Innovative Process Analytical Technologies to Characterize Critical Quality Attributes of Co-Formulated Monoclonal Antibody Products.

Characterizing co-formulated monoclonal antibodies (mAbs) poses significant challenges in the pharmaceutical industry. Due to the high structural similarity of the mAbs, traditional analytical methods, compounded by the lengthy method development process, hinder product development and manufacturing efficiency. There is increasing critical need in the pharmaceutical industry to streamline analytical approaches, minimizing time and resources, ensuring a rapid clinical entry and cost-effective manufacturing. This study investigates the application of process analytical technologies (PAT) to address such challenges. Our investigation introduces two complementary technologies, on-line ultra-performance liquid chromatography (online UPLC) and multimode fluorescence spectroscopy (MMFS), as potential PAT tools tailored for characterizing critical quality attributes (CQA) in co-formulated mAb products. Specifically, the CQAs under evaluation include the total protein concentration of the mAbs within the co-formulation and the ratio of mAb A to mAb B. Online UPLC enables direct and automated measurement of the CQAs through physical separation, while MMFS determines them in a non-destructive and more swift manner based on chemometric modeling. We demonstrate these technologies' comparable performance to conventional methods, alongside substantial benefits such as reduced analytical turnaround time and decreased laboratory efforts. Ultimately, integrating them as innovative PAT tools expedites the delivery of therapeutic solutions to patients and enhances manufacturing efficiency, aligning with the imperative for swift translation of scientific discoveries into clinical benefits.

Blend uniformity monitoring in a continuous manufacturing mixing process for a low-dosage formulation using a stream sampler and near infrared spectroscopy

Continuous manufacturing has the potential to offer several benefits for the production of oral solid dosage forms, including reduced costs, low-scale equipment, and the application of process analytical technology (PAT) for real-time process control. This study focuses on the implementation of a stream sampler to develop a near infrared (NIR) calibration model for blend uniformity monitoring in a continuous manufacturing mixing process. Feeding and mixing characterizations were performed for three loss-in-weight feeders and a commercial continuous mixer to prepare powder blends of 2.5–7.5 % w/w ibuprofen DC 85 W with a total throughput of 33 kg/h. The NIR spectral acquisition was performed after the mixing stage using a stream sampler for flowing powders. A continuous mixer shaft speed of 250 RPM was selected to operate the mixing process based on a variability analysis developed with in-line spectral data acquired using the stream sampler at 6 RPM. A partial least squares regression (PLS-R) model was performed and evaluated, yielding a root-mean-square error of prediction (RMSEP) of 0.39 % w/w and a bias of 0.05 % w/w. An independent experimental run conducted two days later revealed that the continuous mixing process and the NIR calibration model presented low day-to-day variation. The minimum practical error (MPE) and sill values through variographic analysis showed low variance associated with the sampling process using the stream sampler. Results demonstrated the promising capacity of the stream sampler coupled to an NIR probe to be implemented within continuous manufacturing processes for the real-time determination of API concentration.

Expediting online liquid chromatography for real-time monitoring of product attributes to advance process analytical technology in downstream processing of biopharmaceuticals

The application of Process Analytical Technology (PAT) principles for manufacturing of biotherapeutics proffers the prospect of ensuring consistent product quality along with increased productivity as well as substantial cost and time savings. Although this paradigm shift from a traditional, rather rigid manufacturing model to a more scientific, risk-based approach has been advocated by health authorities for almost two decades, the practical implementation of PAT in the biopharmaceutical industry is still limited by the lack of fit-for-purpose analytical methods. In this regard, most of the proposed spectroscopic techniques are sufficiently fast but exhibit deficiencies in terms of selectivity and sensitivity, while well-established offline methods, such as (ultra-)high-performance liquid chromatography, are generally considered as too slow for this task. To address these reservations, we introduce here a novel online Liquid Chromatography (LC) setup that was specifically designed to enable real-time monitoring of critical product quality attributes during time-sensitive purification operations in downstream processing. Using this online LC solution in combination with fast, purpose-built analytical methods, sampling cycle times between 1.30 and 2.35 min were achieved, without compromising on the ability to resolve and quantify the product variants of interest. The capabilities of our approach are ultimately assessed in three case studies, involving various biotherapeutic modalities, downstream processes and analytical chromatographic separation modes. Altogether, our results highlight the expansive opportunities of online LC based applications to serve as a PAT tool for biopharmaceutical manufacturing.

Machine learning algorithms for in-line monitoring during yeast fermentations based on Raman spectroscopy

Given the intricacies and nonlinearity inherent to industrial fermentation systems, the application of process analytical technology presents considerable benefits for the direct, real-time monitoring, control, and assessment of synthetic processes. In this study, we introduce an in-line monitoring approach utilizing Raman spectroscopy for ethanol production by Saccharomyces cerevisiae. Initially, we employed feature selection techniques from the realm of machine learning to reduce the dimensionality of the Raman spectral data. Our findings reveal that feature selection results in a noteworthy reduction of over 90% in model training time, concurrently enhancing the predictive performance of glycerol and cell concentration by 14.20% and 17.10% at the root mean square error (RMSE) level. Subsequently, we conducted model retraining using 15 machine learning algorithms, with hyperparameters optimized through grid search. Our results illustrate that the post-hyperparameter adjustment model exhibits improvements in RMSE for ethanol, glycerol, glucose, and biomass by 9.73%, 4.33%, 22.22%, and 13.79%, respectively. Finally, specific machine learning algorithms, namely BaggingRegressor, Support Vector Regression, BayesianRidge, and VotingRegressor, were identified as suitable models for predicting glucose, ethanol, glycerol, and cell concentrations, respectively. Notably, the coefficient of determination (R2) ranged from 0.89 to 0.97, and RMSE values ranged from 0.06 to 2.59 g/L on the testing datasets. The study highlights machine learning's effectiveness in Raman spectroscopy data analysis for improved industrial fermentation monitoring, enhancing efficiency, and offering novel modeling insights.

Diagnostic development using net analyte signal for pure component modeling approaches

The use of calibration-free or minimal calibration chemometric modeling approaches has garnered increased interest as the application of process analytical technologies (PAT) has expanded in the pharmaceutical industry. Pure component models such as iterative optimization technology (IOT) algorithms require only pure component spectra and no mixture samples as model inputs. However, the deployment of pure component models for PAT is limited by the lack of model diagnostics to establish confidence in model predictions and identify outliers. In the presented research, a novel diagnostic for use with IOT, called NAS-T, is proposed based on comparing the shape of net analyte signals (NAS) between the pure components and a sample mixture. Circular statistics were used in the analysis of NAS-T. The new diagnostic was applied in parallel with the partial least squares (PLS) Hotelling's T2 diagnostic to identify outlier near-infrared spectral samples from a set of pharmaceutical powder mixtures. The outliers detected by the NAS-T diagnostic included both chemical interferences (contamination) and physical interferences (process variations). Preprocessing the mixture sample spectra produced trends in the model diagnostics that were consistent between IOT and PLS. These results support the adoption of IOT and other pure component models for PAT applications in the pharmaceutical industry.

Phase-appropriate Application of Process Analytical Technology for Early Pharmaceutical Development of Oral Solid Dosage Forms-the Case Study of Uniformity Screening of Dosage Units and Blends.

Process analytical technology (PAT) in late-stage drug product development is typically used for real-time process monitoring, in-process control, and real-time release testing. In early research and development (R&D), PAT usage is limited as the manufacturing scale is relatively small with frequent changes and only a few batches are produced on an annual basis. However, process understanding is critical at early R&D in order to identify process and formulation boundaries, so PAT applications could be particularly useful in early-stage R&D. For oral solid dosage form, conventional HPLC-based content uniformity (CU) methods with sampling of 3 tablets per stratified sampling location in early R&D are typically not sufficient to identify these manufacturing process boundaries and temporal profile. Here, we report a screening CU method based on a multivariate model using transmission Raman spectroscopy (TRS) data on a phase-appropriate calibration set of only 16 tablets. This initial model was used for multiple pre-GMP development batches to provide critical information about blend uniformity and content uniformity (CU). In this work, the precision of the TRS method was evaluated; multiple spectral preprocessing approaches were compared regarding their effects on measurement precision as well as their ability to mitigate the photo bleaching effects during precision experiments. Overall, the TRS-based CU method was much faster than a traditional HPLC-based method allowing a much larger number of tablets to be screened. This larger number of analyzed tablets enabled the processes boundaries and temporal changes in CU to be identified while providing proper statistical assurance on product quality.

Review of the Application of PAT in the Pharmaceutical Continuous Crystallization Process.

As an important pharmaceutical process, crystallization greatly impacts the final product. In recent years, the continuous crystallization process has attracted more attention from researchers, with the promotion of continuous manufacturing (CM) by the Food and Drug Administration (FDA). The continuous crystallization process has the advantages of high economic benefit, stable and uniform quality, a short production cycle, and personalization. To carry out continuous crystallization, some related process analytical technology (PAT) tools have become the focus of breakthroughs. Infrared (IR) spectroscopy, Raman spectroscopy, and focused beam reflection measurement (FBRM) tools have gradually become research hotspots due to their fast, non-destructive, and real-time monitoring characteristics. This review compared the advantages and disadvantages of the three technologies. Their applications in the upstream mixed continuous crystallization process, the middle reaches of crystal nucleation and growth, and the process of the downstream refining were discussed to provide corresponding guidance for the practice and further development of these three technologies in the continuous crystallization process and promote the development of CM in the pharmaceutical industry.

Application of process analytical technology (PAT) in real-time monitoring of pharmaceutical cleaning process: Unveiling the cleaning mechanisms governing the cleaning-in-place (CIP)

We report for the first time the combination of inline process analytical technology and optical imaging to track and understand different cleaning mechanisms governing the cleaning process of Olanzapine. Clean-in-Place process parameters were studied through simultaneous inline process analytical technology and image analysis in a film flow apparatus. Methanol and water were compared as cleaning agents, and the effect of flow (0.5—1 L.min−1) and temperature (20–40 °C, and 60 °C for water) was investigated. The cleaning process was assessed in terms of cleaning time, volumetric efficiency, surface residue and governing phenomena. Raman spectroscopy was used to prove no degradation occurred during cleaning. Temperature increase improves the efficiency even when solubility is negligible. High variability was observed when detachment behaviour is dominant, and it is then advisable to prioritize dissolution in the final clean-in-place steps to improve repeatability. Results show that the cleaning process is governed by an interplay of dissolution and mechanical shear phenomena and is more efficient when solubility is significant. The combination of in-situ process analytical technology and optical imaging analysis during process development allows for the determination of the most efficient and repeatable conditions, which in turn significantly reduces solvent usage in pharmaceutical cleaning.

Implementation of a fully integrated CM direct compression and coating process at a commercial pharmaceutical facility – Part 2: PAT and RTD results for normal operational conditions batches

This is the second of two articles detailing the continuous manufacturing (CM) development and implementation activities for an marketed product which have been realized in novel, qualified equipment, using validated control strategy elements to enable manufacture of batches under current good manufacturing practices (cGMP) and compliant with data integrity principles. Here, the application of process analytical technologies (PAT) and automation tools on batches produced under normal operational conditions is reviewed. The results from residence time distribution (RTD) models for predicting API concentration, in-line near infrared (NIR) testing of blend uniformity (BU) and at-line NIR spectroscopy analysis of core tablet concentration and tablet identity for real-time release testing (RTRT) are discussed. The influences of process equipment and design choices on NIR and RTD model variability, as well as the use of the PAT tools for monitoring the evolving properties understanding of CM process development, such as overcoming flow instabilities, is described. Results demonstrate that the RTD and NIR models developed and validated are robust to operating conditions and are critical for assuring steady state control of the continuous manufacturing process. Finally, the NIR and RTD model lifecycle, including procedures for necessary and normal model upgrades in a cGMP production environment, are presented.

Rapid Evaluation of the Extent of Haptoglobin Glycosylation Using Orthogonal Intact-Mass MS Approaches and Multivariate Analysis.

Intact-mass measurements are becoming increasingly popular in mass spectrometry (MS) based protein characterization, as they allow the entire complement of proteoforms to be evaluated within a relatively short time. However, applications of this approach are currently limited to systems exhibiting relatively modest degrees of structural diversity, as the high extent of heterogeneity frequently prevents straightforward MS measurements. Incorporation of limited charge reduction into electrospray ionization (ESI) MS is an elegant way to obtain meaningful information on most heterogeneous systems, yielding not only the average mass of the protein but also the mass range populated by the entire complement of proteoforms. Application of this approach to characterization of two different phenotypes of haptoglobin (1-1 and 2-1) provides evidence of a significant difference in their extent of glycosylation (with the glycan load of phenotype 2-1 being notably lighter) despite a significant overlap of their ionic signals. More detailed characterization of their glycosylation patterns is enabled by the recently introduced technique of cross-path reactive chromatography (XP-RC) with online MS detection, which combines chromatographic separation with in-line reduction of disulfide bonds to generate metastable haptoglobin subunits. Application of XP-RC to both haptoglobin phenotypes confirms that no modifications are present within their light chains and provides a wealth of information on glycosylation patterns of the heavy chains. N-Glycosylation patterns of both haptoglobin phenotypes were found to be consistent with bi- and triantennary structures of complex type that exhibit significant level of fucosylation and sialylation. However, multivariate analysis of haptoglobin 1-1 reveals higher number of the triantennary structures, in comparison to haptoglobin 2-1, as well as a higher extent of fucosylation. The glycosylation patterns deduced from the XP-RC/MS measurements are in agreement with the conclusions of the intact-mass analysis supplemented by limited charge reduction, suggesting that the latter technique can be employed in situations when fast assessment of protein heterogeneity is needed (e.g., process analytical technology applications).

Development of calibration-free/minimal calibration wavelength selection for iterative optimization technology algorithms toward process analytical technology application

As continuous manufacturing (CM) processes are developed, process analytical technology (PAT) via NIR spectroscopy has become an integral tool in process monitoring. NIR spectroscopy requires the deployment of complex multivariate models to extract the relevant information. The model of choice for the pharmaceutical industry is Partial Least Squares (PLS). However, the development of PLS can be burdensome due to the time and resource intensive requirements of calibration. To overcome this challenge, calibration-free/minimal calibration approaches have become of increasing interest. Iterative optimization technology (IOT) algorithms are a favorable calibration-free/minimal calibration approach with only the requirement of pure component spectra for successful active pharmaceutical ingredient (API) quantification. IOT algorithms were utilized to monitor potency trends (qualitative) and API content (quantitative) in a CM system and compared to a traditional PLS model. To overcome the reduced prediction performance of IOT during non-steady state conditions, a novel wavelength method based on variable importance in projection scores was employed. Overall, the success and value of IOT algorithms for application in CM settings was demonstrated.

Systematic assessment of process analytical technologies for biologics.

The application of process analytical technology (PAT) for biotherapeutic development and manufacturing has been employed owing to technological, economic, and regulatory advantages across the industry. Typically, chromatographic, spectroscopic, and/or mass spectrometric sensors are integrated into upstream and downstream unit operations in in-line, on-line, or at-line fashion to enable real-time monitoring and control of the process. Despite the widespread utility of PAT technologies at various unit operations of the bioprocess, a holistic business value assessment of PAT has not been well addressed in biologics. Thus, in this study, we evaluated PAT technologies based on predefined criteria for their technological attributes such as enablement of better process understanding, control, and high-throughput capabilities; as well as for business attributes such as simplicity of implementation, lead time, and cost reduction. The study involved an industry-wide survey, where input from subject matter industry experts on various PAT tools were collected, assessed, and ranked. The survey results demonstrated on-line liquid Chromatography (LC), in-line Raman, and gas analysis techniques are of high business value especially at the production bioreactor unit operation of upstream processing. In-line variable path-length UV/VIS measurements (VPE), on-line LC, multiangle light scattering (MALS), and automated sampling are of high business value in Protein A purification and polishing steps of the downstream process. We also provide insights, based on our experience in clinical and commercial manufacturing of biologics, into the development and implementation of some of the PAT tools. The results presented in this study are intended to be helpful for the current practitioners of PAT as well as those new to the field to gauge, prioritize and steer their projects for success.

Process monitoring of polysaccharide deketalization for vaccine bioconjugation development using in situ analytical methodology

Pneumococcal conjugate vaccines (PCVs) are formed by bioconjugation of a carrier protein to the purified capsular polysaccharide (Ps) from multiple serological strains of Streptococcus pneumoniae. The associated bioconjugation chemistry relies on initial selective modifications to the Ps backbone structure. Among these modifications, removal of a ketal functional group, termed deketalization, is one that is important for pharmaceutical PCV production. Herein, we report a process monitoring investigation into the deketalization of a polysaccharide relevant to PCV process development. We have applied process analytical technology (PAT) for in situ process monitoring to study the deketalization reaction in real time. We find that in situ FTIR spectroscopy elucidates multiple classes of reaction kinetics, one of which correlates strongly with the deketalization reaction of interest. This PAT approach to real time reaction monitoring offers the possibility of improved process monitoring in the pharmaceutical production of PCVs. To our knowledge, this report represents the first PAT investigation into Ps deketalization. Our findings suggest that broader application of PAT to the chemical modifications associated with PCV bioconjugation, as well as other pharmaceutically relevant bioconjugation processes, carries the power to enhance process understanding, control, and efficiency through real time process monitoring.

HOT MELT EXTRUSION IN ENGINEERING OF DRUG COCRYSTALS: A REVIEW

Crystal engineering technique has been widely explored in recent times to bring about changes in crystallinity which aids to achieve various goals such as solubility enhancement, stability and in vivo bioavailability without altering the chemical properties of the drug. Cocrystallisation is one of the crystal engineering approaches where the drug and an inert coformer are linked together by hydrogen bonding forming supramolecular homosynthon or heterosynthon using solvent-based or solvent-free techniques. Processing of active pharmaceutical ingredients with inert water-soluble coformers yields multicomponent crystalline cocrystals with high-performance characteristics and enhanced flow properties. Due to the emerging need of the industry for greener techniques, hot melt extrusion (HME), a continuous and solvent-free process is emerging as a field of interest in the mechanochemical synthesis of various pharmaceutical dosage forms such as solid dispersions, implants, ointments, and cocrystals. The current review emphasizes the role of HME as a cocrystallization technique for drugs to tailor-make their properties and ease of formulation. The distinct feature of HME is phase control during the process of cocrystallization. Furthermore, the selection of appropriate coformers with desirable water-solubility and stability features makes HME amenable to cocrystallization of versatile actives yielding suitable dosage forms. The application of process analytical technology further adds ease of monitoring during HME in cocrystallization approaches. Due to these salient features of HME, it can act as a prospective technique for cocrystallization of versatile drugs thus yielding dosage forms with desirable solubility and stability features.

Process analytical technology for on-line monitoring of quality attributes during single-use ultrafiltration/diafiltration.

Process analytical technology (PAT) is a fast-growing field within bioprocessing that enables innovation in biological drug manufacturing. This study demonstrates novel PAT methods for monitoring multiple quality attributes simultaneously during the ultrafiltration and diafiltration (UF/DF) process operation, the final step of monoclonal antibody (mAb) purification. Size exclusion chromatography (SEC) methods were developed to measure excipients arginine, histidine, and high molecular weight (HMW) species using a liquid chromatography (LC) system with autosampler for both on-line and at-line PAT modes. The methods were applied in UF/DF studies for the comparison of single-use tangential flow filtration (TFF) cassettes to standard reusable cassettes to achieve very high concentration mAb drug substance (DS) in the order of 100-200 g/L. These case studies demonstrated that single-use TFF cassettes are a functionally equivalent, low-cost alternative to standard reusable cassettes, and that the on-line PAT measurement of purity and excipient concentration was comparable to orthogonal offline methods. These PAT applications using an on-line LC system equipped with onboard sample dilution can become a platform system for monitoring of multiple attributes over a wide dynamic range, a potentially valuable tool for biological drug development and manufacturing.

Process analytical technology application for protein PEGylation using near infrared spectroscopy: G-CSF as a case study

Conjugation of protein therapeutics with polymers like polyethylene glycol (PEG) has been shown to increase their therapeutic efficiency. However, manufacturing of PEGylated drugs requires an additional, carefully controlled reaction step after purifying the protein, followed by further purification of over- and under-PEGylated variants. In this work, we have used a combined spectroscopic and statistical approach for monitoring and control of the PEGylation reaction for G-CSF using near infrared spectroscopy (NIRS). An online NIRS probe deployed in the reaction vessel has been used to track conversion of G-CSF into monoPEGylated and multiPEGylated forms using calibrated partial least squares regression models on the NIRS spectra which are collected in real time every 3 s. A pH probe integrated with a peristaltic pump facilitates automated quenching of the reaction at the targeted time. The NIRS spectra have also been used to build a batch evolution model for the reaction from end-to-end, including the addition of the reactants to the reaction vessel, the progress of the reaction for 70 min, and the final quenching with Tris base. Online spectra are compared against the statistical process control charts of the batch evolution model in real time to detect deviations as soon as they occur. The system was demonstrated for four common deviations in the PEGylation process, namely: delayed quenching time, wrong concentration of reducing agent added, wrong PEG to G-CSF ratio, and wrong sequence of addition of reactants. The system was able to identify all four deviations in real time and alert the operator to take control actions. The PAT approach suggested here embraces the quality by design framework and can be generalized for manufacturing scale monitoring and control of different biotechnology reactions with spectroscopic signatures.

Photoacoustic method for real-time assessment of salt content in aqueous solutions

In 2004, the Food and Drug Administration established the foundations for the application of process analytical technologies (PAT) in real-time control of the drug manufacturing process, where progress has been essentially directed to solid formulations. In order to enlarge the application of PAT principles to injectable drug products, the development of appropriate manufacturing process control tools is mandatory. Photoacoustics is a non-invasive technique with the potential for application in real-time control of the manufacturing process of injectable drug products. Herein, we applied a photoacoustic method for the determination of the concentration of salts (sodium chloride) in mono-salt formulations by measuring the changes induced in the speed of sound by density changes. This method was explored using two modes of generating the photoacoustic wave and two detectors with central frequencies of 10 MHz and 100 MHz. The results were analyzed using a 2k full-factorial design, considering the generation mode and detection as independent variables. The optimized method was subsequently validated according to the International Council for Harmonisation (ICH) standards. The method showed good linearity, precision, and accuracy, with a lower limit of quantification of 0.05% (w/v) of NaCl and a limit of detection of 0.02% (w/v) of NaCl. Due to its simplicity and high throughput, this method has potential applicability as PAT in the manufacturing of injectable drug products.

Application of Process Analytical Technology for Pharmaceutical Coating: Challenges, Pitfalls, and Trends.

Coating process is a critical unit operation for manufacturing solid oral dosage forms. For a long time, the coating weight gain has been discerned as the most important, if not only, characteristic describing the coating quality. As the introduction of quality by design (QbD) and advancement of process analytical technology (PAT), nowadays more techniques are available to analyze other quality attributes which have been overlooked but have substantial impacts on the performance of coated products. The techniques that permit rapid and non-destructive measurements are of particular importance to improve process operation and product quality. This article reviews the analytical techniques that have been and potentially could be used as PAT tools for characterizing the quality of pharmaceutical coating product. By identifying the challenges and pitfalls encountered during PAT application, the review aims at fostering the adoption of PAT for paving the way to enhanced quality and efficiency of the coating processes.

Process Analytical Technology Implementation for Peptide Manufacturing: Cleavage Reaction of Recombinant Lethal Toxin Neutralizing Factor Concatemer as a Case Study.

The α-chymotrypsin-based cleavage reaction is necessary for manufacturing peptides using rDNA technology with tandem repeats. The current work showcases application of process analytical technology (PAT) tools for monitoring and control of this reaction, using recombinant Lethal Toxin Neutralizing Factor (rLTNF) as a case study. At-line Fourier Transform infrared spectroscopy (ATR-FTIR) combined with attenuated total internal reflectance sampling accessory was exploited to monitor the reaction. PLS spectral calibration models were created for real-time quantification of concentrations of rLTNF concatemer and urea in the reaction mixture. An end-to-end PAT monitoring and control strategy was developed to address potential deviations and ensure that targets for yield, purity, and impurity profile are met for each batch. The impact of various deviations of process parameters outside the operating space, such as deviations in the reaction buffer, concentration of concatemer in the IBs, enzyme loading relative to protein concentration, and reaction time with late quenching were investigated. Variation in impurity profile over time in the case of late reaction quenching was determined through HPLC and mass spectrometry. It has been demonstrated how process signatures from the PAT tools across various batches and campaigns can be analyzed to facilitate real-time process monitoring and control.

Implementation of real-time and in-line feedback control for a fluid bed granulation process.

The application of process analytical technologies (PAT) to monitor critical quality attributes (CQAs) provides an important approach to enhance process understanding and improve the reliability of pharmaceutical production processes. The present study focuses on the first PAT based feedback control system for a fluid bed granulation batch process. Real-time particle size measurement by in-line spatial filtering technique (SFT) using a modified time-based buffer system was applied to define a target particle size after spraying a specific amount of binder solution. After identifying an appropriate control variable, a suitable strategy for feedback control was established, followed by tuning of the control loop to obtain best performance of the integrated system. By adapting the final target particle size within a specified range good functionality of the system could be demonstrated. Investigations of the robustness further showed that the implemented system enables the production of a predefined target particle size also by varying process and formulation parameters. The effect of increasing spray rates and binder concentrations on the particle size could be compensated in a given range by feedback control ensuring a predefined product quality. The study provides an advanced approach for quality assurance of fluid bed granulation.