Use of In-Line Near-Infrared Spectroscopy in Combination with Chemometrics for Improved Understanding of Pharmaceutical Processes

Chemometrics Approach Based on Wavelet Transforms for the Estimation of Monomer Concentrations from FTIR Spectra

Fourier-transform infrared (FTIR) spectroscopy can detect the presence of functional groups and molecules directly from a mixed solution of organic molecules. Although it is quite useful to monitor chemical reactions, quantitative analysis of FTIR spectra becomes difficult when various peaks of different widths overlap. To overcome this difficulty, we propose a chemometrics approach to accurately predict the concentration of components in chemical reactions, yet interpretable by humans. The proposed method first decomposes a spectrum into peaks with various widths by the wavelet transform. Subsequently, a sparse linear regression model is built using the wavelet coefficients. Models by the method are interpretable using the regression coefficients shown on Gaussian distributions with various widths. The interpretation is expected to reveal the relation of broad regions in spectra to the model prediction. In this study, we conducted the prediction of monomer concentration in copolymerization reactions of five monomers against methyl methacrylate by various chemometric approaches including conventional methods. A rigorous validation scheme revealed that the proposed method overall showed better predictive ability than various linear and non-linear regression methods. The visualization results were consistent with the interpretation obtained by another chemometric approach and qualitative evaluation. The proposed method is found to be useful for calculating the concentrations of monomers in copolymerization reactions and for the interpretation of spectra.

Real-Time Monitoring of Critical Quality Attributes during High-Shear Wet Granulation Process by Near-Infrared Spectroscopy Effect of Water Addition and Stirring Speed on Pharmaceutical Properties of the Granules

To produce high-quality pharmaceuticals, a real-time monitoring method for the high-shear wet granulation process (HSWG) was developed based on near-infrared spectroscopy (NIRS). Samples consisting of lactose, potato starch, and hydroxypropyl cellulose were prepared using HSWG with varying amounts of purified water (80, 90, and 100 mL) and impeller speed (200, 400, and 600 rpm), which produces granules of different characteristics. Twelve batches of samples were used for the calibration and nine batches were used for validation. After drying, the median particle size (D50), tapped density (TD), and Hauser ratio (HR) were measured. The best calibration models to predict moisture content (MC), D50, TD, and HR were determined based on pretreated NIR spectra using partial least squares regression analysis (PLSR). The temporal changes in the pharmaceutical properties under different amounts of water added and stirring speed were monitored in real time using NIRS/PLSR. Because the most important critical quality attribute (CQA) in the process was MC, granule characteristics such as D50, TD, and HR were analyzed with respect to MC. They might be used as robust and simple monitoring methods based on MC to evaluate the pharmaceutical properties of HSWG granules.

Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets

The tablet manufacturing process is a complex system, especially in continuous manufacturing (CM). It includes multiple unit operations, such as mixing, granulation, and tableting. In tablet manufacturing, critical quality attributes are influenced by multiple factorial relationships between material properties, process variables, and interactions. Moreover, the variation in raw material attributes and manufacturing processes is an inherent characteristic and seriously affects the quality of pharmaceutical products. To deepen our understanding of the tablet manufacturing process, multivariable modeling techniques can replace univariate analysis to investigate tablet manufacturing. In this review, the roles of the most prominent multivariate modeling techniques in the tablet manufacturing process are discussed. The review mainly focuses on applying multivariate modeling techniques to process understanding, optimization, process monitoring, and process control within multiple unit operations. To minimize the errors in the process of modeling, good modeling practice (GMoP) was introduced into the pharmaceutical process. Furthermore, current progress in the continuous manufacturing of tablets and the role of multivariate modeling techniques in continuous manufacturing are introduced. In this review, information is provided to both researchers and manufacturers to improve tablet quality.

Process Monitoring of Moisture Content and Mass Transfer Rate in a Fluidised Bed with a Low Cost Inline MEMS NIR Sensor

PURPOSE

The current trend for continuous drug product manufacturing requires new, affordable process analytical techniques (PAT) to ensure control of processing. This work evaluates whether property models based on spectral data from recent Fabry-Pérot Interferometer based NIR sensors can generate a high-resolution moisture signal suitable for process control.

METHODS

Spectral data and offline moisture content were recorded for 14 fluid bed dryer batches of pharmaceutical granules. A PLS moisture model was constructed resulting in a high resolution moisture signal, used to demonstrate (i) endpoint determination and (ii) evaluation of mass transfer performance.

RESULTS

The sensors appear robust with respect to vibration and ambient temperature changes, and the accuracy of water content predictions (±13 % ) is similar to those reported for high specification NIR sensors. Fusion of temperature and moisture content signal allowed monitoring of water transport rates in the fluidised bed and highlighted the importance water transport within the solid phase at low moisture levels. The NIR data was also successfully used with PCA-based MSPC models for endpoint detection.

CONCLUSIONS

The spectral quality of the small form factor NIR sensor and its robustness is clearly sufficient for the construction and application of PLS models as well as PCA-based MSPC moisture models. The resulting high resolution moisture content signal was successfully used for endpoint detection and monitoring the mass transfer rate.

Prediction of drug dissolution from Toremifene 80 mg tablets by NIR spectroscopy

The aim of our study was to justify substitution of dissolution analysis for NIR measurement of Toremifene 80 mg tablets. We studied implementation of a NIRS method by integrating the method development to discrimination power of the dissolution method. Hence, we analyzed 20 DoE tablet batches and studied which of the critical formulation factors affecting dissolution were statistically significant. To study if these factors can be detected by NIRS, PLS calibration models were developed. Finally, PLS model was built to correlate NIR data with the actual dissolution results to predict the released amount of toremifene in 30 min. To obtain the data the tablet batches were measured by NIR using diffuse reflectance technique and multivariate analysis tool was used to calibrate the NIRS models. Correlations between the critical formulation factors and the NIR spectra of Toremifene 80 mg tablet were shown and it was thus justified to develop a NIRS prediction model for dissolution. Variance (R²), standard error of estimate (SEE) and standard error of prediction (SEP) of the model were 90.0%, 4.3% and 5.9%, respectively. It was thus shown that multi-phased and time consuming dissolution procedure could be substituted for fast non-invasive NIRS method.

Investigation of the effects of particle size on fragmentation during tableting

Particle size is a critical parameter during tablet production as it can impact tabletability, flowability, and dissolution rate of the final product. The purpose of this study was to investigate the effect of initial particle size on fragmentation of pharmaceutical materials during tableting. Initial particle size fractions ranging from 0-125 to 355-500 µm of dibasic calcium phosphate (DCP), lactose monohydrate, and agglomerated and non-agglomerated microcrystalline cellulose (MCC) were blended with magnesium stearate and compressed into tablets. Larger initial particle sizes were found to fragment more extensively than smaller initial particle sizes for all materials based on the particle size distributions determined by laser diffraction. DCP was found to fragment most extensively followed by lactose and both MCCs. The fragmentation degrees of DCP, lactose, agglomerated and non-agglomerated MCC reached 95, 81, 32, and 29%, respectively. These findings were further supported by an increase in specific surface area with increasing compression pressure of compressed particles. The NIR spectral baseline offset from tablets was found to increase with increasing compression pressure up to 50 MPa for all materials, which was the same compression pressure range where fragmentation was observed. The NIR spectral slope from tablets as a function of compression pressure furthermore showed a similar trend as the tabletability profiles. NIR spectroscopy can thereby potentially be used as a surrogate control strategy for assessing compression related particle size changes and possibly tablet density and deformation behavior during tablet production.

Continuous Twin Screw Wet Granulation and Drying-Control Strategy for Drug Product Manufacturing

The use of continuous manufacturing has been increasing within the pharmaceutical industry over the last few years. Continuous direct compression has been the focus of publications on the topic to date. The use of wet granulation can improve segregation resistance, uniformity, enhance density, and flow properties for improved tabletability, or improve stability of products that cannot be manufactured by using a direction compression process. This article focuses on development of appropriate control strategies for continuous wet granulation (especially twin screw wet granulation) through equipment design, material properties and manufacturing process along with areas where additional understanding is required. The article also discusses the use of process analytical technologies as part of the control and automation approach to ensure a higher assurance of product quality. Increased understanding of continuous wet granulation should result in increased utilization of the technique, thereby allowing for an increase in diversity of products manufactured by continuous manufacturing and the benefits that comes with a more complex process such as wet granulation compared with direct compression process.

Development of a PAT tool for monitoring the Wurster coater performance

Real-time process analytical technology (PAT) is proposed as an effective approach for monitoring the performance of a Wurster coater. The coater was used for coating of 0.78 mm pharmaceutical pellets. The coating solution consisted of Hydroxypropyl methylcellulose/Poly ethylene glycol. During the coating process, small amounts of pellets (∼2 g) were sampled at 10 min. intervals and the pressure fluctuations were recorded at the same time. The signals were analyzed using the wavelet transform (WT) and decomposed into different sub-signals. Principal component analysis (PCA) was employed to the energies of these sub-signals, whose outliers were eliminated using the Mahalanobis distance method. The reference coating thickness data were obtained via spectrophotometry during the coating process. The partial least squares (PLS) regression was incorporated with the PCA for the development of a model for prediction of the coating thickness. The PLS regression revealed that the pressure fluctuations can be used to evaluate the thickness with a good precision. This study demonstrated the applicability of pressure fluctuations for the prediction of the coating thickness. This method can be regarded as a new robust, fast and non-intrusive PAT approach for monitoring the coating process which can be easily used by engineers and practitioners.

Acoustic emission detection of crystallization in two forms: monohydrate and anhydrous citric acid

Reliable monitoring of solution crystallization processes is important to provide further insight into process dynamics and to improve process control in the regimen of Process Analytical Technology (PAT), e.g. as the case studied here: detection of crystallization of the anhydrous and monohydrate forms of Citric Acid (CA). To set up the relationship between acoustic emission (AE) and crystallization form, two experiments (monohydrate and anhydrous citric acid) were carried out to specify the features and origins of the different acoustic signals emitted during batch cooling solution crystallization processes. Two kinds of AE experimental variables convey information about the development of crystallization processes: frequency and acoustic energy variables. The experimental results show notably that though it has less acoustic bursts, the acoustic activity generated by the crystallization of the monohydrate form of CA actually releases more acoustic energy than the crystallization of anhydrous form. It is also shown that the form of the crystallization is associated with the percentage of absolute energy. The proportion of the absolute energy [150-700 KHz] released by CA_m (43% of total absolute energy) in the total energy [0-700 KHz] is much more than that of CA_a (3% of total absolute energy).

Using 3D Printing for Rapid Prototyping of Characterization Tools for Investigating Powder Blend Behavior

There is an increasing need to provide more detailed insight into the behavior of particulate systems. The current powder characterization tools are developed empirically and in many cases, modification of existing equipment is difficult. More flexible tools are needed to provide understanding of complex powder behavior, such as mixing process and segregation phenomenon. An approach based on the fast prototyping of new powder handling geometries and interfacing solutions for process analytical tools is reported. This study utilized 3D printing for rapid prototyping of customized geometries; overall goal was to assess mixing process of powder blends at small-scale with a combination of spectroscopic and mechanical monitoring. As part of the segregation evaluation studies, the flowability of three different paracetamol/filler-blends at different ratios was investigated, inter alia to define the percolation thresholds. Blends with a paracetamol wt% above the percolation threshold were subsequently investigated in relation to their segregation behavior. Rapid prototyping using 3D printing allowed designing two funnels with tailored flow behavior (funnel flow) of model formulations, which could be monitored with an in-line near-infrared (NIR) spectrometer. Calculating the root mean square (RMS) of the scores of the two first principal components of the NIR spectra visualized spectral variation as a function of process time. In a same setup, mechanical properties (basic flow energy) of the powder blend were monitored during blending. Rapid prototyping allowed for fast modification of powder testing geometries and easy interfacing with process analytical tools, opening new possibilities for more detailed powder characterization.

In-Line Monitoring of a High-Shear Granulation Process Using the Baseline Shift of Near Infrared Spectra

Although near infrared (NIR) spectra are primarily influenced by undesired variations, i.e., baseline shifts and non-linearity, and many applications of NIR spectroscopy to the real-time monitoring of wet granulation processes have been reported, the granulation mechanisms behind these variations have not been fully discussed. These variations of NIR spectra can be canceled out using appropriate pre-processing techniques prior to spectral analysis. The present study assessed the feasibility of directly using baseline shifts in NIR spectra to monitor granulation processes, because such shifts can reflect changes in the physical properties of the granular material, including particle size, shape, density, and refractive index. Specifically, OPUSGRAN^®, a novel granulation technology, was investigated by in-line NIR monitoring. NIR spectra were collected using a NIR diffuse reflectance fiber optic probe immersed in a high-shear granulator while simultaneously examining the morphology, particle size, density, strength, and Raman images of the mixture during granulation. The NIR baseline shift pattern was found to be characteristic of the OPUSGRAN^® technology and was attributed to variations in the light transmittance, reflection, and scattering resulting from changes in the physicochemical properties of the samples during granulation. The baseline shift also exhibited an inflection point around the completion of granulation, and therefore may be used to determine the endpoint of the process. These results suggest that a specific pattern of NIR baseline shifts are associated with the unique OPUSGRAN^® granulation mechanism and can be applied to monitor the manufacturing process and determine the endpoint.

Quantitative Monitoring the Anti-Solvent Crystallization and Storage Process for Nandrolone by Near-Infrared Spectroscopy

A novel hydrate (S_H2O) of nandrolone was prepared by anti-solvent methods. The crystallization processes with 2 schemes (A and B) were monitored by in-line near-infrared (NIR) spectroscopy. The amounts of S_H2O in powder samples obtained by the anti-solvent crystallization and storage process were quantified by NIR combined with chemometrics methods. In-line NIR spectra from 4500 to 8000 cm^-1 were chosen to capture physicochemical changes during the whole crystallization process. The combination of the principal component results with offline characterization (scanning electron microscopy, powder X-ray diffraction, NIR) data showed that both schemes yielded high purity S_H2O products, but the crystallization speed of scheme B was significantly accelerated. It was demonstrated that in-line NIR spectroscopy combined with principal component analysis can be very useful to monitor in real time and control the anti-solvent crystallization process. Moreover, the solubility and the solid-state transformation of nandrolone under different storage conditions were investigated. The apparent solubility of S_H2O was 2.19-2.44 times of Form I, and S_H2O was relatively stable when stored at a high relative humidity and temperature below 25°C.

Real-time monitoring of granule properties during high shear wet granulation by near-infrared spectroscopy with a chemometrics approach

An in-line near-infrared spectroscopy monitoring method was developed for analyzing granule properties during a high shear wet granulation process.

A novel toolbox for E. coli lysis monitoring

The bacterium Escherichia coli is a well-studied recombinant host organism with a plethora of applications in biotechnology. Highly valuable biopharmaceuticals, such as antibody fragments and growth factors, are currently being produced in E. coli. However, the high metabolic burden during recombinant protein production can lead to cell death, consequent lysis, and undesired product loss. Thus, fast and precise analyzers to monitor E. coli bioprocesses and to retrieve key process information, such as the optimal time point of harvest, are needed. However, such reliable monitoring tools are still scarce to date. In this study, we cultivated an E. coli strain producing a recombinant single-chain antibody fragment in the cytoplasm. In bioreactor cultivations, we purposely triggered cell lysis by pH ramps. We developed a novel toolbox using UV chromatograms as fingerprints and chemometric techniques to monitor these lysis events and used flow cytometry (FCM) as reference method to quantify viability offline. Summarizing, we were able to show that a novel toolbox comprising HPLC chromatogram fingerprinting and data science tools allowed the identification of E. coli lysis in a fast and reliable manner. We are convinced that this toolbox will not only facilitate E. coli bioprocess monitoring but will also allow enhanced process control in the future.

Near infrared spectroscopic transmittance measurements for pharmaceutical powder mixtures

This study describes the development of near infrared (NIR) calibration models using transmittance measurements in powder samples and compares the results obtained with those of tablet transmittance and diffuse reflectance of powders. Transmission near infrared spectroscopy is a method widely used for the analysis of tablets in the evaluation of drug concentration due to the larger sample volume analyzed, but not commonly used for the analysis of powder samples. Diffuse reflection near infrared spectroscopy is a method used in both powder and tablets for the evaluation of quality attributes. In this initial study NIR transmittance measurements were obtained using an off-line spectrometer equipped with a high intensity light source. Spectra were obtained with three different resolutions for the analysis of powder and tablet samples of 7.50-22.50% (w/w) acetaminophen. The Partial Least Squares (PLS) calibration models developed include pretreatments such as Standard Normal Variate (SNV) and first derivative in the region from 9500-7500 cm(-1). Transmittance in powder presented low Root Mean Square Error of Prediction (RMSEP) values that varied from 0.23-1.15% (w/w) APAP with resolution of 64 and 16 cm(-1). The lowest RMSEP values (0.23-0.39% (w/w) APAP) were obtained using a resolution of 64 cm(-1). The RMSEP values for powder transmittance measurements were 2.4-5.6 times lower than the diffuse reflectance measurements of the powder mixtures.

A modified random forest approach to improve multi-class classification performance of tobacco leaf grades coupled with NIR spectroscopy

A novel approach, namely MC-UVE-RF, to improve multi-class classification performance of tobacco leaf grades by NIR spectroscopy.

A quality by design approach to scale-up of high-shear wet granulation process

High-shear wet granulation is a complex process that in turn makes scale-up a challenging task. Scale-up of high-shear wet granulation process has been studied extensively in the past with various different methodologies being proposed in the literature. This review article discusses existing scale-up principles and categorizes the various approaches into two main scale-up strategies - parameter-based and attribute-based. With the advent of quality by design (QbD) principle in drug product development process, an increased emphasis toward the latter approach may be needed to ensure product robustness. In practice, a combination of both scale-up strategies is often utilized. In a QbD paradigm, there is also a need for an increased fundamental and mechanistic understanding of the process. This can be achieved either by increased experimentation that comes at higher costs, or by using modeling techniques, that are also discussed as part of this review.

Detecting Blending End-Point Using Mean Squares Successive Difference Test and Near-Infrared Spectroscopy

An algorithm based on mean squares successive difference test applied to near-infrared and principal component analysis scores was developed to monitor and determine the blending profile and to assess the end-point in the statistical stabile phase. Model formulations consisting of an active compound (acetylsalicylic acid), together with microcrystalline cellulose and two grades of calcium carbonate with dramatically different particle shapes, were prepared. The formulation comprising angular-shaped calcium carbonate reached blending end-point slower when compared with the formulation comprising equant-shaped calcium carbonate. Utilizing the ring shear test, this distinction in end-point could be related to the difference in flowability of the formulations. On the basis of the two model formulations, a design of experiments was conducted to characterize the blending process by studying the effect of CaCO3 grades and fill level of the bin on blending end-point. Calcium carbonate grades, fill level, and their interaction were shown to have a significant impact on the blending process.

Sample presentation, sources of error and future perspectives on the application of vibrational spectroscopy in the wine industry

Vibrational spectroscopy encompasses a number of techniques and methods including ultra-violet, visible, Fourier transform infrared or mid infrared, near infrared and Raman spectroscopy. The use and application of spectroscopy generates spectra containing hundreds of variables (absorbances at each wavenumbers or wavelengths), resulting in the production of large data sets representing the chemical and biochemical wine fingerprint. Multivariate data analysis techniques are then required to handle the large amount of data generated in order to interpret the spectra in a meaningful way in order to develop a specific application. This paper focuses on the developments of sample presentation and main sources of error when vibrational spectroscopy methods are applied in wine analysis. Recent and novel applications will be discussed as examples of these developments.

Solvent-free melting techniques for the preparation of lipid-based solid oral formulations

Lipid excipients are applied for numerous purposes such as taste masking, controlled release, improvement of swallowability and moisture protection. Several melting techniques have evolved in the last decades. Common examples are melt coating, melt granulation and melt extrusion. The required equipment ranges from ordinary glass beakers for lab scale up to large machines such as fluid bed coaters, spray dryers or extruders. This allows for upscaling to pilot or production scale. Solvent free melt processing provides a cost-effective, time-saving and eco-friendly method for the food and pharmaceutical industries. This review intends to give a critical overview of the published literature on experiences, formulations and challenges and to show possibilities for future developments in this promising field. Moreover, it should serve as a guide for selecting the best excipients and manufacturing techniques for the development of a product with specific properties using solvent free melt processing.

On-line application of near-infrared spectroscopy for monitoring water levels in parts per million in a manufacturing-scale distillation process

An on-line analytical method based on transmission near-infrared spectroscopy (NIRS) for the quantitative determination of water concentrations (in parts per million) was developed and applied to the manufacture of a pharmaceutical intermediate. Calibration models for water analysis, built at the development site and applied at the manufacturing site, were successfully demonstrated during six manufacturing runs at a 250-gallon scale. The water measurements will be used as a forward-processing control point following distillation of a toluene product solution prior to use in a Grignard reaction. The most significant impact of using this NIRS-based process analytical technology (PAT) to replace off-line measurements is the significant reduction in the risk of operator exposure through the elimination of sampling of a severely lachrymatory and mutagenic compound. The work described in this report illustrates the development effort from proof-of-concept phase to manufacturing implementation.

Model-based analysis of high shear wet granulation from batch to continuous processes in pharmaceutical production--a critical review

The manufacturing of pharmaceutical dosage forms, which has traditionally been a batch-wise process, is now also transformed into a series of continuous operations. Some operations such as tabletting and milling are already performed in continuous mode, while the adaptation towards a complete continuous production line is still hampered by complex steps such as granulation and drying which are considered to be too inflexible to handle potential product change-overs. Granulation is necessary in order to achieve good flowability properties and better control of drug content uniformity. This paper reviews modelling and supporting measurement tools for the high shear wet granulation (HSWG) process, which is an important granulation technique due to the inherent benefits and the suitability of this unit operation for the desired switch to continuous mode. For gaining improved insight into the complete system, particle-level mechanisms are required to be better understood, and linked with an appropriate meso- or macro-scale model. A brief review has been provided to understand the mechanisms of the granulation process at micro- or particle-level such as those involving wetting and nucleation, aggregation, breakage and consolidation. Further, population balance modelling (PBM) and the discrete element method (DEM), which are the current state-of-the-art methods for granulation modelling at micro- to meso-scale, are discussed. The DEM approach has a major role to play in future research as it bridges the gap between micro- and meso-scales. Furthermore, interesting developments in the measurement technologies are discussed with a focus towards inline measurements of the granulation process to obtain experimental data which are required for developing good models. Based on the current state of the developments, the review focuses on the twin-screw granulator as a device for continuous HSWG and attempts to critically evaluate the current process. As a result, a set of open research questions are identified. These questions need to be answered in the future in order to fill the knowledge gap that currently exists both at micro- and macro-scale, and which is currently limiting the further development of the process to its full potential in pharmaceutical applications.

Towards better process understanding: chemometrics and multivariate measurements in manufacturing of solid dosage forms

The manufacturing of tablets involves many unit operations that possess multivariate and complex characteristics. The interactions between the material characteristics and process related variation are presently not comprehensively analyzed due to univariate detection methods. As a consequence, current best practice to control a typical process is to not allow process-related factors to vary i.e. lock the production parameters. The problem related to the lack of sufficient process understanding is still there: the variation within process and material properties is an intrinsic feature and cannot be compensated for with constant process parameters. Instead, a more comprehensive approach based on the use of multivariate tools for investigating processes should be applied. In the pharmaceutical field these methods are referred to as Process Analytical Technology (PAT) tools that aim to achieve a thorough understanding and control over the production process. PAT includes the frames for measurement as well as data analyzes and controlling for in-depth understanding, leading to more consistent and safer drug products with less batch rejections. In the optimal situation, by applying these techniques, destructive end-product testing could be avoided. In this paper the most prominent multivariate data analysis measuring tools within tablet manufacturing and basic research on operations are reviewed.

Chemometrics-based process analytical technology (PAT) tools: applications and adaptation in pharmaceutical and biopharmaceutical industries

Process analytical technology (PAT) is used to monitor and control critical process parameters in raw materials and in-process products to maintain the critical quality attributes and build quality into the product. Process analytical technology can be successfully implemented in pharmaceutical and biopharmaceutical industries not only to impart quality into the products but also to prevent out-of-specifications and improve the productivity. PAT implementation eliminates the drawbacks of traditional methods which involves excessive sampling and facilitates rapid testing through direct sampling without any destruction of sample. However, to successfully adapt PAT tools into pharmaceutical and biopharmaceutical environment, thorough understanding of the process is needed along with mathematical and statistical tools to analyze large multidimensional spectral data generated by PAT tools. Chemometrics is a chemical discipline which incorporates both statistical and mathematical methods to obtain and analyze relevant information from PAT spectral tools. Applications of commonly used PAT tools in combination with appropriate chemometric method along with their advantages and working principle are discussed. Finally, systematic application of PAT tools in biopharmaceutical environment to control critical process parameters for achieving product quality is diagrammatically represented.