Assessment of Recent Process Analytical Technology (PAT) Trends: A Multiauthor Review

Spatially Resolved Spectral Powder Analysis: Experiments and Modeling

Understanding the behavior of light in granular media is necessary for determining the sample size, shape, and weight when probing using fiber optic setups. This is required for a correct estimate of the active pharmaceutical ingredient content in a pharmaceutical blend via near-infrared spectroscopy. Several strategies to describe the behavior of light in granular and turbid media exist. A common approach is the Monte-Carlo simulation of individual photons and their description using mean free path lengths for scattering and absorption. In this work, we chose a complementary method by approximating these parameters via real physical counterparts, i.e., the particle size, shape, and density and the resulting chord lengths. Additionally, the wavelength dependence of refractive indices is incorporated. The obtained results were compared with those obtained in an experimental setup that included the SAM-Spec Felin probe head by Indatech for detecting spatially resolved spectra of samples. Our method facilitates the interpretation of the acquired experimental results by contrasting the optical response, the physical particle attributes, and the simulation results.

The Use of UV-Vis Spectroscopy in Bioprocess and Fermentation Monitoring

Real-time analytical tools to monitor bioprocess and fermentation in biological and food applications are becoming increasingly important. Traditional laboratory-based analyses need to be adapted to comply with new safety and environmental guidelines and reduce costs. Many methods for bioprocess fermentation monitoring are spectroscopy-based and include visible (Vis), infrared (IR) and Raman. This paper describes the main principles and recent developments in UV-Vis spectroscopy to monitor bioprocess and fermentation in different food production applications.

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.

Chain length effects on the vibrational structure and molecular interactions in the liquid normal alkyl alcohols

Alkyl alcohols are widely used in academia, industry, and our everyday lives, e.g. as cleaning agents and solvents. Vibrational spectroscopy is commonly used to identify and quantify these compounds, but also to study their structure and behavior. However, a comprehensive investigation and comparison of all normal alkanols that are liquid at room temperature has not been performed, surprisingly. This study aims at bridging this gap with a combined experimental and computational effort. For this purpose, the alkyl alcohols from methanol to undecan-1-ol have been analyzed using infrared and Raman spectroscopy. A detailed assignment of the individual peaks is presented and the influence of the alkyl chain length on the hydrogen bonding network is discussed. A 2D vibrational mapping allows a straightforward visualization of the effects. The conclusions drawn from the experimental data are backed up with results from Monte Carlo simulations using the simulation package Cassandra.

Development of an automated multi-stage continuous reactive crystallization system with in-line PATs for high viscosity process

Lower E-factor was obtained in an automated multi-stage continuous reactive-crystallization system.

Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody-peptide fusion

Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody-peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high-throughput (HT) micro-bioreactor system (AmbrTM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on-line and off-line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale-up. Biotechnol. Bioeng. 2017;114: 2222-2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

Monitoring of Batch Industrial Crystallization with Growth, Nucleation, and Agglomeration. Part 2: Structure Design for State Estimation with Secondary Measurements

This work investigates the design of alternative monitoring tools based on state estimators for industrial crystallization systems with nucleation, growth, and agglomeration kinetics. The estimation problem is regarded as a structure design problem where the estimation model and the set of innovated states have to be chosen; the estimator is driven by the available measurements of secondary variables. On the basis of Robust Exponential estimability arguments, it is found that the concentration is distinguishable with temperature and solid fraction measurements while the crystal size distribution (CSD) is not. Accordingly, a state estimator structure is selected such that (i) the concentration (and other distinguishable states) are innovated by means of the secondary measurements processed with the geometric estimator (GE), and (ii) the CSD is estimated by means of a rigorous model in open loop mode. The proposed estimator has been tested through simulations showing good performance in the case of mismatch in the initial conditions, parametric plant-model mismatch, and noisy measurements.

PAT-Based Control of Fluid Bed Coating Process Using NIR Spectroscopy to Monitor the Cellulose Coating on Pharmaceutical Pellets

Current endeavor was aimed towards monitoring percent weight build-up during functional coating process on drug-layered pellets. Near-infrared (NIR) spectroscopy is an emerging process analytical technology (PAT) tool which was employed here within quality by design (QbD) framework. Samples were withdrawn after spraying every 15-Kg cellulosic coating material during Wurster coating process of drug-loaded pellets. NIR spectra of these samples were acquired using cup spinner assembly of Thermoscientific Antaris II, followed by multivariate analysis using partial least squares (PLS) calibration model. PLS model was built by selecting various absorption regions of NIR spectra for Ethyl cellulose, drug and correlating the absorption values with actual percent weight build up determined by HPLC. The spectral regions of 8971.04 to 8250.77 cm^-1, 7515.24 to 7108.33 cm^-1, and 5257.00 to 5098.87 cm^-1 were found to be specific to cellulose, where as the spectral region of 6004.45 to 5844.14 cm^-1was found to be specific to drug. The final model gave superb correlation co-efficient value of 0.9994 for calibration and 0.9984 for validation with low root mean square of error (RMSE) values of 0.147 for calibration and 0.371 for validation using 6 factors. The developed correlation between the NIR spectra and cellulose content is useful in precise at-line prediction of functional coat value and can be used for monitoring the Wurster coating process.

Experimental cocrystal screening and solution based scale-up cocrystallization methods

Cocrystals are crystalline single phase materials composed of two or more different molecular and/or ionic compounds generally in a stoichiometric ratio which are neither solvates nor simple salts. If one of the components is an active pharmaceutical ingredient (API), the term pharmaceutical cocrystal is often used. There is a growing interest among drug development scientists in exploring cocrystals, as means to address physicochemical, biopharmaceutical and mechanical properties and expand solid form diversity of the API. Conventionally, coformers are selected based on crystal engineering principles, and the equimolar mixtures of API and coformers are subjected to solution-based crystallization that are commonly employed in polymorph and salt screening. However, the availability of new knowledge on cocrystal phase behaviour in solid state and solutions has spurred the development and implementation of more rational experimental cocrystal screening as well as scale-up methods. This review aims to provide overview of commonly employed solid form screening techniques in drug development with an emphasis on cocrystal screening methodologies. The latest developments in understanding and the use of cocrystal phase diagrams in both screening and solution based scale-up methods are also presented. Final section is devoted to reviewing the state of the art research covering solution based scale-up cocrystallization process for different cocrystals besides more recent continuous crystallization methods.

Pharmaceutical cocrystals, salts and polymorphs: Advanced characterization techniques

The main goal of a novel drug development is to obtain it with optimal physiochemical, pharmaceutical and biological properties. Pharmaceutical companies and scientists modify active pharmaceutical ingredients (APIs), which often are cocrystals, salts or carefully selected polymorphs, to improve the properties of a parent drug. To find the best form of a drug, various advanced characterization methods should be used. In this review, we have described such analytical methods, dedicated to solid drug forms. Thus, diffraction, spectroscopic, thermal and also pharmaceutical characterization methods are discussed. They all are necessary to study a solid API in its intrinsic complexity from bulk down to the molecular level, gain information on its structure, properties, purity and possible transformations, and make the characterization efficient, comprehensive and complete. Furthermore, these methods can be used to monitor and investigate physical processes, involved in the drug development, in situ and in real time. The main aim of this paper is to gather information on the current advancements in the analytical methods and highlight their pharmaceutical relevance.

Monitoring of Batch Industrial Crystallization with Growth, Nucleation, and Agglomeration. Part 1: Modeling with Method of Characteristics

This paper develops a new simulation model for crystal size distribution dynamics in industrial batch crystallization. The work is motivated by the necessity of accurate prediction models for online monitoring purposes. The proposed numerical scheme is able to handle growth, nucleation, and agglomeration kinetics by means of the population balance equation and the method of characteristics. The former offers a detailed description of the solid phase evolution, while the latter provides an accurate and efficient numerical solution. In particular, the accuracy of the prediction of the agglomeration kinetics, which cannot be ignored in industrial crystallization, has been assessed by comparing it with solutions in the literature. The efficiency of the solution has been tested on a simulation of a seeded flash cooling batch process. Since the proposed numerical scheme can accurately simulate the system behavior more than hundred times faster than the batch duration, it is suitable for online applications such as process monitoring tools based on state estimators.

A Novel Calibration-Minimum Method for Prediction of Mole Fraction in Non-Ideal Mixture

This article proposes a novel concentration prediction model that requires little training data and is useful for rapid process understanding. Process analytical technology is currently popular, especially in the pharmaceutical industry, for enhancement of process understanding and process control. A calibration-free method, iterative optimization technology (IOT), was proposed to predict pure component concentrations, because calibration methods such as partial least squares, require a large number of training samples, leading to high costs. However, IOT cannot be applied to concentration prediction in non-ideal mixtures because its basic equation is derived from the Beer-Lambert law, which cannot be applied to non-ideal mixtures. We proposed a novel method that realizes prediction of pure component concentrations in mixtures from a small number of training samples, assuming that spectral changes arising from molecular interactions can be expressed as a function of concentration. The proposed method is named IOT with virtual molecular interaction spectra (IOT-VIS) because the method takes spectral change as a virtual spectrum x _nonlin,i into account. It was confirmed through the two case studies that the predictive accuracy of IOT-VIS was the highest among existing IOT methods.

Process analytical techniques for hot-melt extrusion and their application to amorphous solid dispersions

Newly developed active pharmaceutical ingredients (APIs) are often poorly soluble in water. As a result the bioavailability of the API in the human body is reduced. One approach to overcome this restriction is the formulation of amorphous solid dispersions (ASDs), e.g., by hot-melt extrusion (HME). Thus, the poorly soluble crystalline form of the API is transferred into a more soluble amorphous form. To reach this aim in HME, the APIs are embedded in a polymer matrix. The resulting amorphous solid dispersions may contain small amounts of residual crystallinity and have the tendency to recrystallize. For the controlled release of the API in the final drug product the amount of crystallinity has to be known. This review assesses the available analytical methods that have been recently used for the characterization of ASDs and the quantification of crystalline API content. Well-established techniques like near- and mid-infrared spectroscopy (NIR and MIR, respectively), Raman spectroscopy, and emerging ones like UV/VIS, terahertz, and ultrasonic spectroscopy are considered in detail. Furthermore, their advantages and limitations are discussed with regard to general practical applicability as process analytical technology (PAT) tools in industrial manufacturing. The review focuses on spectroscopic methods which have been proven as most suitable for in-line and on-line process analytics. Further aspects are spectroscopic techniques that have been or could be integrated into an extruder.

Critical review of real-time methods for solid waste characterisation: Informing material recovery and fuel production

Waste management processes generally represent a significant loss of material, energy and economic resources, so legislation and financial incentives are being implemented to improve the recovery of these valuable resources whilst reducing contamination levels. Material recovery and waste derived fuels are potentially valuable options being pursued by industry, using mechanical and biological processes incorporating sensor and sorting technologies developed and optimised for recycling plants. In its current state, waste management presents similarities to other industries that could improve their efficiencies using process analytical technology tools. Existing sensor technologies could be used to measure critical waste characteristics, providing data required by existing legislation, potentially aiding waste treatment processes and assisting stakeholders in decision making. Optical technologies offer the most flexible solution to gather real-time information applicable to each of the waste mechanical and biological treatment processes used by industry. In particular, combinations of optical sensors in the visible and the near-infrared range from 800nm to 2500nm of the spectrum, and different mathematical techniques, are able to provide material information and fuel properties with typical performance levels between 80% and 90%. These sensors not only could be used to aid waste processes, but to provide most waste quality indicators required by existing legislation, whilst offering better tools to the stakeholders.

Real-time imaging as an emerging process analytical technology tool for monitoring of fluid bed coating process

A direct imaging system (Eyecon^TM) was used as a Process Analytical Technology (PAT) tool to monitor fluid bed coating process. Eyecon^TM generated real-time onscreen images, particle size and shape information of two identically manufactured laboratory-scale batches. Eyecon^TM has accuracy of measuring the particle size increase of ±1 μm on particles in the size range of 50-3000 μm. Eyecon^TM captured data every 2 s during the entire process. The moving average of D90 particle size values recorded by Eyecon^TM were calculated for every 30 min to calculate the radial coating thickness of coated particles. After the completion of coating process, the radial coating thickness was found to be 11.3 and 9.11 μm, with a standard deviation of ±0.68 and 1.8 μm for Batch 1 and Batch 2, respectively. The coating thickness was also correlated with percent weight build-up by gel permeation chromatography (GPC) and dissolution. GPC indicated weight build-up of 10.6% and 9.27% for Batch 1 and Batch 2, respectively. In conclusion, weight build-up of 10% can also be correlated with 10 ± 2 μm increase in the coating thickness of pellets, indicating the potential applicability of real-time imaging as an endpoint determination tool for fluid bed coating process.

Potential of vis-NIR spectroscopy to monitor the silica precipitation reaction

Controlling production online is an important issue for chemical companies. Visible and near-infrared (NIR) spectroscopy offers a number of important advantages for process monitoring, and has been used since the 1980s. For complex media such as silica precipitation samples, it is interesting to be able to study independently the scattering and absorption effects. From the scattering coefficient it is possible to extract information on the physical structure of the medium. In this work, the physical changes were monitored during a silica precipitation reaction by simple measurement of collimated transmittance NIR spectra. It is shown that it is possible to differentiate samples before and after the gel point, which is a key parameter for monitoring the process. From these NIR spectra the scattering coefficients were simply extracted, allowing a global vision of the physical changes in the medium. Then principal component analysis of the spectra allowed refinement of the understanding of the scattering effects, in combination with particle size monitoring.

Advances in downstream processing of biologics - Spectroscopy: An emerging process analytical technology

Process analytical technologies (PAT) for the manufacturing of biologics have drawn increased interest in the last decade. Besides being encouraged by the Food and Drug Administration's (FDA's) PAT initiative, PAT promises to improve process understanding, reduce overall production costs and help to implement continuous manufacturing. This article focuses on spectroscopic tools for PAT in downstream processing (DSP). Recent advances and future perspectives will be reviewed. In order to exploit the full potential of gathered data, chemometric tools are widely used for the evaluation of complex spectroscopic information. Thus, an introduction into the field will be given.

Respiration activity monitoring system for any individual well of a 48-well microtiter plate

BACKGROUND

Small-scale micro-bioreactors have become the cultivation vessel of choice during the first steps of bioprocess development. They combine high cultivation throughput with enhanced cost efficiency per cultivation. To gain the most possible information in the early phases of process development, online monitoring of important process parameters is highly advantageous. One of these important process parameters is the oxygen transfer rate (OTR). Measurement of the OTR, however, is only available for small-scale fermentations in shake flasks via the established RAMOS technology until now. A microtiter plate-based (MTP) μRAMOS device would enable significantly increased cultivation throughput and reduced resource consumption. Still, the requirements of miniaturization for valve and sensor solutions have prevented this transfer so far. This study reports the successful transfer of the established RAMOS technology from shake flasks to 48-well microtiter plates. The introduced μRAMOS device was validated by means of one bacterial, one plant cell suspension culture and two yeast cultures.

RESULTS

A technical solution for the required miniaturized valve and sensor implementation for an MTP-based μRAMOS device is presented. A microfluidic cover contains in total 96 pneumatic valves and 48 optical fibers, providing two valves and one optical fiber for each well. To reduce costs, an optical multiplexer for eight oxygen measuring instruments and 48 optical fibers is introduced. This configuration still provides a reasonable number of measurements per time and well. The well-to-well deviation is investigated by 48 identical Escherichia coli cultivations showing standard deviations comparable to those of the shake flask RAMOS system. The yeast Hansenula polymorpha and parsley suspension culture were also investigated.

CONCLUSIONS

The introduced MTP-based μRAMOS device enables a sound and well resolved OTR monitoring for fast- and slow-growing organisms. It offers a quality similar to standard RAMOS in OTR determination combined with an easier handling. The experimental throughput is increased 6-fold and the media consumption per cultivation is decreased roughly 12.5-fold compared to the established eight shake flask RAMOS device.

Use of near-infrared spectroscopy and multipoint measurements for quality control of pharmaceutical drug products

Near-infrared (NIR) spectroscopy is a non-destructive analytical technique that enables better-understanding and optimization of pharmaceutical processes and final drug products. The use in line is often limited by acquisition speed and sampling area. This work focuses on performing a multipoint measurement at high acquisition speed at the end of the manufacturing process on a conveyor belt system to control both the distribution and the content of active pharmaceutical ingredient within final drug products, i.e., tablets. A specially designed probe with several collection fibers was developed for this study. By measuring spectral and spatial information, it provides physical and chemical knowledge on the final drug product. The NIR probe was installed on a conveyor belt system that enables the analysis of a lot of tablets. The use of these NIR multipoint measurement probes on a conveyor belt system provided an innovative method that has the potential to be used as a new paradigm to ensure the drug product quality at the end of the manufacturing process and as a new analytical method for the real-time release control strategy. Graphical abstract Use of near-infrared spectroscopy and multipoint measurements for quality control of pharmaceutical drug products.

Quantitative determination based on the differences between spectra-temperature relationships

In the Near-infrared (NIR) spectral measurement it is not always possible to keep the experimental conditions constant. The fluctuations in external variables, such as temperature, will result in a nonlinear shift and a broadening of the spectral bands. In this study, the temperature-induced spectral variation coefficient (TSVC) was obtained by using loading space standardization (LSS). The relationship between TSVC and normalized squared temperature was quantitatively analyzed and applied to the quantitative determination of the compositions in mixtures. NIR spectra of peanut-soy-corn oil mixtures measured at seven temperatures were analyzed. It was found that, the relationship between TSVC and normalized squared temperature can be established by using LSS. Furthermore, the quantitative determination of the compositions in a mixture can be achieved by using the difference between the relationships, i.e., the slope of the relationship. The calibration curves between slope and composition volume are found to be reliable with the correlation coefficients (R(2)) as high as 0.9992. Quantitative determination by the calibration curves were also validated. Therefore, the method can be an effective tool for investigating the effect of temperature and quantitatively analysis.

Drop-on-Demand System for Manufacturing of Melt-based Solid Oral Dosage: Effect of Critical Process Parameters on Product Quality

The features of a drop-on-demand-based system developed for the manufacture of melt-based pharmaceuticals have been previously reported. In this paper, a supervisory control system, which is designed to ensure reproducible production of high quality of melt-based solid oral dosages, is presented. This control system enables the production of individual dosage forms with the desired critical quality attributes: amount of active ingredient and drug morphology by monitoring and controlling critical process parameters, such as drop size and product and process temperatures. The effects of these process parameters on the final product quality are investigated, and the properties of the produced dosage forms characterized using various techniques, such as Raman spectroscopy, optical microscopy, and dissolution testing. A crystallization temperature control strategy, including controlled temperature cycles, is presented to tailor the crystallization behavior of drug deposits and to achieve consistent drug morphology. This control strategy can be used to achieve the desired bioavailability of the drug by mitigating variations in the dissolution profiles. The supervisor control strategy enables the application of the drop-on-demand system to the production of individualized dosage required for personalized drug regimens.