The optimization of process analytical technology for the inline quantification of multiple drugs in fixed dose combinations during continuous processing

Dadou, Suha; Tian, Yiwei; Li, Shu; Jones, David S.; Andrews, Gavin

doi:10.1016/j.ijpharm.2020.120024

Cited by 9 publications

(7 citation statements)

References 18 publications

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“…PAT tools are readily integrated within continuous API manufacturing processes. [169][170][171][172] They are often categorized as (I) In-Line PAT, in which the analyzer is located within the process stream; (II) On-Line PAT, in which a portion of the stream is diverted to the PAT tool for analysis and recycled back to the primary stream; (III) At-Line PAT, in which the analytical tool is located at a terminal point and the extracted sample is not returned to the process stream; and finally (IV) Off-Line PAT, in which a sample is manually extracted from the process stream by a technician and analyzed with a standalone PAT tool at a separate location, see Figure 12.…”

Section: Pat Tools For Continuous Manufacturing Of Api'smentioning

confidence: 99%

Continuous Manufacturing of Active Pharmaceutical Ingredients: Current Trends and Perspectives

Hyer,

Gregory,

Kay

et al. 2024

Adv Synth Catal

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The pharmaceutical industry has traditionally employed batch processing as a means of synthesizing active pharmaceutical ingredients (APIs) on a commercial scale. Batch manufacturing enables API synthesis in large quantities in order to meet regulations. Yet, this strategy remains cumbersome, is labor‐intensive, and creates complex logistical networks. In recent decades, batch API processing has gradually eroded American economic competitiveness and has led to the off‐shoring of API manufacturing from the United States. Today it is estimated that +80% of APIs are manufactured overseas. Meanwhile, disruptions from the Coronavirus Disease (SARS‐CoV‐2) have exacerbated weaknesses in the global supply chain, culminating with widespread shortages of critical life‐saving drugs. These shortages have emphasized the importance of reshoring drug manufacturing to the U.S. and fostered a regulatory landscape that seeks advanced methods of API manufacturing in order to bolster America’s supply chain resiliency. Recently, increased attention has been directed towards continuous drug manufacturing to enable nonstop API production within modular stand‐alone flow systems. Continuous manufacturing (CM) facilitates modular automation, offers new avenues towards process intensification, and even enables in‐line analytical monitoring from raw materials to packaged products. This strategy offers better conversion, increased safety, reduced waste, and overall cost savings versus traditional batch‐style processing. The rise of advanced API manufacturing, coupled with the current regulatory landscape, offers a rare window of opportunity to convert traditional batch pharmaceutical processes into continuous, streamlined production systems to on‐shore API manufacturing and eliminate drug shortages. This review will outline the current state‐of‐the‐art in the CM of APIs and will highlight the translation of chemistry and unit operations from batch processes to modular CM systems.

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Section: Pat Tools For Continuous Manufacturing Of Api'smentioning

confidence: 99%

Continuous Manufacturing of Active Pharmaceutical Ingredients: Current Trends and Perspectives

Hyer,

Gregory,

Kay

et al. 2024

Adv Synth Catal

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“…These six later runs were used as an external test set and allowed for an assessment of robustness. Note that similar studies on the validation of soft sensors for monitoring drug content using in-process NIR, Raman, or UV-Vis spectra typically have internal validation sets of fewer than ten runs and external test sets of the order of three to five runs (e.g., [5,36]).…”

Section: Performance Evaluationmentioning

confidence: 99%

NIR-Based Intelligent Sensing of Product Yield Stress for High-Value Bioresorbable Polymer Processing

Mulrennan

Munir

Creedon

et al. 2022

Sensors

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PLA (polylactide) is a bioresorbable polymer used in implantable medical and drug delivery devices. Like other bioresorbable polymers, PLA needs to be processed carefully to avoid degradation. In this work we combine in-process temperature, pressure, and NIR spectroscopy measurements with multivariate regression methods for prediction of the mechanical strength of an extruded PLA product. The potential to use such a method as an intelligent sensor for real-time quality analysis is evaluated based on regulatory guidelines for the medical device industry. It is shown that for the predictions to be robust to processing at different times and to slight changes in the processing conditions, the fusion of both NIR and conventional process sensor data is required. Partial least squares (PLS), which is the established ’soft sensing’ method in the industry, performs the best of the linear methods but demonstrates poor reliability over the full range of processing conditions. Conversely, both random forest (RF) and support vector regression (SVR) show excellent performance for all criteria when used with a prior principal component (PC) dimension reduction step. While linear methods currently dominate for soft sensing of mixture concentrations in highly conservative, regulated industries such as the medical device industry, this work indicates that nonlinear methods may outperform them in the prediction of mechanical properties from complex physicochemical sensor data. The nonlinear methods show the potential to meet industrial standards for robustness, despite the relatively small amount of training data typically available in high-value material processing.

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“…Over recent years, Raman spectroscopy technology has continued to be developed, and researchers have combined Raman spectroscopy technology with a variety of other technologies to make detection technologies more effective, such as confocal Raman microscopy [ 96 ], Raman imaging technology [ 97 , 98 ], resonance Raman technology [ 99 ], surface-enhanced Raman spectroscopy (SERS) technology [ 100 ], and so forth. Raman spectroscopy technology is widely used in the fields of medicine [ 101 ], pharmaceuticals [ 102 , 103 , 104 ], cosmetics [ 105 , 106 ], carbon materials [ 107 , 108 ], geology [ 109 , 110 ], and life sciences because of its ability to rapidly analyze chemical structures in a nondestructive manner and its powerful imaging functions. Compared with other spectroscopic techniques, Raman spectroscopy has improved analytical performance for samples in aqueous solutions, biological tissues, and cells because the Raman signal of water is very weak.…”

Section: Raman Spectroscopymentioning

confidence: 99%

Vibrational Spectroscopy in Assessment of Early Osteoarthritis—A Narrative Review

Chen

Zhao

et al. 2021

IJMS

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Osteoarthritis (OA) is a degenerative disease, and there is currently no effective medicine to cure it. Early prevention and treatment can effectively reduce the pain of OA patients and save costs. Therefore, it is necessary to diagnose OA at an early stage. There are various diagnostic methods for OA, but the methods applied to early diagnosis are limited. Ordinary optical diagnosis is confined to the surface, while laboratory tests, such as rheumatoid factor inspection and physical arthritis checks, are too trivial or time-consuming. Evidently, there is an urgent need to develop a rapid nondestructive detection method for the early diagnosis of OA. Vibrational spectroscopy is a rapid and nondestructive technique that has attracted much attention. In this review, near-infrared (NIR), infrared, (IR) and Raman spectroscopy were introduced to show their potential in early OA diagnosis. The basic principles were discussed first, and then the research progress to date was discussed, as well as its limitations and the direction of development. Finally, all methods were compared, and vibrational spectroscopy was demonstrated that it could be used as a promising tool for early OA diagnosis. This review provides theoretical support for the application and development of vibrational spectroscopy technology in OA diagnosis, providing a new strategy for the nondestructive and rapid diagnosis of arthritis and promoting the development and clinical application of a component-based molecular spectrum detection technology.

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The optimization of process analytical technology for the inline quantification of multiple drugs in fixed dose combinations during continuous processing

Cited by 9 publications

References 18 publications

Continuous Manufacturing of Active Pharmaceutical Ingredients: Current Trends and Perspectives

Continuous Manufacturing of Active Pharmaceutical Ingredients: Current Trends and Perspectives

NIR-Based Intelligent Sensing of Product Yield Stress for High-Value Bioresorbable Polymer Processing

Vibrational Spectroscopy in Assessment of Early Osteoarthritis—A Narrative Review

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