Tools for Enabling Process Analytical Technology Applications in Biotechnology - Pharmaceutical Technology

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Tools for Enabling Process Analytical Technology Applications in Biotechnology
The success of process analytical technology (PAT), a recent initiative by FDA, depends to a large extent on efficient control of manufacturing processes to achieve predefined quality of the final product. In this paper, the authors review the various analytical methods that can enable use of PAT.


Pharmaceutical Technology
pp. s16-s22, s28-s31

The success of process analytical technology (PAT), a recent initiative by FDA, depends to a large extent on efficient control of manufacturing processes to achieve predefined quality of the final product. In this paper, the authors review the various analytical methods that can enable use of PAT. A critical evaluation of suitability of each analytical method as a PAT tool in terms of sampling (in-line, at-line, or on-line), sample preparation, duration of analysis, and its industrial application is performed.


Table I: Examples of the various combinations of analyzers and statistical tools that together form a PAT application.
PAT is a system for designing, analyzing, and controlling manufacturing through timely measurement (that is, during processing) of critical quality and performance attributes of raw and in-process materials and processes, with the goal of ensuring final product quality (1–3). Although the term analytical in PAT is broadly defined to include chemical, physical, microbiological, mathematical, and risk analysis conducted in an integrated manner (see Table I), the emphasis in this article is on analytical techniques that enable the monitoring of critical performance attributes of raw and in-process materials and processes during biotechnology manufacturing. However, it is important to understand that the goal of PAT is not only the use of these analytical techniques for monitoring, but also to control the manufacturing process to consistently yield the desired product quality.

Successful implementation of PAT requires the appropriate selection of a process analyzer. The selection of technique depends on the application and molecule, as well as the capability of the analytical method under consideration. In the biotechnology industry, drug products are manufactured using a series of unit operations. These products have to meet high expectations with respect to product quality, as documented in the pharmacopoeias and other regulatory documents. This is important to ensure the safety and efficacy of the manufactured drug substance and drug product. These requirements may be with respect to identity, content, quality, purity profile, moisture content, particle size, polymorphic form, and other such characteristics of the product. Traditional manufacturing involves the use of extensive analytical testing, most of which is retrospective as the data from analysis is received after the product lot has already advanced to the next process step. This approach results in a waste of manufacturing plant time, product rejects, scraps, and reprocessing (4). In contrast, PAT relies on enhanced process understanding to create controls that can result in continuous verification of product quality through all stages of manufacturing, reducing the chances of product loss.

Process analyzers play a key role in successful implementation of PAT and hence, are the focus of this paper. The analyzers may be used for monitoring of the critical quality attributes (CQAs) of the product, performance attributes of the process, and key characteristics of the various raw and in-process materials used in the process.

Process analytical techniques used in the biotech industry


Figure 1: Comparison of analyzers with respect to their ease of implementation in microbial fermentations and mammalian cell culture unit operations for various quality attributes: (a) misincorporation, (b) nutrients, (c) glycosylation, and (d) cell growth.
The demand for real-time and near-real-time monitoring in the past two decades has resulted in significant innovation and automation in the field of process analyzers. In the following subsections, we briefly review some of the commonly used process analysis techniques in the biotech industry (5).

Near-infrared (NIR) spectroscopy is one of the most commonly used analyzers for PAT applications. It is based on molecular overtone and combination vibrations. This analyzer typically utilizes a frequency range of 4000–12,500 cm-1 (800–2500 nm) to cover overtones and combinations of the lower energy fundamental molecular vibrations that include at least one X–H bond vibration. The functional groups involved in NIR (almost exclusively) are those involving the hydrogen atom: C-H, N-H, and O-H. A key advantage that NIR has is the possibility of direct measurement of the sample (6,7) either in situ, or after extraction of the sample from the process in a fast loop or bypass. The data from NIR measurements require multivariate analysis to extract the desired chemical information (8). NIR spectroscopy and multivariate data analysis (MVDA) has been successfully used for screening basal medium powders used in a mammalian cell culture in the biopharmaceutical industry (9) and also for at-line control and fault analysis of high cell-density fermentations (10). NIR probes also are used in crystallization processes to detect the particle size, shape, and the polymorphic form. This enables monitoring during routine production and determination of the crystallization endpoint (11).


Figure 2: Comparison of analyzers with respect to their ease of implementation in isolation and purification of biotech products: (a) removal of cell mass, (b) misfolds, (c) charge variants; and (d) mass variants.
Raman spectroscopy is a spectroscopic technique used to study vibrational, rotational, and other low-frequency modes in a system (12). A monochromatic light, usually from a laser in the visible, near-infrared, or near-ultraviolet range, interacts with molecular vibrations and phonons, resulting in the energy of the laser photons being shifted up or down. The shift in energy gives information about the compound in the system. Samples for analysis can be solids, liquids, gases, or any form in between, such as slurries, gels, and gas inclusions in solids. The Raman spectrum of water is extremely weak so direct measurements of aqueous systems are easy to do, giving this technique an advantage compared to infrared spectroscopy in which water has a very strong absorption. There is no inherent sample size restriction because it is fixed by the optic probe (13). Measurements can be made noninvasively or in direct contact with the targeted material (14). Applications in biotechnology processing include the monitoring of moisture content during lyophilization (15).


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