OR WAIT null SECS
© 2023 MJH Life Sciences™ and Pharmaceutical Technology. All rights reserved.
Pharmaceutical Technology Europe
When Pharmaceutical Technology Europe was established 20 years ago, PAT was not a hot topic in the industry. It was started in 2002 by FDA to modernize pharmaceutical manufacturing and increase the efficiency of manufacturing processes.
When Pharmaceutical Technology Europe was established 20 years ago, PAT was not a hot topic in the industry. It was started in 2002 by FDA to modernize pharmaceutical manufacturing and increase the efficiency of manufacturing processes.1,2 It consists of controlling and monitoring critical process parameters using timely measurements and an understanding of the process's physical and chemical phenomena, and the properties of excipients and APIs. Many of the elements of PAT were under development 20 years ago, but they lacked the driving force to encourage industry to innovate and implement these concepts.
FDA's concern with the efficiency of manufacturing processes may not seem to be consistent with the usual drug evaluation, inspection and compliance activities of the agency. However, FDA's mission statement includes a commitment to making safe and affordable products accessible to citizens. The PAT guidance states: "Efficient pharmaceutical manufacturing is a critical part of an effective US healthcare system. The health of our citizens (and animals in their care) depends on the availability of safe, effective, and affordable medicines."2
The availability of drugs cannot be taken for granted, as FDA's list of drug shortages usually contains several products, and many are usually related to manufacturing problems.3 The availability of 'affordable' medicines is also a subject of significant discussion.
Pharmaceutical manufacturing processes comprise a series of unit operations. However, the quality of the product is evaluated by analysis of the final dosage form at the end of the process. Current processes are characterized by fixed blending and lubrication times where the excipients and APIs received are expected to have the same physical and chemical properties as the previous batch. Most current processes are not designed to control the unavoidable variation in the properties of excipients and APIs.
PAT systems are part of the 'quality by design' (QbD) efforts outlined in the ICH Q8 guidance on pharmaceutical development, and can be used to improve process knowledge and efficiency of currently marketed products. The majority of the applications discussed in this article are PAT systems for small molecule pharmaceutical processes, but PAT may also be used for manufacturing APIs and biotechnology-derived drug products. PAT efforts must consider:
The PAT guidance provides FDA with a regulatory framework to evaluate manufacturing processes that involve PAT. Many of the approaches described in the PAT guidance were outlined by Callis and collaborators in 1987.4 The guidance does not describe any new scientific or technical approaches, but it provides an opportunity to use PAT and other innovative approaches to improve pharmaceutical manufacturing.
On the go...
The guidance was preceded by a number of pharmaceutical research efforts that could be considered the beginning steps for the current PAT initiative. For example, vision systems were evaluated to inspect the correct printing of lot numbers and expiration dates during packaging.5 There were also projects showing that near-infrared (NIR) spectroscopy could be used to identify placebo and drug-loaded tablets used in clinical studies, and identify raw materials for pharmaceutical manufacturing.6–9 The majority of the projects focused on achieving quality through inspection or substituting established quality control methods with faster ones that did not require sample preparation.10 However, it became increasingly difficult to justify these innovative projects because of concern that FDA would think their driving force was recurring problems within the company rather than quality improvement.
The PAT initiative has provided a window for innovation in pharmaceutical manufacturing. There is now a framework for regulators to consider and discuss innovative projects that will, ultimately, lead to higher quality products. This window of opportunity includes the possibility of having pharmaceutical processes where critical processes parameters are monitored and controlled leading to real time release of the product.
The goal of the PAT initiative is not to increase the number of PAT systems in the next 20 years, but to increase the efficiency of manufacturing processes. The essence of the PAT guidance is: "Within an established quality system and for a particular manufacturing process, one would expect an inverse relationship between the level of process understanding and the risk of producing a poor quality product."2
The next 20 years should include significant progress in relating excipient and API attributes to their effect on the final product. The PAT initiative is designed to build quality into products by using scientific principles to identify the raw material attributes and variables that affect and control the final product. Carvajal, Pinal and Morris, and their groups at Purdue University, have applied QbD through NIR spectroscopy and multivariate analysis to roller compaction to quantitatively assess the effects of different process variables on the properties of the obtained ribbons, as well as the downstream granules produced from the ribbons.11,12 Three different processes, roller compaction, powder mixing and high-shear wet granulation end-point have been studied. Research has shown that although the operating parameters of the process are critical in the production of the compacted ribbon, the raw material attributes of the formulation are just as important, if not more so, than the processing parameters. The particle size, true density and percentage of active ingredient in the formulation have all been identified as important parameters that influence the compaction of the ribbon. Furthermore, the line of best fit through the NIR spectrum of roller compacted ribbon can be used to extract the ribbon porosity, post milled particle size and the tensile strength of tablets produced from the milled ribbons. These correlations make the NIR slope an excellent tool to monitor the compacted ribbon and control the operating parameters of the roller compactor.
A large number of scientists have worked on applying PAT to pharmaceutical blending processes. Current blending processes are monitored using off-line techniques, where "time-defined end-points do not consider the effects of physical differences in raw materials", and batch failures may result even though the raw materials meet Pharmacopeia standards.2 Thief sampling techniques disturb the mixture, leading to sampling errors and sample biases causing misleading results.13 Noninvasive blend uniformity evaluation and real-time data collection have become a primary focus of researchers investigating blend monitoring techniques with the added benefit of realizing "real-time control and quality assurance during manufacturing", a principle advocated in the PAT guidance.2 Real-time blend monitoring feasibility studies have included NIR spectroscopy,14–18 Raman spectroscopy,19 laser-induced fluorescence,20 electrical capacitance tomography and thermal effusivity.21,22 NIR spectroscopy has received the most attention during the years, perhaps because of the fast analysis time and the wide range of materials that can be quantified. Real-time control and process understanding will facilitate formulation development according to the QbD approach.2,23
Several companies have created PAT groups and worked with FDA through PAT and QbD submissions.24 These groups are now using some of the methods developed by academic laboratories and implementing them in industry. They are providing valuable feedback to academic research laboratories, and suggesting future projects that will benefit pharmaceutical manufacturing. Furthermore, FDA has participated in numerous conferences and stressed the importance of engaging the agency as early as possible in the PAT and QbD efforts.25
Because of the cost of many of the sensors used in PAT studies, PAT is viewed as being only applicable to high-volume manufacturing processes, and as being out of reach for small-volume contract manufacturing companies. However, NIR or Raman systems at very reasonable costs may be used in laboratory-scale studies to start developing process understanding as illustrated in Figure 1. Drennen's group at Duquesne University (PA, USA) has modified an 8-quart V-blender with sapphire windows to obtain NIR spectra at 10 different locations, demonstrating that process knowledge can be obtained for laboratory batches at a very reasonable cost.26,27 Meanwhile, Taylor's group at Purdue University (IN, USA) used Raman spectroscopy in laboratory-scale experiments to investigate a lyophilization process.28
The methods developed by these groups may be used by a company to monitor a process in laboratory-scale experiments. The company can then continue to increase its process knowledge by monitoring the process in pilot-scale studies, and then bringing the PAT system to the manufacturing plant. In the future, process validation will be defined as the transfer of process knowledge from laboratory-scale experiments to the manufacturing plant, as illustrated in Figure 1. This new definition will replace the current 'three successful-lots' definition.
Figure 1: The relationship between pharmaceutical development, QbD validation, pharmaceutical validation and process knowledge.
Many companies are developing PAT methods and QbD approaches for the new products in their pipeline. However, it is also possible to implement PAT for currently marketed products, and companies embarking on PAT projects are asking: 'how much money, or what instruments should I place on my budget for next year?' This initial emphasis on new technology will shift to science and process understanding questions. As PAT evolves during the next 20 years, companies will include in their strategic plans the determination of critical process parameters for their products, as process understanding is necessary for the successful implementation of PAT.
For example, the technology to monitor granulation processes is already available, but the current challenge is the development of control methods.29–31 Thus, PAT in granulation requires understanding and controlling the physical phenomena occurring during granulation. Primary particles with specific size distribution are mixed and a binder is added to increase the probability of agglomeration.32 Depending on the ratio between large and small particles, the growing process could be slow, fast, stable or quasi-uncontrollable.33
The amount of binder and the concentration of the binder also play a key role in the strength of the granules, and the velocity of the particles in the growth rate.33 By understanding the particle growth phenomenon, the granulation process can be modelled by the population balance approach to allow development of a control strategy. For example, if the particle size distribution (PSD) of each material is determined before entering the granulator, adjustment in the amount of binder or paddle speed could be implemented to ensure constancy in the attributes of the granulation at the end of the process.
The drying process can be understood through energy and material balances.34 However, PSD is essential for determining mechanical operating conditions. For example, small particles (<100 μm) are difficult to fluidize and require high-air speed or low-pressure fluidization. High-speed fluidization increases the solvent removal at the beginning, but not towards the end of the drying (dominated by diffusion), where energy will be wasted. By understanding these phenomena, a control strategy with a sensor installed in the dryer to monitor the humidity content will help in maintaining an adequate fluidization, while minimizing the energy consumption in the diffusion period.
The challenges in the implementation of control strategies in pharmaceutical operations are not related to the strategy per se, but to the understanding of the process and the selection of adequate strategies. There are a number of developed control strategies that have been implemented for electrical, mechanical and chemical processes, and could be implemented in pharmaceutical processes.35,36 For example, a proportional integral derivative (PID) strategy could be used only between two variables, while a model predictive control strategy could be implemented for two or more outputs and inputs. Process understanding is essential to PAT, and is also the key to the selection between the PID and the model predictive strategies.
QbD and PAT will become part of companies' quality systems in the future. Harbour and Kieffer emphasized that quality systems are about the future, and are needed to describe how quality will be achieved by design and not by inspection.37 FDA has already issued guidance, based on ICH Q10, that emphasizes transfer of process knowledge from the product development units that are charged with QbD formulations to the manufacturing units that will be responsible for commercial production.38 Hopefully, the 40th anniversary issues of Pharmaceutical Technology Europe will include articles describing the success of QbD and PAT, and their incorporation in companies' quality systems.
PAT and QbD initiatives open the door to future pharmaceutical manufacturing processes where products are evaluated during pharmaceutical and API manufacturing before the process is completed.39–42 Data obtained while monitoring a process can be used to continuously improve the process. Quality assurance will not be an additional cost, but an element for continuous improvement in manufacturing and competitiveness. Real-time release of pharmaceutical products will become a reality within the next 20 years. The implementation of PAT will help pharmaceutical scientists and technical support personnel to be more productive in their process improvements efforts, as much of the information needed on critical process parameters will be available through the PAT system.43
The next 20 years will be an era with a marked increase in process understanding for pharmaceutical products. QbD of new pharmaceutical products will become expected and required. PAT is a tool used within QbD and its use will depend on whether the pharmaceutical process requires it. The main achievement will not be the implementation of new technology, but more reliable processes, as process knowledge is acquired during development, and commercial production is used to improve processes.
M.Teresa Carvajal is Assistant Professor of Industrial and Physical Pharmacy at Purdue University (IN, USA).
Manel Alcalá is a Post-Doctoral Research Associate in the NSF Engineering Research Center on Structured Organic Particulate Systems.
Carlos Velázquez is Associate Professor of Chemical Engineering at University of Puerto Rico-Mayagüez (Puerto Rico).
Rodolfo J. Romañach is Professor of Chemistry at University of Puerto Rico.
The authors acknowledge funding from the National Science Foundation, which has allowed them to collaborate in the Engineering Research Center on Structured Organic Composites.
1. R.J. Romañach, Pharm. Technol. Eur., 19(10), 47–51 (2007).
2. FDA Draft Guidance PAT — A Framework for Innovative Pharmaceutical Manufacturing and Quality Assurance, August 2003. www.fda.gov
3. FDA, Drug Shortages (2008). www.fda.gov/cder/drug/shortages/default.htm
4. J.B. Callis, D.L. Illman and B.R. Kowalski, Analytical Chemistry, 59:624A (1987).
5. J.G. Shabushnig, C.S. Foran and R.J. Romañach, Pharm. Technol., 13(9), 114 (1989).
6. P.K. Aldridge et al., Appl. Spectrosc., 48(10), 1272–1276 (1994).
7. M. Blanco and M.A. Romero, Analyst, 126(12), 2212–2217 (2001).
8. R.G. Whitfield, M.E. Gerger and R.L. Sharp, Appl. Spectrosc., 41(7), 1204–1213 (1987).
9. T. Herkert, H. Prinz and K.A. Kovar, Eur. J. Pharm. Biopharm., 51(1), 9–16 (2001).
10. J. Gottfries et al., J. Pharm. Biomed. Anal., 14, 1495–1503 (1996).
11. J.L.P. Soh et al., Journal of Pharmaceutical Innovation, 2(3–4), 106–124 (2007).
12. A. Gupta et al., J. Pharm. Sci. 2004, 93(4), 1047–1053 (2004).
13. J. Berman, PDA Journal of Pharmaceutical Science and Technology, 55, 209–222 (2001).
14. C. Ufret, K. Morris, Drug Dev. Ind. Pharm., 27(7), 719–729 (2001).
15. D. Ely, S. Chamarthy and M.T. Carvajal, Colloid. Surface. Physicochem. Eng. Aspect., 288(1–3), 71–76 (2006).
16. O. Berntsson et al., Powder Technol., 123(2–3), 185–193 (2002).
17. S. Sekulic et al., Anal. Chem. 68(3), 509–513 (1996).
18. R.D. Maesschalck et al., Appl. Spectrosc., 52(5), 725–732 (1998).
19. D.S. Hausman, R.T. Cambron, A. Sakr, Int. J. Pharm., 298(1), 80–90 (2005).
20. C.K. Lai, C.C. Cooney, J. Pharm. Sci., 93(1), 60–70 (2004).
21. N. Ehrhardt et al., Chem. Eng. Process., 44(2), 303–313 (2005).
22. G. Léonard et al., Powder Technol., 181(2), 149–159 (2008).
23. A.S. Hussain, Quality by Design (QbD) —Integration of Prior Knowledge and Pharmaceutical Development into CMC Submission and Review (2005). www.aapspharmaceutica.com
24. R. Guenard and G. Thurau, "Implementation of Process Analytical Technologies," in K.Bakeev, Ed., Process Analytical Technology (Blackwell Publishing, UK, 2005) pp 12–38.
25. P. Hernández et al., Journal of Process Analytical Technology, 3(6), 20–23 (2006).
26. A.S. El-Hagrasy et al., J. Pharm. Sci., 90(9), 1298–1307 (2001).
27. A.S. El-Hagrasy, F. D'Amico and J.K. Drennen, J. Pharm. Sci., 95(2), 392–406 (2006).
28. S. Romero-Torres et al., PDA Journal of Pharmaceutical Science and Technology, 61(2), 131–145 (2007).
29. R.L. Green et al., Anal. Chem., 77(14), 4515–4522 (2005).
30. P. Frake et al., Int. J. Pharm. 151(1), 75–80 (1997).
31. J. Rantanen et al., Anal. Chem., 77(2), 556–563 (2005).
32. A. Realpe and C. Velázquez, Chem. Eng. Sci., 63(6), 1602–1611 (2008).
33. B. Ennis, G. Tardos and R. Pfeffer, Powder Technol., 65(1–3), 257–272 (1991).
34. Z.H. Wang and G. Chen, Chem. Eng. Sci., 55(10), 1857–1869 (2000).
35. T. Edgar, D.Mellichamp and D. Seborg, Process Dynamics and Control, 2nd Ed. (Wiley & Sons, New York, NY, USA, 2004).
36. C.A. Smith and A.B. Corripio, Principle and Practice of Automatic Process Control, 3rd Ed. (Wiley & Sons, New York, NY, USA, 1997).
37. G.C. Harbour and R.C. Kieffer, "Quality Systems Management" in Encyclopedia of Pharmaceutical Technology (Marcel Dekker, New York, NY, USA, 2002), pp 3075–3081.
38. FDA Guidance for Industry — Quality Systems Approach to Pharmaceutical CGMP Regulations, September 2006. www.fda.gov
39. J.P. Higgins et al., Anal. Chem. 75(8), 1777–1785 (2003).
40. F. Wang et al., Organic Process Research and Development, 4(5), 391–395 (2000).
42. Y. Hu et al., Ind. Eng. Chem. Res. 44(5), 1233–1240 (2005).
43. R.J. Romañach, Pharm. Technol. Eur., Accepted for publication.