Anurag S. Rathore is a professor in the Department of Chemical Engineering at the Indian Institute of Technology Delhi,  Tel. +91.9650770650, asrathore@biotechcmz.com.

Anurag S. Rathore

Commercialization rights for novel therapeutic products are protected for a finite period by patents and other measures. After expiration of patents and other exclusivity rights, other manufacturers are allowed to make copies of these products, referred to as generics in the case of small-molecule pharmaceuticals and biosimilars in the case of biopharmaceuticals. Biosimilars are biological products that are highly similar to and have no clinically meaningful differences from an existing approved reference product. They offer improved affordability and are thus expected to have major impact on accessibility of biotherapeutics, including in developing and emerging economies. The global market value of biosimilars is expected to reach $36 billion by 2020.

	This article presents some key differences between the US and European regulation of biosimilars, including naming conventions and pharmacovigilance of biosimilars, and the impact of biosimilars on commercialization and affordability of biotherapeutics.

Biologics and Sterile Drug Manufacturing 2019

	When referring to this article, please cite it as A. Rathore et al., "Challenges with Successful Commercialization of Biosimilars," 

Pharmaceutical Technology Biologics and Sterile Drug Manufacturing 

Articles

This article presents some key differences between the US and European regulation of biosimilars, including naming conventions and pharmacovigilance of biosimilars, and the impact of biosimilars on commercialization and affordability of biotherapeutics.

Challenges with Successful Commercialization of Biosimilars

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.  

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 

), 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. 

 Table I: Examples of the various combinations of analyzers and statistical tools that together form a PAT application.			

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

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). 

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.			

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). 

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). 

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.			

Nuclear magnetic resonance (NMR) spectroscopy exploits the magnetic properties of atomic nuclei to determine physical and chemical properties of atoms or the molecules in which they are contained. It can provide detailed information about the structure, reaction state, dynamics, and chemical environment of molecules which can be an essential tool for PAT (16). Duarte and colleagues identified and characterized 30 compounds in beer through high resolution (HR)-NMR (17). Two-dimensional (2D) NMR spectroscopy has been used for metabolic flux analysis of high-density perfusion cultures of Chinese hamster ovary (CHO) cells lines (18). Bench-top (BT)-NMR has been used in characterization of emulsions and lipid ingredients and monitoring adsorption as a noninvasive tool in drug delivery research (19). 

Mass spectrometry (MS) uses the difference in mass-to-charge ratio (m/z) of ionized atoms or molecules to separate them from each other. It is useful for quantitation of atoms or molecules and also for determining chemical and structural information about them. Because of its inherent sensitivity, speed, and molecular selectivity, MS has been used for process analysis, including in-process monitoring of exhaust gases of fermentation processes, monitoring of drying processes, and environmental monitoring (20). Other applications include on-line, real-time deuterium abundance measurements in water vapor in aqueous liquids, including urine and serum (21); real-time quantification of trace gases in food products (22); and obtaining structural information for identification or structural elucidation of pharmaceutical drug products (23). 

Figure 3: Comparison of analyzers with respect to their ease of implementation in formulation and packaging: (a) moisture content, (b) product content, (c) foreign particles, and (d) labeling.			

Acoustic resonance spectroscopy (ARS) involves spectroscopic measurements in the acoustic region, primarily the sonic and ultrasonic regions. It is typically much more rapid than high performance liquid chromatography (HPLC) and NIR, and it is nondestructive, requiring no sample preparation because the sampling waveguide can simply be pushed into a sample powder, liquid, or solid (24). Applications include a high-throughput, nondestructive method of online analysis and label comparison before shipping to obviate the need for recall or disposal of a batch of mislabeled drugs (25). 

Calorimetry involves direct measurement of any endothermic or exothermic change in any process in order to better monitor or control all chemical, physical, and biological processes by providing the ability to measure enthalpy, power, and the heat coefficient (26). It is an on-line, nonintrusive technique for monitoring and optimizing a process. Applications include control of cooling profiles or rates during crystallization, real time measurement of heat transfer coefficient, monitoring and control of bioreactors, and determination of precise specific thermal profiles or signatures (27). 

Dielectric spectroscopy is also known as impedance spectroscopy and measures the dielectric properties of a material. It offers the ability to measure bulk physical properties of materials based on the interaction of an external field with the electric dipole moment of the sample. It has an advantage compared to other spectroscopic techniques because it is not an optical spectroscopy or a noncontact technique. This allows for measurement without disturbing a sample in process. This tool has been used as a real-time and in-line monitoring tool for process optimization, automation, consistent product quality, and cost reduction in mammalian and insect cell cultures (28). 

Fluorescence spectroscopy is a type of electromagnetic spectroscopy that analyzes fluorescence by using a beam of light, usually ultraviolet light, that excites the electrons in molecules of certain compounds and causes them to emit light at a lower energy (29). Fluorophores such as proteins, coenzymes, and vitamins can simultaneously be detected qualitatively and quantitatively inside and outside the cells. Cell metabolism and cell growth also can be measured (30). Teixeira and colleagues monitored on-line cell viability of recombinant baby hamster kidney (BHK) cell lines, as well as the concentration of the expressed glycoprotein IgG1-IL2 with 2D fluorometry and multivariate chemometric models (31). Other applications include real time monitoring of cell density and antibody titer in bioreactors containing CHO cell lines for production of monoclonal antibodies (32) and detection of antigen-antibody complexes for measuring immunoglobulin G (IgG) concentration in mammalian cell cultures (33). 

On-Line HPLC: Rathore and colleagues have published a series of case studies that examine the use of on-line HPLC, at pilot and manufacturing scales, for performing analyses to facilitate real-time decisions for column pooling based on product quality attributes (34, 35). HPLC also has been used for the monitoring of protein purity and levels of the different protein-related variants and impurities to enable the timely ending of refold on the basis of product quality data (36). The metabolism in a mammalian cell culture was examined by monitoring the concentration of 17 amino acids and glucose with online HPLC (37). Other applications include separation of recombinant human insulin-like growth factor-I (IGF) from IGF aggregate to allow for real-time control of column pooling (38) and using a combination of on-line size-exclusion HPLC, differential refractometry, and multiangle laser light scattering analysis (MALLS) for real-time estimation of product quality of a mutant form of the human immunodeficiency virus (HIV) vaccine protein antigen (39). 

In situ microscopy (ISM) involves the use of a direct-light microscope with a measuring chamber, integrated in a 25-mm stainless steel tube, as well as two CCD-cameras and two frame-grabbers. The data obtained are processed by an automatic image analysis system. The microscopic examination of the liquid is performed in the measuring chamber, which is situated near the front end of the sensor head. ISM mainly allows for on-line microscopic observation of microorganisms during fermentations in bioreactors (40). Applications include in-line monitoring of Hansenula anomala culture in a batch fermentation process; real-time monitoring of hybridoma cells concentration in a stirred bioreactor; measurement of the level of colonization of fibroblasts (murine cell line NIH-3T3) on microcarrier surfaces during cultivation; detection of cell viability without conventional staining techniques; and on-line monitoring of enzyme carriers to determine their mechanical stability in the bioreactor (41-45). 

Microwave resonance technology (MRT) is a noninvasive and nondestructive method of evaluating the moisture content of analytes using a microstrip waveguide with a resonance in the 300 MHz to 3 GHz range. It has been used for continuous moisture measurement in pharmaceutical granules and for determining moisture, temperature, and density of the granules to improve process understanding in fluid bed granulation (46). 

Terahertz technology has a frequency gap from 100 GHz to 30 THz in the electromagnetic spectrum, which is in between microwave and infrared and has found a variety of applications in biology, medical science, quality control of food, pharmaceutical, and agriculture products, as well as global environment monitoring. Terahertz time domain spectroscopy (THz-TDS) also has been applied to many materials, including biomolecules, medicines, cancer tissue, DNA, proteins, and bacteria (47). It enables 3D imaging of structures and materials, and the measurement of the unique spectral fingerprints of chemical and physical forms, which is especially relevant in 3D imaging of tablets (48) and estimation of concentrations of the various excipients (49). 

Photoacoustic spectroscopy (PAS) is based on the absorption of electromagnetic radiation by the molecules in the sample. The nonirradiative collisions of molecules in sample lead to warming of the sample matrix, which gives a pressure fluctuation because of thermal expansion that can be detected in the form of acoustic waves (50). These waves propagate through the volume of the gas to the detector (microphone, piezoelectric transducers, or optical method) where a signal is produced. This detector or microphone signal, when plotted as a function of wavelength, will give a spectrum proportional to the absorption spectrum of the sample (51). Applications include on-line and nondestructive monitoring of growth, thickness, and detachment of biofilms in waste water treatment plants and unraveling the influence of various process parameters (such as pH, flow conditions) on the structure and stability of a biofilm (52). 

Suitability of a process analyzer for PAT applications in biotechnology processes

There are several challenges when designing a PAT application that can be successfully implemented on the floor of the manufacturing plant (53,54). One of the most significant challenges is the time it takes to analyze compared to the time that is available for making decisions for a step before proceeding to the next unit operation (55,56). In a recent publication, this ratio of times has been proposed as an indicator of the ease of implementation of PAT for a given unit operation (57). 

presents an analysis of this ratio for a variety of unit operations and attributes. Ratios greater than one indicate that using the analytical method is feasible with the feasibility improving as the number increases. Ratios of one or less indicate that the analytical method cannot be used for PAT applications. It is shown in 

 that for each unit operation there are several methods that can be used to create a successful PAT application. There are a few trends that can be observed. First, while HPLC is one of the most important assays for characterization of biotechnology products, because of the large analysis time it is not well suited for most PAT applications. The emergence of ultrahigh-pressure liquid chromatography (UHPLC) as an alternative has somewhat alleviated this issue (34, 35). Second, spectroscopy-based methods such as NIR are well suited for PAT applications because of the rapid analysis that they offer. However, their use is limited by the quality and process attributes that they can monitor. Third, while techniques such as NMR and MS can be useful for several PAT applications, especially in the upstream part of the process, the instrumentation may not be easy to install in a manufacturing plant and also the samples in the upstream process may need to undergo a significant amount of sample preparation before they can be analyzed. Fourth and final, for any given unit operation there are several options available with respect to analytical methods that can be used for creating successful PAT applications. More case studies need to be performed to promote the widespread application of PAT concepts in the biotechnology industry. 

Table II: Suitable process analyzer for biopharmaceutical manufacturing process.			

Success of PAT depends to a large extent on efficient control of manufacturing processes to achieve predefined quality of the final product. This requires accurate and timely measurement of the critical attributes of the raw materials and process parameters and implies that capability of the analytical methods and their selection are critical for successful implementation of PAT. In this article, we reviewed the various analytical methods that enable the use of PAT. A critical evaluation of suitability of each analytical method as a PAT tool in terms of sampling (in-line, at-line, on-line), sample preparation, duration of analysis, and its industrial application was performed. It is our observation that while significant advancements have been accomplished with respect to our ability to analyze and monitor key process and quality attributes in the biotechnology industry, a lot more needs to be done with respect to utilizing the collected data for subsequent control of the process to achieve optimal yield and product quality. Only then shall we be able to achieve the benefits that will result from true PAT implementation. 

The authors would like to acknowledge support of Mr. Muralikrishnan T, Dr. Amarnath Chatterjee, Mr. Samuel Mathew, and Dr. Nitin Patil, all from Biocon Ltd. (Bangalore, India), for critical review of the manuscript.   

 is an associate Professor, Department of Chemical Engineering, Indian Institute of Delhi, and 

 is a professor emeritus of chemistry and chemical biology at Northeastern University. 

PAT Guidance for Industry— A Framework for Innovative Pharmaceutical Development, Manufacturing and Quality Assurance

 5. A.S. Rathore, R. Bhambure, and V. Ghare, 

Near-Infrared Technology in the Agricultural and Food Industries

 D.A. Burns and E.W. Ciurczak, Eds. (CRC Press, Taylor & Francis Group, Boca Raton, Florida, 2001) 22, 573–575.  

 8. M. Roman Balabin, Z. Ravilya Safieva, and I. Ekaterina Lomakina, 

 9. A.O. Kirdar, G. Chen, and A.S. Rathore,

 10. S. Gnoth, M. Jenzsch, R. Simutis, and A. Lubbert, 

In this paper, the authors review the various analytical methods that can enable use of PAT.

Tools for Enabling Process Analytical Technology Applications in Biotechnology

Quality by design (QbD) began to gain momentum in the biotechnology industry after FDA published its process analytical technology (PAT) guidance, PAT—A Framework for Innovative Pharmaceutical Manufacturing and Quality Assurance in 2004 (1). Global acceptance of QbD and PAT principles are reflected in the contents of the International Conference on Harmonization (ICH) quality guidelines: ICH Q8 

 (2–4). During the past seven years, industry and regulators have devoted significant resources to elucidate a path forward for implementing QbD in the drug-manufacturing environment and toward resolving the various challenges tied to successful implementation (5–8). To date, the first biotech drug application using a QbD approach has yet to be approved by FDA. Still, QbD principles are already being adopted widely throughout the biotechnology industry. This article provides an overview of QbD implementation for the development and commercialization of biologics and follow-on biologics.  

 (IMAGE: INFLUX PRODUCTIONS, PHOTODISK, GETTY IMAGES)			

QbD's beginnings and  cost of implementation

In the traditional approach to biotechnology production, manufacturers define a process and aim to perform the process consistently in a manner that the critical parameters are controlled within a narrow range so as to reduce variability in product quality. This approach has been successfully used to make safe and efficacious biotechnology products for the past few decades. However, because the process controls are fixed in this approach, any variability in raw materials, environmental controls, and/or process operations manifests as variability in product quality and results in lot failures (6–7). 

ICH Q8 defines QbD as "a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management" (2). Figure 1 illustrates a roadmap for QbD implementation and outlines the key steps that need to be taken to successfully implement QbD for a biologic drug (5-8). 

Figure 1: Illustration of key steps in implementation of QbD for a biotech product. Risk assessment and management, raw-material management, and statistical approaches are some of the elements that provide foundational support to the implementation (Ref. 5).			

The current environment, where the cost of healthcare has been recognized to be spiraling out of control, has forced biotechnology companies to become sensitive to the cost of manufacturing their products. It is not surprising then, that when the discussions around QbD first started, cost of implementation was highlighted as a major concern. Today, industry has realized that the benefits of QbD implementation outweigh the startup costs. The biotechnology industry does hope, however, that the approaches taken today to generate the required product and process information, will become more efficient and cost effective.  

As demonstrated in Figure 2, the market for these products is expected to pick up in 2012 as a significant number of innovator product patents expire through the year 2017. Expected expiries include Enbrel, Neulasta, Herceptin, Lantus, and Rituxan/Mab Thera. In Europe, a regulatory pathway already exists for follow-on biologics, and 14 such products have been approved (Abseamed, Binocrit, Biograstim, Epoetin-a hexal, Filgrastim hexal, Filgrastim ratiopharm, Nivestim, Omnitrope, Ratiograstim, Retacrit, Silapo, Tevagrastim, Valtropin and Zarzio) (9). A pathway, although approved, is still pending implementation in the United States. Established generic-drug companies, such as Teva Pharmceuticals and Sandoz, are expected to continue to play significant role in development and commercialization of follow-on biologics. At the same time, ewer players based in India and China are expected to emerge as potential follow-on manufacturers. It remains to be seen how companies in less-developed parts of the world will manage the high-cost dynamics of manufacturing these products. 

Figure 2: Upcoming patent expirations of 10 top-selling biopharmaceutical products (Data based on Ref. 9).			

				 Looking ahead, certain technologies and processes will need to be refined for QbD implementation in the biopharmaceutical industry (10).  			

 As noted, QbD implementation requires extensive process and product knowledge (6, 7). Acquiring this level of understanding requires extensive experimentation. In the current environment, where cost needs to be controlled, use of high-throughput tools and approaches has emerged as a means of saving considerable costs on needed chemicals, feed material, product, equipment, and most importantly, staff (11). There is a strong likelihood that widespread use of high-throughput tools and approaches will dramatically change how the biotech industry performs the various activities required for product and process development and commercialization in the next decade.   

Nonclinical studies as predictors of safety and/or efficacy.

 Industry at present relies heavily on clinical studies to assess drug safety and efficacy. Although advances have been made in the past decade with regard to industry's ability to model safety and/or efficacy through nonclinical studies, more is needed to reduce reliance on human clinical trials (10). Developments in the way drugs are discovered and in molecular design are expected.  

Use of statistical approaches and risk management.

 QbD implementation requires extensive information about the product and its manufacturing process. However, in view of the large number of variables and attributes that interplay to impact safety and efficacy of a biotechnology product, it is not possible to evaluate the effect of every variable. Statistical approaches, such as design of experiments (DOE) and multivariate data analysis (MVDA), along with risk management tools such as the Failure Modes and Effects and Analysis (FMEA), can help to ensure that resources are spent on the most important tasks.  

 Thus far, QbD implementation has been limited to large and mid-size biotechnology companies in the US and the Europe. As manufactures based in India and China start producing follow-on biologics for the European and the US markets, they too will start imbibing QbD principles. Some of these companies have already started this alignment. In the near future, the biotechnology industry is likely to see a major overhaul of scientific and quality-based manufacturing approaches as well as a more global adoption of QbD principles.  

The economics of developing and commercializing follow-on biologics, in particular in Asia, necessitate that manufacturers cannot merely replicate process and product development practices that have been established at US and European manufacturers. The raised expectations of the regulatory agencies, as represented by the PAT and ICH guidelines, will need to be met. For QbD implementation, the next decade is likely to witness an evolution into a more cost-efficient approach, driven by innovation in the areas mentioned herein and beyond.  

 is a faculty member in the Department of Chemical Engineering at the Indian Institute of Technology, Hauz Khas, New Delhi, 110016, India, +91 96 5077 0650, 

Guidance for Industry: PAT—A Framework for Innovative Pharmaceutical Development, Manufacturing and Quality Assurance 

 3. ICH, Q9 Quality Risk Management (Geneva, June 2006).  

 4. ICH, Q10 Pharmaceutical Quality Systems (Geneva, September, 2006).  

 7. S. Kozlowski and P. Swann, "Considerations for Biotechnology Product Quality by Design," in Quality by Design for Biopharmaceuticals: Perspectives and Case Studies, Eds. A.S. Rathore and R. Mhatre (Wiley Interscience 2009), pp. 9-30. 

 11. R. Bhambure, K. Kumar, and A. S. Rathore, 

(2010), doi:10.1016/j.tibtech.2010.12.001.  

The author provides an overview of QbD implmentation for biopharmaceuticals.

Quality by Design for Biologics and Biosimilars

References for the article published in the print issue of 

FDA PAT Guidance for Industry  A Framework for Innovative Pharmaceutical Development, Manufacturing and Quality Assurance, September 2004. 

FDA Guidance for Industry: Q8 Pharmaceutical Development May 2006. Q8 Annex Pharmaceutical Development, Step 3, November, 2007.

FDA Guidance for Industry: Q9 Quality Risk Management, June 2006.

FDA Guidance for Industry: Q10 Quality Systems Approach to Pharmaceutical CGMP Regulations, September, 2006. 

A.S. Rathore and H. Winkle, Nature Biotechnology, 27, 2634 (2009). 

S. Kozlowski and P. Swann, "Considerations for biotechnology product Quality by Design," in A.S. Rathore and R. Mhatre, Eds, Quality by Design for Biopharmaceuticals: Perspectives and Case Studies (Wiley Interscience, NJ, USA 2009) pp 930. 

A.S. Rathore et al., BioPharm Intl., 21(12), 3741 (2008). 

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A.S. Rathore, R. Branning and D. Cecchini, BioPharm Intl., 20(4), 3640 (2007). 

A.S. Rathore et al., BioPharm Intl., 22(1), (2009). 

J. Harms et al., Biotech. Prog., 24(3), 655662 (2008). 

P. van Hoek et al., "Case Study on Definition of Design Space for a Microbial Fermentation Step," in A.S. Rathore and R. Mhatre, Eds, Quality by Design for Biopharmaceuticals: Perspectives and Case Studies, (Wiley Interscience, NJ, USA, 2009) pp 85109. 

D.J. Cecchini, "Applications of design space for biopharmaceutical purification processes," in A.S. Rathore and R. Mhatre, Eds, Quality by Design for Biopharmaceuticals: Perspectives and Case Studies (Wiley Interscience, NJ, USA, 2009) pp. 127141. 

P.K. Watler and J. Rozembersky, "Application of QbD principles to tangential flow filtration operations," in A.S. Rathore and R. Mhatre, Eds, Quality by Design for Biopharmaceuticals: Perspectives and Case Studies (Wiley Interscience, NJ, USA, 2009) pp 111125. 

K. Ng and N. Rajagopalan, "Application of Quality by Design and risk assessment principles for the development of formulation design space," in A.S. Rathore and R. Mhatre, Eds, Quality by Design for Biopharmaceuticals: Perspectives and Case Studies (Wiley Interscience, NJ, USA, 2009) pp 161174. 

A.S. Rathore, Trends in Biotechnology, 27, 546553 (2009). 

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S. Kozlowski, BIO/FDA Liaison Meeting on QbD (September 2008). 

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A.O. Kirdar et al., Biotech. Prog., 23, 6167 (2007). 

A.A. Shukla et al., Journal of Chromatography B, 848(1), 2839 (2008). 

B.S. Kendrick et al., BioPharm Intl., 22(8), 3244 (2009). 

D.M. Boyle et al., Biotechnol. Appl. Biochem., 54(2), 8592 (2009). 

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M.A. Schenerman et al., "Using a Risk Assessment Process to Determine Criticality of Product Quality Attributes," in A.S. Rathore and R. Mhatre, Eds, Quality by Design for Biopharmaceuticals. Wiley Interscience, NY, USA, 2009) pp 5384. 

FDA, Notice of pilot programme for submission of quality information for biotechnology products in the Office of Biotechnology Products, Docket number FDA-2008-N-03551. 

References for the article published in the February issue of Pharmaceutical Technology Europe.

Quality by Design for biotechnology products: challenges and solutions &#151; References

The number of biotechnology-based human therapeutic products in the late-stage pipeline along with the average cost to commercialize a biotech product has been steadily increasing with time. In addition, the biotech industry is facing unprecedented challenges of a sagging global economy and rising regulatory expectations. Companies have to continue to evolve their approaches to be more efficient with respect to time, resources and cost. This article describes some of the technologies that can help optimize time and cost of biopharmaecutical manufacturing.

Creating processes that are not only optimal and robust, but also economical in a time and resource efficient manner is the Holy Grail for the biotech industry today. Regulatory initiatives such as Quality by Design and PAT require an improved process understanding earlier in the product life cycle.

Recent advances in fermentation and cell culture processes have increased cell densities and protein titers in process fluids, requiring reliable upstream technologies to handle growing production demands.

 Moreover, within the bioprocessing industry there is a strong trend toward the application of single-use technologies, eliminating the expense of cleaning and cleaning validation, a major cost factor in operating reusable systems. One of the commonly used technologies for primary separation after fermentation is tangential flow filtration (TFF).

 TFF processes have traditionally used cassettes or hollow fiber formats. Typically, TFF cassettes are installed in stainless steel housings that require post-use cleaning and validation of cleaning. The installation and preconditioning steps before process use are time consuming and require a reasonable level of skill to avoid potential malfunction. Hollow fiber filter systems provide an alternative primary separation technology. However, this open channel format tends to require relatively high pumping rates for optimal performance. Achieving these high rates with fully disposable equipment can be difficult.

Membrane chromatography has already proven to be a powerful alternative to traditional packed‑bed chromatography in flow‑through operations, such as polishing for the removal of viruses and contaminants in biologics manufacturing.

 Case studies have been described for the purification of monoclonal antibodies (mAbs) with a high isoelectric point and have demonstrated the popularity of their implementation. As flow‑through utilization has expanded, membrane chromatography applications have also included the capturing of large molecules.

 Such bind‑and‑elute applications imply the demand for higher capacity and larger surface membrane area compared with flow‑through applications.

Manufacturers of biopharmaceuticals are required to characterize the ability of key process steps to clear viruses. Typically, the entire manufacturing process is qualified to attain a cumulative virus reduction factor, which significantly contributes to the documentation of virus safety. In many of these manufacturing processes, a virus retentive filter is used to achieve a robust and effective virus clearance step. The key to implementing virus filtration is the assurance of virus retention and device integrity while maintaining high productivity and ease of use.

While developments in chromatography media (resins) have brought the technique much closer to practical and theoretical limits of binding capacity, future advances are likely to focus on new surface chemistries and a more efficient use of chromatography as a unit operation. One way to gain productivity improvements is to use smaller equipment or the similar size equipment in a more time‑efficient manner.

 series and will present some of the most promising technologies that are being introduced in biotech manufacturing by some of the major biopharmaceutical vendors.

TFF microfiltration capsule for cell clarification and harvest


The Kleenpak TFF microfiltration (MF) capsule from Pall Life Sciences (NY, USA) uses an Ultipleat pleated filter cartridge and Kleenpak Nova capsule with their operation based on TFF principles. The capsule is configured similarly to hollow fibers or cassette formats with feed, retentate and permeate ports. As Figure 1 shows, the pleated construction is used inside the capsule to create multiple parallel flow channels while increasing the effective membrane area in a reduced footprint. It is simple to install and requires limited preconditioning before exposure to process fluid. 

This technology has been tested with representative industrial strains such as Chinese hamster ovary (CHO) cells, and bacteria such as 

 and yeast. Feed volumes of 50100 L have been processed per single full‑scale capsule (0.5 m

), depending on cell type and characteristics. The capsules can be manifolded together in series or in parallel to accommodate larger process requirements; for example, a six capsule assembly can process up to 1000 L. Stable performance has been observed for mAb clarification from CHO cell feed with starting cell counts up to 1x107 cells/mL and step yields of greater than 98% have been obtained. For clarification of hybridoma cells expressing mAbs, filtrate flux rates of 70 L/m

/h (LMH) to a volumetric throughput (VT) of 180 L/m

 have been obtained with a protein transmission of 100%. Protein expression for these cells was approximately 0.1 mg/mL.

A comparison of the Kleenpak TFF technology and two different types of cassettes for concentrating 

 with all three devices incorporating membranes rated at 0.2 μm (nominal) is presented in Figure 2. 

All three devices were operated at a crossflow flux rate (CFF) of 1.5 L/min/ft

. A five-fold volumetric concentration followed by a three‑fold diafiltration buffer exchange was performed. The data show that all three devices can be operated at a flux rate of 30 LMH throughout both concentration and diafiltration stages. Although the start and finish transmembrane pressure (TMP) values are different for the Kleenpak TFF filter compared with the cassette formats, the TMP gradient is similar for all three technologies and suggests stable operation. The flux and throughput performance of all three technologies was similar during these trials. Figure 3 presents a comparison of a Kleenpak TFF MF capsule with a Pall Microza hollow fiber module for clarification of IgG from a CHO cell culture with a cell density of approximately 2x106/mL.

 Each format was operated at a pumping capacity or CFF of 20 L/min/m

. It is seen that the Kleenpak TFF outperforms the hollow fiber module by processing more than three times the filtrate volume for a similar terminal TMP. 

Experiments were conducted with a recombinant 

solution at a cell density of approximately 4% w/w for production of a plasmid used for gene therapy treatment. The primary objective of the application was to concentrate the 

feed by a minimum concentration factor of 10‑fold using a single‑use technology. Initial trials were conducted with the small‑scale device and the filtrate flux rate for concentration was selected to be 22.5 LMH. It was estimated that six full-scale modules (membrane area of 3 m

) will be required to process 500 L of feed at a feed flow rate of approximately 21 L/min (CFF of 7 L/min/m

). To demonstrate scalability to a series and parallel configuration, a trial was conducted to compare the performance of a single full-scale module against the performance of three full‑scale modules operated in series. The filtrate flux rate was maintained at 22.5 LMH for each module throughout the trial. Pressure gauges were installed throughout the system to enable accurate TMP determination across each module. The results shown in Figure 4 indicate that each of the three capsules manifolded together in series provided a VT 

 TMP curve very similar to a single module operated in isolation. 

In summary, the Kleenpak TFF MF capsules’ single‑use TFF technology offers major benefits for cell harvesting and clarification. The self‑contained format eliminates the need to purchase and install holders or housings, and also reduces exposure to biologically active solutions. This is a critical consideration for manufacturers of vaccines and other products that present potential workplace hazards. The optimized feed channel screen provides good performance at low flows and the technology is scalable and reproducible.

Hydrophobic interaction membrane chromatography


Sartobind Phenyl membrane adsorber from Sartorius Stedim Biotech (Germany) uses hydrophobic interaction chromatography (HIC) principles and assembled into a 30‑layer radial flow process capsule (Sartobind). It is based on hydrophilic regenerated stabilized cellulose with the hydrophobic phenyl groups covalently attached to the cellulose matrix. The novel macroporous membrane structure with 13 µm pores has been designed for high flow rates and high binding capacities. As seen in Table 1, the binding capacity for a mAb on HIC membrane is found to be at par with conventional HIC resins even at significantly higher flow rates. 

Table 1: Protein binding capacity on Sartobind Phenyl Membrane and conventional Phenyl Resin. Binding buffer for mAb: 08 M (NH

Upcoming technologies to facilitate more efficient biologics manufacturing

Creation and qualification of scale-down models is essential for performing several critical activities that support process validation and commercial manufacturing. This article is the second of two parts covering scaling down biopharmaceutical operations, Part I was published in April 2006 and detailed fermentation. In this segment, we present some guidelines and examples for scale-down of common downstream unit operations used in biotech processes — chromatography and filtration. 

In theory, chromatography is one of the more straightforward unit operations to scale down. Factors at the large scale such as column-header design and packing can be difficult to control and may result in reduced accuracy of the scale-down model. This section presents a review of general guidelines for scaling down.  

Use representative feed streams, preferably from full-scale manufacturing. First perform a complete analysis of product concentration, quality attributes and other feed stream characteristics (such as pH and conductivity) to ensure a good match. If possible, use feed streams from different lots at small scale to learn about the effect of feed stream quality on the performance. In addition, acquire some knowledge of the storage and stability of the feed stream material. Storage-related degradation of the inventory could affect the outcome of the small-scale runs. 

Use a representative chromatography resin. It would be ideal to have resin from the lot being used at full scale. If you can't obtain GMP-released resin, then make a match based on the vendor's certificate of analysis. 

 Figure 1 Chromatographic profiles of small- and large-scale columns. Raw material is a proprietary aqueous solution that has undergone one step of preliminary purification. The small column (green data) is 1.6 cm diameter by 12 cm. The large column (black data) is 63 cm diameter by 12 cm.			

Buffers and other solutions should be made up and released by manufacturing. If it is not possible to obtain these, mix solutions with GMP-released raw materials, or material of an equivalent grade from an approved vendor. Follow exactly the solution recipes from manufacturing. The pH, temperature and conductivity probes that check buffer properties must be comparable with those used at the large scale. Measure pH and conductivity at the same temperature spelled out in the recipe. The pH and conductivity standards should also be comparable (preferably identical) to those used in manufacturing. 

 Our experience has been that an automated small-scale chromatography system, such as the äKTA Explorer, excels at small-scale studies. It offers precise, accurate and reproducible control of flow rates and gradients. However, you still have to check and calibrate the accuracy and precision of in-line detectors (pH, conductivity, temperature) by using off-line probes.  

The type of column is generally not a major issue; however, whenever possible use the same bed support material. We prefer to not use column diameters of less than 1.0 cm since the ratio of system dead volume to column volume can result in pool concentrations significantly lower than those seen at large scale. The packing procedures and solutions should be similar to those used at large scale.  

Controlling temperature at small scale to mimic that of cold rooms or cold-boxes can be a challenge. The use of water baths with column jacketing can provide precise temperature control, but the tubing leading up to the column can frequently act as a mini heat exchanger, making it difficult to control the actual inlet temperature. Using heat exchangers on the inlet tubing and column jacketing may be necessary for accurate, consistent and precise temperature control. 

Table 1 Comparison of scale-down model with a large-scale cation-exchange column. Input material roughly 98% antibody, 3 ppm DNA, 3000 ppm CHOP and  

Constraints associated with equipment can make scale-down a challenging exercise.