Pharmaceutical Validation: 2018-03-04

Saturday, March 10, 2018

Managing the Cost of Non-Compliance

Pixelagestudio/shutterstock.comThe main regulatory standard for ensuring pharmaceutical quality is 21 Code of Federal Regulations (CFR) Parts 210 and 211, collectively referred to as the current good manufacturing practice (CGMPs) regulation for human pharmaceuticals. It’s not only the CGMP regulations that matter; the approaches biopharmaceutical companies take to interpret and embrace these regulations are of equal, if not more, importance. CGMPs place emphasis on product quality and compliance with the regulations. So how do companies embrace, and even embody, quality and compliance with CGMPs? One way is to operate under a quality culture.

A company should have a pharmaceutical quality system as described in FDA Guidance for Industry, Q10 Pharmaceutical Quality System (1). A quality culture is created when managers believe a company has a duty to create a mutually beneficial relationship between itself, its employees, and its customers. Culture is the shared beliefs, values, attitudes, and behavior patterns that characterize a family, a community, or an organization. A healthy organizational culture is rooted in the understanding that quality is good for the company and its customers. Thus, its existence is a driving force behind how employees act and behave regardless of level, title, or decision-making authority. A quality culture begins with company leaders who believe in the necessity of serving customers in order for their organizations to succeed. In defining a set of desirable values for a corporate culture, some of the primary core values should include integrity, customer focus, and people.

FDA conducts several types of inspections to help protect consumers from unsafe products: pre-approval inspection, routine inspections of a registered facility, and “for-cause” inspections. After FDA completes an inspection, company management may receive an FDA Form 483 (2) when an investigator(s) has observed any conditions that, in their judgment, may constitute violations of the Food Drug and Cosmetic (FD&C) Act, related acts, and applicable sections of 21 CFR 210 and 211. Observations are made when, in the investigator’s judgment, conditions or practices observed would indicate that product has been adulterated or is being prepared, packed, or held under conditions whereby it may become adulterated or rendered injurious to health. FDA Form 483 notifies the company’s management of objectionable conditions. Companies respond to the 483 in writing with their corrective action plan and implement schedule. The 483 is closed when the company receives their establishment inspection report (EIR). Unfortunately, there are companies that either do not follow through on their commitments or they do so too slowly. If circumstances merit, FDA can choose to escalate the situation by serving the company with a warning letter.

Typically, FDA gives individuals and companies an opportunity to take voluntary and prompt corrective action before the agency initiates an enforcement action. A warning letter is FDA’s principal means of notifying regulated companies of violations and achieving prompt voluntary correction. The following factors are used to determine whether to issue a warning letter (3):

The firm’s compliance history (e.g., a history of serious violations, or repeated failure to prevent the recurrence of violations)
The nature of the violation (e.g., a violation that the firm was aware of [was evident or discovered] but failed to correct
The risk associated with the product and the impact of the violations on such risk
The overall adequacy of the firm’s corrective action and whether the corrective action addresses the specific violations, related violations, related products or facilities, and contains provisions for monitoring and review to ensure effectiveness and prevent recurrence
Whether documentation of the corrective action was provided to enable the agency to undertake an informed evaluation
Whether the timeframe for the corrective action is appropriate and whether actual progress has been made in accordance with the timeframe.

When a company repeatedly violates cGMP requirements, FDA can force it, through legal channels, to make specific changes. Under this severe form of escalation by FDA, the objective is no longer a discussion about responses to 483s or warning letter observations, it’s about a forced company make-over. This process, known as consent decree, exposes all broken systems within a company. FDA does not care about any efforts and expenses undertaken by the company to redesign and implement a robust quality management system; a common element of a consent decree is demonstrating sustainability.

Sustainability is the capability of an organization to know when it is veering off course and to make the correct decisions, take the appropriate actions, and maintain a state of control without external intervention. Sustainability embraces the core quality culture values and expected behaviors of integrity, empowerment, and accountability. A consent decree mandates a series of annual inspections performed by a third-party to monitor sustainability. FDA recommends companies hire external experts and invest time and money to inspect and certify compliance, often for many years.

Operating under a consent decree is a dire situation for the company and one where there is no certain predictability of the outcome. To understand the full magnitude of a consent decree’s impact, one needs to take into consideration the many and various modes in which the negative consequences can be realized (see Figure 1).

Figure 1: Overview of different repercussions to and reverberations from a pharma company operating under consent decree. (Figure courtesy of author)

The cost of non-compliance

This discussion focuses on three ways to look at the costs of non-compliance: quantifiable costs, difficult-to-quantify costs, and invisible costs with hidden impacts.

Quantifiable costs. Quantifiable costs are those that can have a value assigned to them with a reasonable degree of accuracy. Quantifiable costs are usually more obvious, but they manifest in several ways as shown in Figure 1.

Often termination and replacement of specified employees with retraining of remaining legacy employees is an immediate step associated with a consent decree. This company action is meant to set the tone that the old way of doing business will not be tolerated anymore. A major requisite term of a consent decree is for the company to retain, at its own expense, an independent third-party for ongoing certification and oversight of the implementation of agreed to corrective action. Another requirement may be a commitment to have every released batch certified to be CGMP.

FDA can levy significant fines for not meeting action dates: Examples include $15,000 per day for missed dates, royalty payments up to 24.6% (4) per product not revalidated on time, and costs for FDA inspections. Furthermore, the US Treasury can garnish profit from sales through fines. Such was the case for Wyeth in October 2000. Wyeth agreed to a consent decree regarding its Marietta, PA and Pearl River, NY. Inspections in 1995, 1996, and 1998 found several GMP deviations and resulted in warning letters (5).

In 2013, one of the largest drug safety settlements occurred when generic-drug manufacturer, Ranbaxy USA Inc., a subsidiary of Indian generic-pharmaceutical manufacturer Ranbaxy Laboratories Limited, pleaded guilty to felony charges relating to the manufacture and distribution of certain adulterated drugs made at two of Ranbaxy’s manufacturing facilities in India (3). Ranbaxy paid a criminal fine and forfeiture totaling $150 million and settled civil claims under the False Claims Act and related state laws for $350 million.

Entering into consent decree can also expose a company to civil penalties. Depending on the circumstances, shareholders, patients, and sometimes even company employees may be able to sue for damages. One such law suit arose from an unsuccessful effort by Baxter International to fix problems with its Colleague Infusion Pump. Westmoreland County Employee Retirement System (Westmoreland) alleged that Baxter’s directors and officers breached their fiduciary duties by “consciously disregarding their responsibility to bring Baxter into compliance with the 2006 consent decree and related health and safety laws” (6).

The breach was alleged to have caused Baxter to lose more than $550 million after FDA mandated a recall of the Colleague Infusion Pumps in 2010. Baxter invested time and money trying to fix the pumps, but the problems persisted into early 2010. FDA invoked its power under the 2006 consent decree by ordering Baxter to recall and destroy all Colleague Infusion Pumps then in use in the US, reimburse customers for the value of the recalled device, and to assist in finding replacement devices for those customers. The company’s stock price fell by more than 4% after the announcement and the company later recorded a pre-tax charge of $588 million to account for the estimated costs of the recall.

A company under consent decree loses future revenue in different ways. One way, which is particularly difficult to quantitate, is the price due to “lost innovation”. The company is redirecting revenue into compliance, oversight, and remediation instead of reinvesting it into research and development of new products.

When a drug manufacturer subject to enforcement action is the sole supplier of an important medicine, drug shortages become a concern. Short-term solutions may include doctors substituting medications that may have lesser efficacy. Pharmaceutical companies with potential manufacturing capability may be incentivized by FDA to manufacture identical or equivalent drug products; however, medium-to-long lead times can delay product availability. When supplies dwindle, patients must pay higher prices for the same drug.

One illustration of this scenario is the FDA consent decree with Genzyme in 2010 (7) regarding repeated manufacturing issues at the company’s Allston, MA facility, which included an up-front disgorgement of past profits of $175 million and the requirement to move fill/finish operations out of the Allston plant by a specific date. Had Genzyme not met those deadlines, FDA could have required the company to disgorge 18.5% of revenue for the affected products.

Difficult-to-quantify costs. Other financial ramifications from consent decrees may be difficult to quantify. For example, some employees may lose their confidence in the commitment or ability of the company’s CEO and other executives to manage the situation. Employee attrition is expected, but if the exodus includes long-tenured employees the company may be drained of valuable knowledge and talent. The longer the situation exists, the more difficult it becomes to retain the best employees.

A company under a consent decree is subject to reputation damage, which can be accentuated by the ease of publicly available negative media coverage about how the company operated. Negative media coverage can result in public fear. In the Ranbaxy case, an import ban had been in place since 2008 for 30 drugs manufactured at two of its Indian manufacturing plants resulting from alleged data falsification (7). This type of information can result in public concerns that medicines could be adulterated.

Lost revenue due to the company’s inability to sell product can also be an issue. Companies under consent decree experience long delays in releasing product due to the intensive oversight required, when a batch fails release testing, and when a product is recalled. The cost for the logistics of product recall and destruction can be high, especially if the API is expensive or has a long lead time.

Another potential cost is the inability to sell a product. Group purchasing organizations (GPOs) use the power of collective purchasing to buy pharmaceuticals at discounts (8). An underlying premise is continuity of supply; if a pharmaceutical manufacturer is unable to deliver the product contracted, the GPO must obtain replacement product from the open market, often at a higher price. GPOs wary of a potential inability of the company to supply its products may consider other sources.

In one of the largest settlements to date, Ranbaxy pled guilty to felony charges (9). The charges were manufacturing and distributing adulterated drugs made at the Indian manufacturing sites. The criminal fine and forfeiture totaled $150 million and another $350 million to settle civil claims under the False Claims Act.

Invisible costs and hidden impacts. If the cost to bring a facility under consent decree into CGMP compliance is determined to exceed the company’s financial ability or it makes no financial sense to continue operations, the company’s management may decide to close the facility. Shuttering a facility, can have devastating impact on the local community, particularly in rural areas where the manufacturer is a primary employer. The community’s tax base will also suffer.

The company can lose its competitive edge because its busy focusing inside rather than externally. This can be a competitive advantage to your closest competition looking for a way in which to leverage your situation for their benefit. The potential opens for the company to become alienated and therefore lose rank compared to its direct competitors.

A company can also be denied approval of new drug while non-compliance exists (4). Because of its consent decree, approval of two new drugs by Eli Lilly was delayed. This was the result of CGMP issues being found during pre-approval inspection in the fall of 2001, which was six years after its consent decree.

Conclusion

The collective cost of remediation of non-compliance far exceeds the cost to remain in compliance. The number of consent decrees issued per year has remained consistent during the past decade. However, companies have found it difficult to extricate themselves from the agreements. As a result, the number of companies under consent decrees at any given time has increased. Generally, it takes many years for a company to demonstrate that it is in full compliance. Only one company that has received a decree in the past 10 years has met all requirements and had the decree lifted.

Considering the fines and the payments to the third-party consultants, the costs associated with a consent decree can become very high and have a significant effect on a company’s profit. It is estimated that the costs incurred by Warner-Lambert from 1993 to 2002 for a 1993 consent decree–in terms of product terminations, delays in approvals, and bringing facilities and systems into compliance–was nearly $1 billion (4). The Warner Lambert fine was only $10 million, a small percentage of the total cost. Schering-Plough’s initial fine was $500 million. Abbott Laboratories has spent almost $1 billion resulting from a consent decree issued in 1999, including a fine of approximately $100 million.

References

1. FDA, Q10 Pharmaceutical Quality System, Guidance for Industry (ICH, April 2009).
2. FDA, FDA Form 483 Frequently Asked Questions.
3. FDA, Warning Letter Procedures, accessed Sept. 29, 2017.
4. S. Chrai and M. Burd, BioPharm International 17 (6) (June 2004).
5. Wyeth, “Wyeth-Ayerst Labs Enters into Consent Decree with FDA,” Press Release, Oct. 2, 2000.
6. R. Kreisman, “Shareholder’s Right to Sue for Breach of Fiduciary Duty by Baxter International Directors and Officers Allowed,” Kreisman Law Offices, Chicago Injury Lawyer Blog, September 24, 2013.
7. Sanofi Genzyme, “Genzyme Announces Final Terms of FDA Consent Decree,” Press Release, May 24, 2010.
8. AmerisourceBergen “The Evolution of GPO Contracting,” Knowledgedriven.com, Nov 25, 2014, accessed Sept. 29, 2017.
9. US Department of Justice, “Generic Drug Manufacturer Ranbaxy Pleads Guilty and Agrees to Pay $500 Million to Resolve False Claims Allegations, CGMP Violations and False Statements to the FDA,” Press Release, May 13, 2013.

Article Details

Pharmaceutical Technology
Vol. 41, No. 11
November 2017
Pages: 54–57

Citation

When referring to this article, please cite it as S. Ayd, “Managing the Cost of Non-Compliance,” Pharmaceutical Technology 41 (11) 2017.

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Analytical Method Development and Optimization

Regulatory guidance documents are written by committees, resulting in statements that are both exact and generic. Meeting regulatory requirements involves not only interpreting these documents correctly but also addressing their omissions. This article provides practical guidance on issues that are not thoroughly covered by current guidance documents regarding validation of analytical methods for biopharmaceuticals.

Table 1. Validation characteristics per ICH Q2(R1) and relevant product specifications

Four of the existing regulatory guidance documents on methods validation state, “Methods validation is the process of demonstrating that analytical procedures are suitable for their intended use.”^1–4 We have all read, and likely used, this phrase many times when summarizing method-validation results. According to Muire-Sluis, development scientists often point out that “validated methods may not be valid.”⁵ The question therefore arises, what exactly makes a validated method valid? According to the Center for Biological Evaluation and Research (CBER), “the acceptability of analytical data corresponds directly to the criteria used to validate the method.”⁴

We can generate evidence for the validity of analytical data in the formal method-validation program where all critical parameters are extensively tested under a detailed protocol that includes scientifically justified and logical step-by-step experimental approaches. All planned data sets must fall within pre-established protocol acceptance criteria limits. These criteria should be derived from and justified in relation to historical data and product specifications. Once evidence for all critical elements is provided, the validated method will become the official, licensed procedure for that particular product and process step, and it will then support production and product release. The relationship between “valid” or “suitable and validated” is often overlooked, but there is a high price when “validated” test systems are simply inappropriate.

Incentives to replace existing licensed test procedures may come from regulatory agencies, or they could be motivated by potential cost savings, ease of use (automation), and the opportunity to generate more accurate and reliable results.

The International Conference on Harmonization (ICH)’s Q2(R1),¹ should be used for basic guidance. However, following just these guidelines will not necessarily produce a “valid” method and may not provide sufficient evidence that this method is suitable for product release. The intent of USP 30 <1225> is to provide guidance only on validation requirements for test methods for inclusion into USP with the expectation that validated USP methods still require verification from users.^6–7 The US Food and Drug Administration (FDA) and European Medicines Agency (EMEA) provide guidance on some of the scientific issues that are not covered by Q2(R1).

Process Map. A process map showing the recommended steps for the selection, development, validation, and potential transfer of analytical methods, illustrating all proposed functional responsibilities was developed. Frequently, larger companies have separate functional units for method development, validation, and testing. The process flow in Figure 1 describes an ideal sequence of steps for better analytical method validation (AMV).

Figure 1

The rigorous standards suggested here are ideal but they are not necessarily required or followed during method development. Methods can be developed without strict adherence to good manufacturing practices (GMP) regulations if adequate documentation systems are used.

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Ultrahigh-Pressure Liquid Chromatography, Part III: Potential Issues

This installment on ultrahigh-pressure liquid chromatography (UHPLC) reviews the potential problems that may be encountered using UHPLC systems and methods, and proposes strategies for their mitigation.

The use of low-dispersion ultrahigh-pressure liquid chromatography (UHPLC) instruments under high operating pressures can present potential issues to the users, particularly for analyses in a regulatory environment. This final entry in the three-part series on UHPLC describes these problems and the strategies for their mitigation.

The potential issues are placed into six groups and are described below:

Safety issues
Viscous heating
System and operating nuances (equipment cost and system compatibility with existing high performance liquid chromatography [HPLC] methods)
Injection precision
Ultraviolet (UV) detection sensitivity
Method translation (conversion)

Note that issues such as injection imprecision and UV baseline perturbation that had been reported in early-generation UHPLC equipment (1,2) are less likely to be seen with newer UHPLC systems. Finally, guidelines for purchasing UHPLC instruments and options for the desired applications are described.

Safety Issues

Operating at pressures exceeding 10,000 psi may sound risky to some operators. Potential safety concerns for operation of UHPLC systems were addressed in a study by Lee and colleagues (3). The conclusion was that analytical-scale UHPLC poses little inherent danger to users under normal operation because of low flow rates (<1 mL/min) and the low compressibility of liquids.

Viscous Heating

Viscous heating by friction within the UHPLC column has been a popular research topic and has resulted in numerous published papers (3–7). The generation of heat within the column packed with small particles and its dissipation are complex phenomena, dependent on factors such as viscosity, thermal conductivity and flow rate of the mobile phase, particle size, length and inner diameter of the column, and the type of column oven used. Viscous heating can cause two types of thermal gradients within the column—a radial thermal gradient and a longitudinal thermal gradient. Let’s look closer at those two gradients.

Radial Thermal Gradient

A radial thermal gradient is caused by the center of the column having higher temperatures, since the generated heat dissipates mostly by thermal conduction at the column wall. Radial gradients cause extra band dispersion and a more pronounced parabolic flow profile. Viscous heating is deleterious to column efficiency, particularly for columns with larger internal diameters (for example, 4.6 mm) (4,8). Early UHPLC columns were only packed in small internal diameter formats (such as ≤ 2.1 mm) to minimize this effect (9). Subsequent studies indicated that the adverse effects of radial thermal gradients may not be of practical concern in still-air ovens because of poor heat dissipation from the stainless steel column wall (5,10). However, it can be significant in an isothermal environment (for example, a constant temperature water bath) or in a forced-air column oven (10,11).

Longitudinal Thermal Gradient

The heat generated inside the column is cumulative along the length of the UHPLC column, giving rise to a longitudinal thermal gradient. According to a study by Gritti and Guiochon (6), the temperatures at the respective column outlets can be 10 to 20 °C higher than those at the column inlets. Therefore, the average column temperature can be substantially higher than the set-point temperature, especially when high operating pressures are reached (for example, 1000 bar; summary data shown in Figure 1). Although a longitudinal thermal gradient does not have an effect on column efficiency, there may be potential method transfer issues for chromatographic critical pairs, whose selectivity is temperature dependent, as shown by Guillarme and colleagues (5,12). This issue can be partially mitigated by deliberately setting the UHPLC methods to lower column temperature values (such as 5 °C).

Figure 1: The experimental procedure and summary data from studies on the effect of longitudinal heating effects of UHPLC columns packed with 1.7-µm particles operating at 10,000 psi. Diagram reprinted with permission from reference 6. Copyright 2008 American Chemical Society.

For fast gradient analysis, it may take up to five injections to achieve thermal equilibration because of viscosity changes in the mobile phase during gradient analyses (13). For most UHPLC applications, it is important to acknowledge the existence of viscous heating. However, viscous heating may not be a serious issue, with the following exceptions: columns packed with very small particles (<2 µm) operating at high pressures (>1000 bar) with samples having critical pairs sensitive to temperature selectivity effects.

Operating Nuances and Backward Compatibility to Existing HPLC Methods

Although UHPLC has improved method performance (speed, resolution, precision, and efficiency) (9,10,14), many new users of UHPLC who are accustomed to HPLC operation are likely to experience some unexpected surprises and operating nuances. First, there could be a substantial cost premium of 10–50% compared to conventional HPLC equipment. Second, the use of smaller internal diameter columns packed with sub-2-µm particles using a low-dispersion instrument will require a better understanding of fundamental concepts, such as column void volume, peak volume, dwell volume, instrumental dispersion, and peak capacity—particularly during method development, method conversion, and troubleshooting (9,15). Some operational and fundamental training would be helpful for laboratory staff to ease the transition to UHPLC systems. Installing UHPLC column fittings correctly to minimize dead volume is also particularly important. A few manufacturers offer products to ensure tight column connections, such as the Agilent A-Line Quick Connect, Thermo Viper, and IDEX MarvelX fittings.

There may be issues regarding the compatibility of UHPLC systems in running conventional HPLC methods. These issues include limitations in flow rate (for example, <2 mL/min), injector sample loop size (<20 µL), and the column capacity of the column oven (<150 mm column length). Newer UHPLC equipment appears to be more backward compatible (for example, some new UHPLC column ovens introduced in 2016 are now able to accommodate columns up to 30-cm long). Most incompatibility issues can be readily resolved by installing optional accessories (that is, a larger sampling loop or syringe).

Historically, other issues of significant concern were column lifetime performance and the limited number of bonded phases available for UHPLC columns packed with sub-2-µm particles. Small-particle columns with smaller frit sizes are easily plugged from particulates (from both the mobile phase and the sample); therefore, higher levels of “chromatographic hygiene” and sample cleanup should be practiced (11). The availability of UHPLC columns was an initial limitation (only C18 and C8 bonded phases with column internal diameters ≤ 2.1 mm were available) during the debut of the first commercial UHPLC system in 2004. Since then, many UHPLC columns packed with sub-2-µm and sub-3-µm particles (both totally porous and superficially porous) have been introduced, including phases for different LC modes (ion exchange, chiral, hydrophilic interaction, and size exclusion) for the separation of both small molecules and biomolecules. Presently, both column lifetimes and the availability of columns and phases no longer appear to be issues of concern.

One trend, necessitated by the more sophisticated engineering of the UHPLC pumps and autosamplers, is in servicing key maintenance parts. As an example, the servicing of pump seals is now often handled by replacing the entire pump head with factory-refurbished parts rather than just replacing the pump seals on site by users or service personnel.

Injector Precision

Marginally acceptable peak area precision from early UHPLC X-Y-Z type autosamplers under partial-loop injection mode were reported (16,17). However, with continued improvements to UHPLC technology and the increased use of integrated-loop autosamplers, the precision of peak areas has improved significantly, even for small injection volumes (for example, <0.1–0.2% relative standard deviation [RSD] down to ~1 µL). An example of peak area and retention time precision data with different injection volumes is shown in Table I. These data demonstrate the excellent precision of <0.1% RSD at injection volumes of 10–20 µL, ~0.2% RSD at injection volume 1–5 µL, and ~0.5% RSD down to 0.2–0.5 µL. It should be noted that excellent peak area and retention time precision (<0.1% RSD) under high-resolution gradient analysis conditions at pressures of >12,000 psi have also been reported (18).

These data show that compliance with the United States Pharmacopeia (USP) precision requirements for chromatographic methods (see USP <621>) can easily be achieved.

UV Detector Sensitivity Issue from Pump Blending

The reduction of system dwell volumes is critical for high-throughput screening applications, and is usually achieved using high-pressure mixing binary pumps (1,10,14). However, if sufficient blending efficiency is not achieved, the low dwell volume may be problematic for high-sensitivity UV detection (1). For example, Figure 2 shows a UHPLC chromatogram of an analgesic drug product extract obtained using an early UHPLC system equipped with a binary pump and an external 100-µL mixer. The mobile phase of 11% acetonitrile in 0.1% acetic acid in water was pump-blended and the UV detector was set at 227 nm. Note that a periodic baseline perturbation is clearly visible. This perturbation was attributed to inadequate blending of mobile phase, considering that 0.1% acetic acid in water has significant absorbance at low UV wavelengths. The baseline perturbation, synchronous with piston strokes of pump B, can be eliminated by using premixed mobile phases or by adding larger mixing volumes to the system (for example, by using a 425-µL mixer) (1).

Figure 2: HPLC chromatogram illustrating the potential issue of UV baseline perturbation from insufficient blending efficiency from a binary UHPLC pump. Column: 50 mm x 3.0 mm, 3.5-µm d_p XBridge C18; mobile-phase A: 0.1% acetic acid in water; mobile-phase B: acetonitrile; flow rate: 1.5 mL/min; temperature: 30 °C; pressure: 2700 psi; detection: 227 nm, 20 pt/s; sample: 1 µL of an analgesic tablet extract (Excedrin). This issue was resolved by replacing the standard 100-µL mixer with a peptide mapping mixer of 425 µL. See reference 1 for more details.

The severity of this UV baseline problem is a function of pump design, the piston (stroke) volume, the mixer volume, and the relative UV absorbance of the two solvents. This potential issue can be minimized using larger-volume mixers (which will increase dwell volumes) or by selecting pumps with micropistons, variable stroke volume capability, or a dual-piston in parallel pump design (10). Note that quaternary pumps have inherently larger dwell volumes (0.4–0.8 mL) and may not need external mixers (10). Readers are encouraged to consult with instrument manufacturers regarding the selection of appropriate mixers for high-sensitivity applications using UV detectors without adding excessive dwell volumes.

Method Translation: Conversion from HPLC to UHPLC Methods and Vice Versa

The pharmaceutical industry prefers “portable” HPLC methods that are usable by most laboratories to facilitate global manufacturing. Since UHPLC systems are not yet standard equipment in most laboratories, many newly developed UHPLC methods for regulatory assays are “converted” back to HPLC methods, using longer 3-µm or sub-3-µm columns. Theoretically, this conversion should be straightforward, by using geometric scaling of flow rates, gradient time (t _G), and injection volumes, while keeping the same length to particle size (d _p) ratio (19). In practice, fine-tuning the HPLC method is often needed for the International Conference on Harmonization (ICH)-compliant stability-indicating methods (1,2).

This process of method translation is often referred to as “method transfer” in the literature. This reference may be technically incorrect, because method transfer is the formal process of demonstrating that a validated analytical method developed in an originating laboratory can be properly executed by another laboratory operating in a good manufacturing practice (GMP) environment. The method transfer process is executed as directed in a written protocol, with pre-established acceptance criteria to ensure that accurate data can routinely be generated in the new laboratory (11,15). On the other hand, method translation is the process of method conversion between HPLC and UHPLC conditions to produce equivalent separations.

There are three scenarios for method translation between HPLC and UHPLC (11):

Same HPLC methods implemented on different types of equipment (HPLC versus UHPLC)
Newly developed UHPLC methods “back translated” to HPLC method conditions
Existing HPLC methods translated to UHPLC methods for faster analysis

Running the Same HPLC Method on HPLC and UHPLC Systems

For laboratories with both HPLC and UHPLC equipment, it would be ideal if equivalent results could be obtained on both types of equipment. As shown in Figure 3, when executing an HPLC method using an identical column and mobile phase, results can be equivalent with the exception of retention time shifts because of the smaller dwell volumes (V _D) of UHPLC systems (~0.1–0.7 mL by UHPLC versus ~1.0 mL by conventional HPLC) (15). In general, the earlier retention times by UHPLC will not impact resolution and, if needed, can be remedied by several means (11):

Increasing the dwell volume of the UHPLC system, by using a larger external mixer
Building an initial isocratic segment into the HPLC method and allowing the user to adjust the duration of this segment in the method (preferred)
Using simulation software available on some chromatography data systems to simulate the performance of different instrument models by automatic method adjustments (21), or by purchasing a dual-path system that converts a UHPLC system into an HPLC system with a switching valve to select a larger flow path (21)

Note that detection sensitivity is generally not impacted when similar UV detectors and flow cells are used except for early eluted peaks where UHPLC systems often yield a slightly higher signal because of lower system dispersion.

Figure 3: Comparative HPLC chromatograms of the retention marker solution of a stability-indicating method for a multichiral drug substance on (a) HPLC (Agilent 1200 quaternary system) and (b) UHPLC systems (Agilent 1290 binary system) under identical column and mobile-phase conditions. Column: ACE C18, (3 µm, 150 mm x 4.6 mm); mobile-phase A: 20 mM ammonium formate at pH 3.7; mobile-phase B: acetonitrile with 0.05% formic acid; gradient: 5–15% B in 5 min, 15–40% B in 25 min, 40–90% B in 3 min; flow rate: 1.0 mL/min at 300 °C and 200 bar; detection: UV at 280 nm, 40 pt/s; sample: 10 µL of a 0.5-mg/mL solution of an active pharmaceutical ingredient (API) spiked with expected impurities. Note that UV detector baseline noise is comparable at ~0.02 mAU while the retention time shifted earlier by 0.8 to 1.4 min on the UHPLC system because of the smaller dwell volume (0.28 mL versus 1 mL on the HPLC system). Structure of the multichiral API is shown in the inset. Chromatograms reproduced with permission from reference 11.

Back-Conversion of UHPLC Methods to HPLC Method Conditions

Many laboratories use UHPLC for rapid method development including column and mobile-phase screening and method optimization (19). The optimized UHPLC methods are “back translated” to HPLC conditions using longer columns via geometric scaling. Only the back-converted HPLC method needs to be validated and serves as the primary regulatory method to support global manufacturing operations while the faster UHPLC method can be used to support any non-GMP process development projects. Case studies for such method conversion processes have been previously reported (1).

Conversion of Existing HPLC Methods to Faster UHPLC Methods

The primary driver for purchasing UHPLC equipment is the ability to perform faster analysis with “good” resolution (20). To duplicate the separation with similar column efficiency and selectivity, this can be accomplished by geometric scaling using the following ground rules:

Column length (L) is scaled to particle size (d_p keeping the L/d_p ratios the same. The bonded phase chemistry must be identical. For example, Acquity (1.7 µm, 50 mm x 2.1 mm)–XBridge (3.5 µm, 100 mm x 3.0 mm)
Flow rate (F) is scaled to the cross-sectional area of the column. For example, 2.1 mm i.d. (0.5 mL/min), 3.0 mm i.d. (1 mL/min), 4.6 mm i.d. (2 mL/min)
Gradient time (t_G is scaled to column length at a geometrically identical flow rate
Sample injection volume is scaled to column void volume. For example, 2 µL (1.7 µm, 50 mm x 2.1 mm) to 10 µL (3.5 µm, 100 mm x 3.0 mm)

One requirement is that both HPLC and UHPLC columns must contain the identical bonded phase materials, to eliminate any selectivity differences. Also, the mobile phases used should be identical (type of buffer, strength, pH, organic modifier, and so forth). An example of this method conversion is shown in Figure 1 of the second installment of this series (18). Calculator programs for method translation are available at various vendors’ websites (Waters, Agilent, and Thermo) and other sources (11).

In practice, the ground rules of geometric scaling may not be strictly followed if equivalent or better resolution can be achieved with UHPLC columns. Figure 4 shows a case study for the conversion of a 42-min regulatory HPLC method of a multichiral drug to UHPLC methods of equal or higher resolution. Here, geometric scaling was not followed since the flow rate of 1 mL/min of the original HPLC method is not optimum to begin with. The faster 17-min method with equivalent resolution was used to support Phase 2 drug product development (18).

Figure 4: Comparative chromatograms of a retention marker solution containing an API (0.5 mg/mL) and spiked impurities analyzed using identical mobile phases on an Agilent 1290 binary UHPLC system by various methods: (a) Regulatory HPLC, (b) fast HPLC, (c) UHPLC. Run time, operating pressure, column, plate count, and resolution values of the diastereomers are shown in the figure. HPLC conditions: (a) regulatory HPLC method: same as in Figure 3. (b) Fast HPLC method: column: ACE C18, (2 µm, 100 mm x 3.0 mm); flow rate: 0.8 mL/min at 40 °C; gradient: 5–15% B in 2 min, 15–40% B in 10 min, 40-90% B in 1 min, 90% B in 2 min, 90–5% B in 0.1 min; injection volume = 3 µL. (c) UHPLC method: column: ACE C18, (2 µm, 150 mm x 3.0 mm); flow rate: 0.8 mL/min at 40 °C; gradient: 5-15% B in 2 min, 15–40% B in 18 min, 40–90% B in 3 min, 90% B in 2 min, 90–5% B in 0.1 min; injection volume = 5 µL. Structure of the multichiral API is shown in the inset. Chromatograms reproduced with permission from reference 18.

Most of the reported method translation case studies have been for reversed-phase separations for small-molecule drugs, for which the retention mechanism is highly predictable and substantial cumulative manufacturing experience with small-particle bonded phases is available. Successes with method translation case studies in other chromatographic modes such as size exclusion, normal-phase chiral, ion exchange, and hydrophilic interaction are reported less often and perhaps they are less predictable.

Method Validation Requirements After Method Translation

For validated HPLC methods, there has been a lot of discussion and considerable confusion regarding what constitutes a method adjustment versus a method change and whether revalidation of the converted UHPLC method is needed (26). The current consensus, including viewpoints from a United States Food and Drug Administration (FDA) reviewer, is that a partial method validation (including specificity, intermediate precision, linearity, and robustness) is needed. The validation should include supporting data on method equivalency between the original and the converted methods. For USP methods, the Chromatograph Chapter <621> in USP 37-NF32 (including supplement 1) of 2014 offers guidelines on permissible method adjustments to pass system suitability testing. In general, injection volume, column temperature (±10%), and mobile-phase pH (±10%) can be adjusted without revalidation. For isocratic methods, wide adjustment ranges of column particle size, column length, flow rate, and column internal diameter are allowed. In contrast, no such changes are allowed for gradient methods.

How to Transition from HPLC to UHPLC: Instrumental Considerations

This final section discusses how to get started in UHPLC by selecting the appropriate UHPLC instrument vendor and model. The decision may be a complex one, since there are many UHPLC models available from numerous manufacturers with diverse features, pricing, and control software (22–25,27). Table II lists UHPLC systems from several major manufacturers with their associated data and mass spectrometry (MS) systems as well as the maximum flow rate and pressure limit.

The purchase decision should be driven by the intended application—whether it is for method development, routine testing, research, quality control, high-throughput screening, or LC–MS analysis—and should be dictated by the most appropriate features available in a specific vendor or model. The second consideration should be whether the instrument is compatible with your existing chromatography data system (CDS) (likely a client-server CDS in most laboratories). With respect to CDS compatibility, the best UHPLC system is often the one supplied by the same CDS manufacturer. This is particularly important for UHPLC–MS systems, in which HPLC control is embedded in the MS data system. For laboratories wishing to run existing HPLC methods, specific vendors may offer UHPLC systems with better backward compatibility.

After selecting the manufacturer, the next consideration is the choice of the specific model and the optional accessories. Pricing is highly variable for UHPLC systems (>15,000 psi) and lower-cost intermediate-pressure HPLC systems or dual-path systems (~10,000 psi) (22–25). The cost for binary pumps is usually higher than for quaternary pumps. Biocompatible titanium-based systems are preferred for bioanalysis of proteins, which typically requires high-salt mobile phases. Quaternary pumps, with built-in switching valves and column ovens, are typical with method development systems. For binary systems used for high-sensitivity purity assays (including peptide mapping), larger external mixers should be selected.

In this mature UHPLC market, most manufacturers offer reliable and competitive products, whose actual specifications (for example, upper pressure limits, autosampler precision, and system dispersion) may have little practical significance in daily operation.

Conclusions

The final entry of this three-part series on UHPLC provided an overview of the potential issues and concerns of running UHPLC methods and the means for their mitigation. Purchasing considerations for UHPLC systems were also discussed.

Acknowledgments

The authors would like to thank Tom Waeghe of MAC-MOD Analytical, Wilhad Reuter of PerkinElmer, Raphael Ornaf (retired), Hernan Fuentes of Ardelyx, Terence Lo from Gilead Sciences, Matt Mullaney of Pentec Health, and Davy Guillarme of the University of Geneva for their technical and editorial inputs.

References

(1) M.W. Dong, LCGC North Am. 25(7), 656–666, (2007).

(2) M.W. Dong, in Chromatography: A Science of Discovery, R.L. Wixom and C.L. Gehrke, Eds. (Wiley, Hoboken, New Jersey, 2010), pp. 328–333.

(3) Y. Xiang, D. Maynes, and M.L. Lee, J. Chromatogr. A 991, 189–196 (2003).

(4) N. Wu and A.M. Clausen, J. Sep. Sci. 30, 1167–1187 (2007).

(5) L. Nováková, J-L. Veuthey, and D. Guillarme, J. Chromatogr. A 1218, 7971–7981 (2011).

(6) F. Gritti and G. Guiochon, Anal. Chem . 80, 5009–5020 (2008).

(7) A. de. Villers, F. Lestremau R. Szucs, S. Gelebart, F. David, and P. Sandra, J. Chromatogr. A 1127(1–2), 60–69 (2006).

(8) D. Cabooter and G. Desmet, in UHPLC in Life Sciences, D. Guillarme, J.-L. Veuthey, and R. M Smith, Eds. (Royal Soc. Chem. Publishing, Cambridge, United Kingdom, 2012), Chapter 1.

(9) U.D. Neue, M. Kele, B. Bunner, A. Kromidas, T. Dourdeville, J.R. Mazzeo, E.S. Grumbach, S. Serpa, T.E. Wheat, P. Hong, and M. Gilar, in Advances in Chromatogr. 48 (CRC Press, Boca Raton, Florida, 2009), pp. 99–143.

(10) J. De Vos, K. Broeckhoven, and E. Eeltin, Anal. Chem. 88, 262–278, (2016).

(11) M.W. Dong, LCGC North Am. 31(10), 868–880, (2013).

(12) B. Debrus, E. Rozet, P. Hubert, J-L Veuthey, S. Rudaz, and D Guillarme, in UHPLC in Life Sciences, D. Guillarme and J-L Veuthey, Eds. (Royal Soc. Chem. Publishing, Cambridge, United Kingdom, 2012), pp. 67–98.

(13) M. Dittmann, K. Choikhet, P. Stemer, and K. Witt, “Method Transfer between HPLC and UHPLC: Issues and Solutions,” presented at Pittcon 2011, Chicago, Illinois, 2011.

(14) M.W. Dong, LCGC North Am. 35(6), 374–381 (2017).

(15) M.W. Dong, Modern HPLC for Practicing Scientists (Wiley, Hoboken, New Jersey, 2006), chapters 2–4, 6, 9.

(16) S.A. Wren and P. Tchelitcheff, J. Chromatogr A. 1119(1–2), 140–146 (2006).

(17) L. Nováková, L. Matysová, and P. Solich, Talanta 68(3), 908–918 (2006).

(18) M. Dong, D. Guillarme, S. Fekete, R. Rangelova, J. Richards, D. Prudhomme, and N. Chetwyn, LCGC North Am. 32(11), 868–76, (2014).

(19) M.W. Dong and K. Zhang, Trends in Anal. Chem. 63, 21-30, 2014.

(20) M.W. Dong, LCGC North Am. 35(8), 486–495 (2017).

(21) Agilent 1290 Infinity LC with Intelligent System Emulation Technology, Agilent Technologies, 20135990-8670EN, 2013.

(22) M.W. Dong, LCGC North Am. 34(4), 262–273 (2016).

(23) M.W. Dong, LCGC North Am. 33(4), 254–261 (2015).

(24) M.W. Dong, LCGC North Am. 32(4), 270–279 (2014).

(25) M.W. Dong, LCGC North Am. 31(4), 313–325 (2013).

(26) M. Swartz and I. Krull, LCGC North Am. 24(8), 480–490 (2006).

(27) “UHPLC: Where We are Ten Years After Its Commercial Introduction,” D. Guillarme and M.W. Dong, Eds., Trends in Anal. Chem. 63, 1–188, (2014) (a special issue).

ABOUT THE COLUMN EDITOR

Michael W. Dong Michael W. Dong , is a principal of MWD Consulting, which provides training and consulting services in HPLC and UHPLC, pharmaceutical analysis, and drug quality. He was formerly a Senior Scientist at Genentech, Research Fellow at Purdue Pharma, and Senior Staff Scientist at Applied Biosystems/PerkinElmer. He holds a PhD in Analytical Chemistry from City University of New York. He has more than 100 publications and a best-selling book in chromatography. He is an editorial advisory board member of LCGC North America. Direct correspondence to: [email protected]

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Scaling Down of Biopharmaceutical Unit Operations — Part 1: Fermentation

The fermentation process can be challenging to scale down and several factors must be evaluated for each step.

Mar 01, 2005

BioPharm International

Volume 18, Issue 3

Anurag Rathore

Creation and qualification of scale-down models are essential for performing several critical activities that support process validation and commercial manufacturing. As shown in Figure 1, these activities include process characterization and production support studies that are performed to evaluate column and membrane lifetimes, demonstrate clearance of host-cell impurities and viruses, and troubleshoot manufacturing issues. While the underlying fundamentals are relatively the same as those when scaling up, some unique considerations should be taken when scaling unit operations down.^1-4 The goal when scaling down is to create a small-scale or lab-scale system that mimics the performance of its large-scale (pilot or manufacturing) counterpart, when both the process parameters are varied within their operating ranges and also when a process parameter deviates outside its operating range. Before it can be used for lab studies, the scale-down model needs to be qualified and its equivalence to large-scale examined. Data from an inaccurate scale-down model could result in conclusions that may not be applicable to large-scale, resulting in an unsuccessful process-validation campaign or continued lot failures in a manufacturing campaign.

This article is divided into two segments. The first part focuses on an upstream unit operation — fermentation. The next segment will cover two downstream unit operations — chromatography and filtration. The combined article is the fifth in the “Elements of Biopharmaceutical Production” series.

Figure 1. Scale-down Models are Best Utilized for Process Characterization and Production Support

HARDWARE SCALE-DOWN GUIDELINES
Fermentation processes often involve several scales of operation, encompassing inoculum development, seed expansion, and production fermentation. The differences in volumes between the steps in a single fermentation process can be 10X to 100X for the pilot scale, and 1,000 to 100,000X for the production scale. This may cause the fermentation processes to be challenging to scale down and the specific process parameters, vessel geometries, and operational control strategies must be evaluated for each step. Some general guidelines to consider in developing a representative scale-down model follow.

Practitioners use the terms “similar reactor” or “similar vessel geometries” to describe optimal conditions for a scale-down strategy. However, similarity in vessel geometry does not necessarily imply identical systems, although this would be the most attractive option. Instead, geometric similarity means that the overall aspect ratios of each vessel (small vs. large) are close enough to not impact performance. More importantly, the impeller and sparger designs and placements within the vessel are nearly identical.

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Technology Improvements Drive Capacity Gains for Biologics Fill/Finish

Until recently, the handling of sterile liquids in the pharmaceutical industry has relied on decades-old techniques and technologies. During the past 10 years, however, biologics have taken a prominent role in the drug-development pipeline. The value of these drugs, sometimes measured in tens of thousands of dollars per dose, has put greater pressure on biologics downstream fill and finish operations. The increased scrutiny from regulators and the greater product value have initiated industry improvements so that quality, safety, and cost-efficiency remain high at this crucial late stage in manufacturing.

BioPlan recently prepared a white paper identifying trends among in-house fill and finish operations for recombinant therapeutics (1). This research excluded outsourced operations and CMOs. BioPlan found significant differences between industry capacity and capacity use for these large-molecule facilities, compared with the constraints currently being experienced in small-molecule fill and finish, which have in some cases even led to drug shortages at the hospital level.

In biologics in-house operations, BioPlan found trends that include the increased use of isolator technologies, more high-speed operations, and other innovative approaches. Findings regarding capacity use indicate that in-house manufacturers, on average, continue to have additional available fill-and-finish vialing, pre-filled device, and lyophilization capacity:

Utilization averaged 55% for lyophilization
58% for pre-filled devices
70% for vialing.

At present, there is sufficient capacity, even without adding shifts or additional equipment. This finding is in contrast to the situation with small molecules, where some facilities are working at near-capacity, and facility consolidation, regulatory actions, closures, and the use of less efficient legacy equipment have created bottlenecks and even serious drug shortages at the hospital level.

The state of in-house fill/finish capacity
BioPlan’s in-house biologics fill/finish market analysis evaluated the capacity for recombinant biologics and compiled information from 89 candidate facilities in the US and Europe. More than 50 industry participants were surveyed at facilities, equipment suppliers, and consulting groups.

Regarding vialing, capacity utilization averaged 70%; this figure represents the average for biopharmaceutical in-house manufacturers, which generally produce at most a few products at each facility. While this indicates that a relatively large flex or expansion vialing capacity may be available among current primary manufacturers, in-house facilities are not designed for, nor are they capable of, running at maximum capacity, due to down-time, maintenance, and cleaning/validation.

For pre-filled devices and syringes (PFS), an even greater amount of flex capacity was found. Pre-filled syringe and cartridges fill-finish capacity averaged 6.75 million per shift; the average PFS fill/finish capacity utilization was 55%, suggesting considerable expansion capacity potential among those facilities doing in-house PFS fill-finish.

Finally, with regards to lyophilization capacity, which averaged 760 square feet among those facilities with these data available, utilization averaged 58%, again indicating room for expanding manufacturing output.

Overall, the largest scale manufacturing operations tend to be concentrated among just a few companies, with this the case for in-house fill/finish. Most of those largest-capacity facilities are based in Europe.

Activities outsourced by biomanufacturers
Although BioPlan’s white paper analysis focused on in-house fill-finish capacity, other BioPlan research found that eight in 10 biopharmaceutical manufacturers worldwide outsource at least some fill/finish operations today, up from 6 in 10 in 2010 (2). In fact, fill/finish operations are one of the most commonly outsourced activities, behind only toxicity testing (86.8% outsourcing to some degree) and analytical testing of other bioassays (89% outsourcing).

The results of BioPlan’s annual report also show that, in volume terms, fill/finish operations are one of the most heavily outsourced activities: Respondents estimated outsourcing (on average) 37.9% of the fill/finish operations at their facilities, ahead of areas like toxicity testing (35.4%) and validation services (19.9%) (see Figure 1).

Figure 1: Top five activities outsourced to some degree by biomanufacturers.

Available in-house capacity implications
The excess capacity available to in-house manufacturers of biologics may allow expansion of in-house fill/finish operations without adding shifts or equipment. Capacity, however, is commonly misrepresented as being related to machine speed or lyophilizer chamber capacity in vials. In-house fill/finish operators also note that equipment turnaround time, cleaning, and sterilization (in situ and ex situ) also need to be considered when calculating efficiencies. In this analysis, capacity utilization was defined as the “typical estimated usage of fill/finish capacity per shift”/“maximum capacity per shift”, using current number of shifts, and production equipment. As noted, a facility could significantly increase capacity by adding shifts, if needed.

Future trends
The fill/finish industry will likely depend on ramp-up of technologies and capabilities both in-house and at CMOs. Future trends will include:

Fill and finish CMOs are becoming larger, through mergers and acquisitions.
CMOs will continue to install state-of-the-art fill/finish equipment, mostly to support clinical manufacturing. Biopharmaceutical CMOs will do less sub-contracting of their fill and finish to specialized CMOs.
Fill-Finish CMOs in India and rapidly developing countries are handling increasing amounts of biopharmaceutical products, mostly for domestic and lesser-regulated international commerce.

Conclusion
In-house biologics fill/finish operations are unique from contract manufacturers’ business strategies. In addition, comparing small molecule in-house vs large molecule/recombinant biologics leads to significantly different conclusions. The lower capacity use rates for biologics can be partly explained by the more recent installation of higher technology equipment, RABS/isolators, and automation. The effect of end-product value is likely also a factor.

Newer technology adoption will impact utilization rates at both in-house and outsourced service providers (CMOs) as legacy equipment is replaced; however, this area requires further research. Fill/finish operations represent one of the top activities projected to be outsourced at significantly greater levels in the future. In fact, nearly 28% of global industry respondents to BioPlan’s annual study indicate they will be outsourcing more of their fill/finish projects over the next 24 months.

Decisions in this area are likely to be based on efficiency, cost effectiveness, and capacity availability as the industry makes critical in-house vs outsource decisions. For CMOs to compete for fill/finish business, data indicate that it’s increasingly important that they position themselves as having state-of-the art equipment, especially in fill/finish services.

References
1. BioPlan Associates, Trends in Aseptic Bioprocessing Capacity for the Fill and Finish of Recombinant Biologics: An Analysis of US and European In-house Capacity and Capacity Utilization (BioPlan Associates, December 2014).
2. BioPlan Associates, 11th Annual Report and Survey of Biopharmaceutical Manufacturing Capacity and Production (Rockville, MD, April 2014), http://ift.tt/2IhMNhA.

Article Details
Pharmaceutical Technology
Vol. 39, Issue 1
Pages: 66-68
Citation: When referring to this article, please cite it as E. Langer, “Fill/Finish Capacity Use for Biologics,” Pharmaceutical Technology 39 (1) 2015.

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FDA Publishes Revised Process-Validation Guidance

FDA published its long-awaited guidance titled Process Validation: General Principles and Practices this week. The document, which revises and replaces the 1987 guidance titled Guideline on General Principles of Process Validation, explains the components of process validation for the manufacture of human and animal drug and biological products, including active pharmaceutical ingredients. The guidance emphasizes the importance of risk-based decision making and recommends that the degree of control over attributes be commensurate with their risk to the process or output.

The new guidance categorizes process-validation activities into three stages.
During Stage 1, process design, a company defines the commercial process based on what it has learned throughout development and scale-up activities. The document recommends that companies use design-of-experiment studies and risk-analysis tools to understand process variables. In Stage 1, a company should develop strategies to control processes by reducing the variation of inputs, adjusting equipment to compensate for input variation, or both tactics. Process design must be based in science, and decisions about design should be documented, according to the guidance.

During Stage 2, process qualification, a company should evaluate its process design. This evaluation should include an examination of the facility and the qualification of equipment and utilities, according to the guidance. In addition, personnel should carry out process-performance qualification (PPQ) to confirm the process design and demonstrate that the commercial manufacturing process performs as expected. “The approach to PPQ should be based on sound science and the manufacturer’s overall level of product and process understanding and demonstrable control,” according to the document. PPQ requires a written protocol that describes items, such as manufacturing conditions, data to be collected, tests to be performed, and the sampling plan. The ultimate decision to begin commercial distribution should be supported by data from commercial-scale batches, according to the guidance.

Stage 3, continued process verification, provides ongoing assurance during routine production that the process remains in a state of control. This goal requires a system for detecting deviations from the process. “Adherence to the CGMP [current good manufacturing practice] requirements, specifically, the collection and evaluation of information and data about the performance of the process, will allow detection of undesired process variability” and help personnel determine whether action must be taken to correct, anticipate, and prevent problems so that the process remains in control, according to the guidance.

During this stage, a company should establish an ongoing program to collect and analyze product and process data that relate to product quality. Trained personnel should statistically trend and review the data, and the information collected should verify that the quality attributes are appropriately controlled throughout the process, according to the guidance.

See related Pharm Tech articles:

The Importance of Equivalence in the Execution and Maintenance of Validation Activities (Pharm Tech)

The New FDA Process Validation Guideline (Pharm Tech)

Is FDA’s Draft Process-Validation Guidance a Mixed Blessing? (Equipment & Processing Report)

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Fill/Finish Capacity Use for Biologics

Utilization averaged 55% for lyophilization
58% for pre-filled devices
70% for vialing.

Figure 1: Top five activities outsourced to some degree by biomanufacturers.

Future trends
The fill/finish industry will likely depend on ramp-up of technologies and capabilities both in-house and at CMOs. Future trends will include:

Fill and finish CMOs are becoming larger, through mergers and acquisitions.
CMOs will continue to install state-of-the-art fill/finish equipment, mostly to support clinical manufacturing. Biopharmaceutical CMOs will do less sub-contracting of their fill and finish to specialized CMOs.
Fill-Finish CMOs in India and rapidly developing countries are handling increasing amounts of biopharmaceutical products, mostly for domestic and lesser-regulated international commerce.

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Is FDA’s Draft Process-Validation Guidance a Mixed Blessing?

The US Food and Drug Administration’s Draft Guidance for Industry—Process Validation: General Principles and Practices provides a life-cycle approach for validating pharmaceutical processes and aims to help pharmaceutical companies achieve consistently high product quality. The document includes several concepts that are familiar to the industry but also contains ambiguities and recommendations that might be difficult for some drugmakers to follow.

The draft guidance suggests manufacturers establish links from their clinical process to their commercial-manufacturing process. This approach is similar to the one FDA has used in its preapproval inspections. If the guidance becomes final as it currently stands, manufacturers may be expected to use the data that they gain during formulation and development to define a product’s critical attributes, which would be the basis for the manufacturing-process parameters.

The agency points out that development and formulation data can improve a company’s understanding of its processes during scale-up and commercial manufacturing. This understanding would help companies control variability and increase product quality, says Chris Ames, director of global validation at Catalent Pharma Solutions (Somerset, NJ). Companies would submit these data to FDA to establish links between clinical and commercial processes.

But the draft guidance does not advise manufacturers about how to identify the most important characteristics of its product or manufacturing process, or about how to demonstrate links from the clinical to commercial process. “They’ve left it completely open to interpretation as to what data you provide and what format you use,” says Jim Agalloco, president of Agalloco and Associates. This ambiguity would suit Big Pharma because it frees companies to use their experience and discretion in deciding how to follow the guidance, says Agalloco. Small and emerging drugmakers, however, would likely be confused because they don’t have the depth of knowledge that would help them define critical attributes.

Some elements of the draft guidance resemble a Six Sigma approach to manufacturing, which is familiar to the pharmaceutical industry. The main similarity is the draft guidance’s recommendation of a statistical link that demonstrates that variability remains constant from the clinical through the commercial manufacturing stages. The statistical link is intended to confirm that processes are the same throughout all phases.

Although the draft guidance suggests statistical analysis, it leaves industry with only a broad understanding of what that means. FDA does not explicitly suggest that manufacturers use particular statistical tools, the agency simply recommends that companies apply good statistics to establish the links, says Agalloco.

The draft guidance suggests manufacturers define a process that can be measured, analyzed, improved, and controlled, and this approach is closely related to Six Sigma. The benefit of the Six Sigma technique is that it provides a mechanism for scientific review of a process, for assessing variability, and for identifying improvements, says Ames.

On the other hand, it is unclear whether the draft guidance recommends a product be refined in the way that a Six Sigma approach would. “To me, Six Sigma implies an acceptance by FDA that you might not have done a sufficient job in development and scale-up and are allowed to improve product and process while it is in operation,” says Agalloco. Patients’ experiences with a product might persuade a manufacturer that it should adjust one of the drug’s parameters to improve it. Six Sigma would allow postcommercialization changes to a product, but the draft guidance may not be compatible with them, Agalloco says.

Before it could submit a regulatory filing, a company would have to spend a great deal of time and money to better understand its ingredients, its product, its manufacturing process, its material handling, and associated variables. Pharmaceutical companies might object to the draft guidance’s approach because it suggests this expensive work be completed before commercialization, but the costs would not be recoverable before commercial-scale manufacturing began.

Although it is based on good science, if the final guidance is approved as drafted, it could easily increase drug-development time by one or two years, thus costing a manufacturer millions of dollars, says Warren Charlton, a consultant at WHC Bio Pharma Technical Services. Manufacturers would need to use smart strategies to shorten development time, but not knowing how much data regulators expect in a submission would make this strategy difficult.

The draft guidance inspired a huge volume of comments that will likely take FDA a long time to review, says Agalloco. Even though the guidance might not be final for at least a year, manufacturers would be wise to study it now and seek advice about interpreting it. In this difficult time for the pharmaceutical industry, no company can afford to ignore regulators’ recommendations, and advance preparation would be to a manufacturer’s benefit.

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Cleaning Validation for APIs | Pharmaceutical Technology

FoapAB/Shutterstock.comAt home, when washing the dishes, do we ever consider what meal they will be used for next? When plates and cutlery are taken out of the cupboard to set the table, do we ever ask what they have been used for and whether they are clean enough for the gourmet course about to be served?

Are there different levels of cleanliness used for the dishes depending on the food served or the guests we entertain? Silly questions, apparently, but the industry’s current approaches to pharmacutical cleaning validation can often seem just as random. Cleaning limits for pharmaceutical manufacturing equipment are computed based on the previous and next products for every product change. As a result, it is often difficult to explain the cleaning and cleaning validation concept.

This article is about combining the simplicity of the household cleaning concept with the science needed to protect patients’ safety. To reach this goal, it may be necessary to revisit a few traditional ideas about cleaning validation and to establish new principles. The focus will be on API manufacturing of small molecular weight substances (i.e., with industrial organic chemistry and the corresponding traditional plant equipment such as reactors, separators, crystallizers, centrifuges, filters, dryers, mills, and blenders, plus all the connecting pumps, pipes, and hoses). The size of the vessels typically ranges from 250 to 10000 L, and a manufacturing line can have up to several hundred square meters of product contact surface.

The change from product A to product B is not a frequent case

APIs are usually produced in multipurpose equipment. Several individual modules are concatenated to build a product- specific production line or train. After a campaign, the line usually gets disconnected and the individual modules, not always all of them, are reconfigured into a new line for the next product. Some products may use exactly the same production line as others, but most of the time, every product uses a somewhat different configuration of modules. Some equipment is used for many products; other parts are practically dedicated to a few or to only one product.

When a line is set up for product B, some parts will indeed have been used for product A right before; other parts, however, may have been in contact with product X, and mobile parts may be taken from the storeroom and have been used for product Y or Z months before. There is rarely a pure product changeover from A to B; in reality, the changes are from products A, X, Y … to product B.

Similarly, when cleaning a piece of equipment, it is not always known what the next product will be. The change could be from A to the next products B, C, or D. This is particularly the case with interchangeable mobile equipment such as flexible hoses, filters, or tanks that go back to the storeroom after cleaning. Under such circumstances, a number of questions will arise, including the following:

What was the previous product manufactured at the facility, and what will be the next one?
How can one make sure that all parts are clean, to the right level for making the next product(s)?
Can the cleaning validation concept be built and the cleaning limits computed based on the ideal product. change from A to B?

The following principles aim to answer these questions.

The cleaning procedure is independent of the following product(s)

Equipment cleaning should be thought as a reset function. The equipment is reset to a clean ground state form where it can be used for any product. Every piece of equipment labeled clean must be ready for use, no questions asked.

Consider the analogy with the household: doing the dishes, one doesn’t ask what will be cooked the next day, and when taking clean plates out of the cupboard, it doesn’t matter what the last meal was. A clean plate is a clean plate.

Cleaning without asking what the next product will be implies that setting the cleaning limit must be a comprehensive exercise that includes all products of a manufacturing unit. Quite often, the “cleaning validation runs” and the corresponding plans and protocols only consider the actual product change A to B, which leads to cleaning à la carte, asking: How clean does it have to be today?

Using the same cleaning procedure for different cleanings, it can happen that different limits must be met from one cleaning to the next, because the limits get recalculated each time for the actual, ideal product change. With such moving targets, it is impossible to properly validate a cleaning process.

A standard cleaning limit (SCL) should be set, in mg/m2

Establishing a standard cleaning limit (SCL) for all the equipment is the core element of the cleaning concept (1). The SCL is the level of cleanliness (expressed in mg/m²) that a production unit must maintain with every cleaning process, every time. The SCL applies to every piece of equipment, fixed or mobile, large or small, independently of the product changes.

What does the cleaning practice tell us?

Most production units will have collected cleanliness data, typically results of swab tests, over quite a long period. An example of such a data set is given in
Figure 1. The example is from a relatively old manufacturing unit (Unit A), which uses traditional equipment for industrial organic chemistry. The cleaning procedures consist mainly of flushing and boil outs with solvents and manual scrubbing with water and a detergent.

Figure 1: Graph of more than 250 swab results collected over a period of 18 months in multipurpose API unit A. Swabs were taken after using different cleaning procedures, after campaigns of different lengths, making different products, and from different pieces of equipment made of different material. The lowest values were often limited by the limit of quantitation of the analytical methods. (All figures courtesy of authors.)

Figure 1 gives a good idea of the level of cleanliness this particular production unit can achieve. The values vary a great deal and the level of cleanliness that can reasonably be guaranteed is limited by:

Physicochemical properties of the process residues
Equipment design
Cleaning methods.

The conclusion from Figure 1 was that this particular production unit could be reliably cleaned down to 25 mg/ m² . Although much lower values than 25 mg/m² were often obtained (see Figure 2), 25 mg/m² is considered the unit’s standard cleaning performance and so, for this unit, the SCL was set at 25 mg/m.²

Figure 2: Histogram with cumulated frequency of swab results from Figure 1. 75% of swabs gave ≤1mg/m², 95%≤10 mg/m².

Based on reality, rather than theory

Setting the SCL in this simple and pragmatic way, solely based on experimental data, without any theoretical considerations, reflects acceptance of the variability and limitations inherent in current cleaning practice. However, this approach represents a radical change from tradition. Previously, the limit was calculated in the validation protocol that only considered the effective product change. The quality assurance (QA) department determined to what limit the equipment was to be cleaned at this one time, without considering the big picture of years of cleaning experience.

The theoretical safety requirements for a changeover from product A to B are known. Based on the permitted daily exposure (PDE) of A, the maximal safe carryover (MSC) of product A into product B can be determined by using Equations 1. Dividing the MSC by the product contact surface used to make B gives the maximum safe surface residue of A (MSSRA) on equipment used for B.

Applying Equations 1 and 2 to all the theoretically possible product changes in a defined manufacturing unit yields the MSSR matrix. The MSSR matrix is the matrix of all possible required levels of cleanliness for a defined portfolio of products. See reference 2 for an example of a computed MSSR matrix.

Figure 1 shows a graph of more than 250 swab results collected over a period of 18 months in multipurpose API unit A. Swabs were taken after using different cleaning procedures, after campaigns of different lengths, making different products, and from different pieces of equipment made of different material. The lowest values were often limited by the limit of quantitation of the analytical methods.

Risk assessment

The risk of carryover contamination can be assessed by comparing the level of cleanliness that can be reasonably expected (the SCL) with the cleanliness required by the MSSR matrix (2). During risk assessment, the following should be addressed:

Are the cleaning processes good enough to ensure safe changeovers? If not, is it reasonable to simply conclude that the cleaning procedures should be improved? Maybe there is room for improvement; but chances are that the cleaning processes have already reached their limits. If this is the case, can risk of the worst changeovers be mitigated by other means than cleaning?
Can a few theoretical changeovers be eliminated from the MSSR matrix because they do not share any common equipment?
Can manufacturing campaigns be planned in a way to avoid critical changeovers?
Do certain products call for partially of fully dedicated equipment?

Such considerations should be summarized in a risk assessment document, which should be part of the cleaning validation master plan. Additional risk assessment can be done based on analysis of the swab results shown in Figure 2. The SCL of 25mg/m² is a safe limit, because the probability of a cleaning giving a swab result >25 mg/m² is <1%. Should a failure risk of 5% be deemed acceptable, the SCL could even be lowered to ≤10 mg/m². Figure 3 shows swab data, as does Figure 1, but, in this case, they were measured in a different manufacturing unit (B) of the same company.

The data for unit B are very similar to those for unit A and the SCL was also set at 25 mg/ m² for unit B. Because units A and B both manufacture small organic molecules, use similar equipment and very similar cleaning processes, it is not really a surprise that similar cleaning results are obtained.

Introducing an SCL opens the possibility of having a single cleaning limit for many different manufacturing units, which can help to further standardize cleaning validation. In fact, the SCL of 25 mg/m² was eventually introduced in five different manufacturing units.

With its general applicability and ease of use, the SCL concept can be compared to the classification system for cleanrooms, where the room class is independent of the room size or the nature and quantity of product that is handled in the room. The SCL is, similarly, independent of equipment size, products, or batch size.

Via the SCL, one can imagine a classification of API manufacturing equipment (e.g., in class 5, 25, and 50 mg/m2). Such equipment classes, which in fact would reflect validated cleaning commitments, could be criteria to consider when allocating new products to manufacturing sites or outsourcing API manufacturing. Comparing the SCL and the MSSR matrix is a straightforward way to start a cleaning risk assessment and to implement the new EMA guideline on shared facilities (3). In addition, adopting the SCL offers a number of benefits. For example, it:

Allows for a consistent level of cleanliness to be enforced over a whole production unit
Simplifies cleaning validation because there is no need to compute and justify the cleaning limit in every single validation plan; the limit can instead be justified once in an appropriate document, (e.g., in the cleaning validation master plan)
Allows manufacturers to standardize validation activities in the analytical laboratory: Specifications for swab tests are constant, as are the working ranges of high-performance liquid chromatography (HPLC) methods and when spiking coupons for recovery studies.

Last but not least, the SCL is a simple concept that is easy to understand and to explain.

Acknowledgements

The authors would like to thank Sébastien Schuehmacher, Michael Wölfle, and Markus Schaefer for their relentless cleaning efforts and their support in the development of the SCL concept, and to Ian Udri for compiling all the data.

References

1 M. Voaden, A Leblanc, RJ. Forsyth, Pharmaceutical Technology, 31 (1) pp. 74-83, 2007.
2 M. Crevoisier et al, Pharmaceutical Technology 40 (1) pp. 52-56, 2016.
3 EMA, Guideline on Setting Health Based Exposure lLmits for Use in Risk Identification in the Manufacture of Different Medicinal Products in Shared Facilities, (EMA, 2014).

Article Details

Pharmaceutical Technology
Vol. 41, No. 9
September 2017
Pages: s12-s16

Citation

When referring to this article, please cite it as M. Crevoisier and T. Peglow, ” Cleaning Validation for APIs,” Pharmaceutical Technology 41 (9) 2017.

About the Authors

Michel Crevoisier is former senior quality expert for Novartis Pharma AG, and Thomas Peglow is senior cleaning validation expert at Novartis Pharma AG, Switzerland. The views expressed in this article are those of the authors and not necessarily of their employers.

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