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PharmTech.com

2014

ANALYTICAL AND

BIOANALYTICAL

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©2014 Advanstar Communications Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical including by photoco py, recording, or information storage and retrieval without permission in writing from the publisher. Authorization to photocopy items for internal/educational or personal use, or the internal/ educational or personal use of specific clients is granted by Advanstar Communications Inc. for libraries and other users registered with the Copyright Clearance Center, 222 Rosewood Dr. Danvers, MA 01923, 978.750.8400 fax 978.646.8700 or visit http://www. copyright.com online. For uses beyond those listed above, please direct your written request to Permission Dept. fax 440.756.5255 or email: [email protected].

METHOD TRANSFER

4 Keys to Successful Method Transfer

Cynthia A. Challener

ANALYTICAL QUALITY BY DESIGN

11 AQbD Adds Rigor to Method Development

Paul Kippax

VIRAL CONTAMINATION

17 The Challenge of Finding the Unknown

Cynthia A. Challener

ELEMENTAL IMPURITIES

21 Rapid Screening for

Elemental Impurities using ICP-MS

Jonathan L. Sims and Fadi Abou-Shakra

ASSAY VALIDATION

26 Validation of a Multiplex

Bead-Based Assay

Rabia Hidi, Catherine Diot, Sebastien Melin, Jiyhe Jang-Lee, and Alain Renoux

DATA MANAGEMENT

29 Standardizing Data Management

James M. Vergis and Dana E. Vanderwall

NEW TECHNOLOGY

31 Advances in Analytical Technology

Ashley Roberts

32

Ad Index

ANALYTICAL AND BIOANALYTICAL TESTING 2014

Issue Editor: Rita Peters.

On the Cover: Rafe Swan/Cultura/Getty Images; Dan Ward EDITORIAL

Editorial Director Rita Peters [email protected] Managing Editor Susan Haigney [email protected]

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Contributing Editors Jill Wechsler [email protected]; Jim Miller info@ pharmsource.com; Hallie Forcinio [email protected]; Susan J. Schniepp

[email protected]; Eric Langer [email protected]; and Cynthia A. Challener, PhD [email protected]

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4 Pharmaceutical Technology ANALYTICAL AND BIOANALYTICAL TESTING

Method Transfer

M

ethod transfer during scale-up of the

biopharma-ceutical manufacturing process can be challenging. Not only must methods be suitable at each phase of the development process, they must be robust and effective on multiple platforms. The skills and capabilities of the technicians and quality control (QC) laboratory personnel (internal or external) must also be considered. Most importantly, open effec-tive communication between groups and clear, established protocols are required, regardless of whether methods are being transferred within the same organization or between contract manufacturers/ laboratories and biopharmaceutical companies.

Types of transfers

Analytical methods transfer exercises (AMTEs) occur throughout the various phases of drug development and are almost unavoidable at certain particular stages, such as when the process is transferred from research to development for clinical trial material manufac-turing and when scaling up for commercial production, according to Roberto Rodriguez, an associate research fellow at Pfizer. Most common are linear transfers (i.e., transferring from a laboratory that supports early-stage drug development to one that supports late-stage development) or for parallel use (i.e., multiple sites supporting drug development).

Suitability a must

The most important aspect of analytical method transfer is ensur-ing that the methods are suitable for their intended purpose at the various phases of the drug-development process and through the product lifecycle, according to Mary Gasper, senior supervisor of

an-Keys to Successful

Method Transfer

Cynthia A. Challener

Methods must be suitable at each development

phase, robust, and effective on multiple platforms.

Cynthia A. Challener is a contributing editor to Pharmaceutical Technology.

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EXPERTISE

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THOROUGH EXAMINATION.

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USP <232>, <233> Heavy Metals Dr. Arthur Ferruzzi, NMR Spectroscopist

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alytical development with SAFC. “In early stages, that means using sound science in practice. Mov-ing into phases I and II, it means lookMov-ing ahead to qualifying methods and preparing them for ICH validation,” she explains.

It is also important to recognize, Gasper notes, that processes must deliver consistent and repre-sentative materials to move forward, and therefore, methods cannot be locked down until the process is locked down, which is a crucial factor for mov-ing toward phase III and into commercialization. “Our experience at Almac is that formal transfer generally does not take place in the development phase of a molecule, but only once the method has been validated by the originating laboratory,” agrees John Wood, analytical account manager with Almac. At Pfizer, however, Rodriguez notes that formal methods transfer is performed during development, with methods validation appropriate for the stage of development required.

The main goal of AMTEs, according to Ro-driguez, is to achieve the same (or very similar) method performance from one site to the other. “Although it is tempting to look at AMTEs from

the technical standpoint only, performing an assay in a second/new laboratory requires a lot more than executing the method’s standard op-erating procedure (SOP). An extensive evalua-tion that includes stage of development (product and method), method knowledge, type of method,

supporting systems (e.g., data collection, storage, and retrieval), and cGMP requirements should be performed prior to initiating an AMTE,” he asserts. Once this information is collected from the laboratories or sites involved, an analysis should be performed with the goal of identify-ing the most appropriate strategy and uncoveridentify-ing potential issues.

Transfer strategies

Most methods begin as a draft with loose speci-fications that detail the general expected results. The transfer of these methods is a scientific exer-cise that gets stricter the further along in develop-ment, including more formal specifications and limitations, according to Gasper. Rodriguez adds that setting meaningful transfer acceptance cri-teria is easier in later stages of development when the method has been optimized and there is less variability. “The transferring strategy and require-ments are dictated by the product stage of develop-ment, partly due to regulatory expectations, but largely because method knowledge is much less early in development than when fully validated, and the success of the transfer depends on the readiness of the method and all that is involved on its execution,” he says.

Three of the most common strategies for method transfer include transfer by scientific rationale, transfer by performance, and transfer by co-valida-tion, according to Rodriguez. AMTEs by “scientific rationale” (i.e., paper exercises without wet analyti-cal work) are used sparingly, because they are not favored by regulatory agencies unless a strong jus-tification is provided, and generally only when the receiving lab has experience with a closely related method used for the same or similar product.

Method Transfer

Most methods begin as a

draft with loose specifications

that detail the general

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Transfer by performance requires a protocol with AMTE acceptance criteria and execution of the method in the receiving lab to generate data, including repetition of some method validation steps, such as precision and linearity that can be compared to the transferring of laboratory data for the same materials. “The second laboratory must ensure that it can perform the analysis and obtain the same results as the originating labora-tory,” comments Wood. “The whole process should be carried out according to a transfer protocol generated by the method sending laboratory and agreed by the receiving laboratory that establishes the specific acceptance criteria for the transfer to be successful.”

Transfer by co-validation commonly involves the second laboratory in the execution of meth-ods validation and demonstration that the pooled data from both laboratories meet method valida-tion acceptance criteria. This strategy would be ap-propriate if it is not possible to conduct compara-tive testing—such as when the sending laboratory has previously outsourced the testing to another laboratory and this laboratory is no longer in a po-sition to carry out its part of the testing, accord-ing to Wood. AMTE by co-validation can be used anytime the two exercises can be combined or are close together, adds Rodriguez.

In all cases, the method-acceptance criteria should be established before the drug is moved toward phase III, so the focus can shift to validation. “It is also important that the materials supply is locked in and that the transfer methods are well documented. QC methods need to have staying power for the life of the drug. For instance, if the drug is produced for 15 years, methodologies need to remain valid through this life span,” Gasper asserts.

In addition, because most transfers (should) gen-erate data, Rodriguez recommends the inclusion of a statistician in the design and evaluation of the transfer. He also notes that, just like method vali-dation, AMTEs usually represent a “point in time” or a “snapshot” that should be complemented with continuous performance verification.

Need for cross-functionality

Once validated, a method should be effective for any suitable instrument, although its performance should be demonstrated as part of the method val-idation or during the transfer, according to Wood. “Methods that can only be run on a single

plat-form or using an instrument from a single vendor are not robust,” states Gasper. Alternative mate-rials are shown to be suitable when using vari-ous sources and lot numbers provides the same (equivalent) results. Demonstrating effectives on different instruments, however, may require more extensive work, according to Rodriguez. “Some in-strument differences are easier to overcome than others. For example, for HPLC [high-performance liquid chromatography], retention time bias due to dead volume can be addressed using a correc-tion factor or having specific criteria within the method for each model or brand. Detector differ-ences such as sensitivity, on the other hand, result in discrepancies for some validation parameters (e.g., linearity, quantitation limit, and detection limit) that may lead to a preference for one instru-ment,” he says.

There has been some movement in the industry towards the harmonization of platforms, according to Gasper, but at this point she believes it is still important to run methods on different platforms to understand the implications.

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Communication and trust

A significant consideration, no matter the phase, is the intended location of manufacturing for the drug, and it makes a difference whether it will be manufactured at an internal GMP lab, pilot plant, CMO, or even an internal manufacturing facility, according to Gasper. In general, she notes that in-ternal transfers are often much smoother because the platforms for manufacturing are already in place. Regardless of location, the capabilities and skills of the receiving lab must be assessed, and the greatest element of success is communication. “Open, honest, face-to-face (if possible) discus-sions about the project background, methods, and process transfer are imperative in order for the re-ceiving lab to be fully invested in the success of the transfer,” she observes. Wood adds that the receiv-ing laboratory should perform a familiarization exercise prior to the actual transfer and have any questions addressed prior to commencement of the transfer. He also notes that many sending labora-tories send an analyst familiar with the method to the receiving lab to aid in the familiarization stage. There are additional considerations that must be taken into account when transferring to external laboratories. Potential issues can be uncovered if the needs for each transferred method are clearly defined, according to Rodriguez, including not only the equipment, materials, personnel training and experience, but also the data management systems, document requirements for quality as-surance (QA) compliance, and lifecycle manage-ment agreemanage-ments (e.g., change approval processes to avoid “assay drift”).

Pfizer has learned that differences may arise due to subtle general laboratory practices not addressed by documents used during the AMTE. “The art of

writing an SOP is a fine balance between providing enough (and accurate) information and writing a protocol the length of a novel. Many details that may affect assay performance are often left out because the writer considers them to be ‘general knowledge’ for someone skillful in the execution of the test,” Rodriguez explains. In one example, an approximate 5% bias between laboratories was traced to the general practice of “blowing” the sample off the pipette tip used to dispense the sam-ple in one laboratory but not the other. “This issue demonstrates how an AMTE can be complicated or derailed by the smallest details,” he comments.

In addition, when transferring to external labo-ratories, the transfer plan should include agree-ment to a strategy and timing that satisfies re-quirements at both companies. “AMTEs are by no means standardized across the industry, and contract laboratories may have internal require-ments that are different than those of the transfer-ring company. The challenge is to identify the best approach to fill those gaps,” he says.

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The industry has reacted to these needs with the development of more strategic alliances and partnerships between companies to maximize specific technical and functional areas of re-search, Gasper observes. “Collaboration allows companies to focus on what they are good at, which creates ample flexibility and cost savings. There is also the benefit of already knowing that the GMP and quality processes are in place, so there can be faster turnaround,” she says.

Added complexity for biopharmaceuticals

In principle, there should be little or no differ-ence in the transfer processes for small molecules and biologics, according to Wood. “The goal for both is to demonstrate that the methods can be operated successfully and reliably in the second laboratory,” he says. Biologics are, however, more complex than small-molecule drugs, and there is generally less historical data available. As a re-sult, it is more difficult to understand the down-stream fates of biotherapeutics and the impact of impurities, according to Gasper. In addition, she notes that biopharmaceutical production processes are much more sensitive to process-ing changes and parameter variability, and there is also often greater variability in raw materials from lot-to-lot. “As a result, more sophisticated analytical tools and resources are required to characterize the science,” she notes. Wood agrees that the acceptance criteria for method transfer for biopharmaceuticals may be looser, but they still must reflect the specification for the product and the capabilities of the method. It may also be necessary to take extra steps to ensure that the receiving laboratory has the knowledge required to run the methods reliably. PT

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Analytical Quality by Design

Q

uality by design (QbD) itself is not a regulatory re-quirement; however, the approach has now been widely adopted and is encouraged by FDA. This is particularly true within the generic drug sector, since regulatory bodies, most especially FDA, have indicated that they would look more favorably upon abbreviated new drug application (ANDA) submissions that demonstrate adherence to QbD principles. This regulatory landscape is promoting in-creasing acceptance of QbD and encouraging its application to other activities. Analytical method development is high on the list of potential beneficiaries.

Like QbD, analytical quality by design (AQbD) is not a regulatory requirement, but there are strong motivating factors for its adoption including commentary by FDA (1). AQbD extends the knowledge-led approach promoted by QbD to the development of robust ana-lytical methodologies and similarly holds out the prize of improved flexibility and control. This prize is achieved through a process of systematic risk assessment and the implementation of appropriate controls for all critical aspects of an analytical method. The applica-tion of AQbD principles ensures that an analytical method will con-sistently deliver accurate and precise data throughout the lifecycle of a pharmaceutical product. It also brings benefits such as flexibility within the defined design space and in-depth assessment of the im-pact that various analytical parameters have on the validity of the results. Together, these benefits assist the ability of the method to continue to perform through production scale ups and the resulting method transfers between different laboratories at the same site or between different sites. In addition to this, it also aids day-to-day troubleshooting and any out-of-specification investigations.

AQbD Adds Rigor to

Method Development

Paul Kippax

Analytical procedures and method validation should be developed with a structured and rigorous approach. Analytical quality by design (AQbD) is a means of ensuring that rigor.

Paul Kippax is product group manager, Malvern Instruments.

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Analytical Quality by Design

AL

AQbD and QbD processes are intrinsically linked, and their respective workflows parallel one another (Figure 1). The conventional QbD workflow begins with the identification of performance targets that define how a product will deliver the required clinical efficacy, the quality target product profile (QTPP). The QTTP usually relates to a defined pharmacological or physical feature, such as the dissolution profile for an oral solid dosage form. The variables that must be controlled to deliver the QTTP are then identified as critical quality attri-butes (CQAs). Subsequent steps involve identifying the best way to implement control over these CQAs which directly affect product performance.

A CQA is required to be measured and con-trolled by the applica-tion of an appropriate analytical method. For instance, a CQA that in-fluences dissolution rate of an API is its particle size distribution. Con-trolling particle size to deliver the QTPP relies on employing a suitable ana ly tica l technique. This is where AQbD comes in. AQbD begins with the identification of an analytical target profile (ATP)—a defini-tion of what the method is required to do—such as measuring API par-ticle size in a way that is meaningful to control of dissolution and delivers a certain level of repro-ducibility and accuracy. A detailed consideration of both the ATP and the range of analytical tech-niques available to measure the targeted CQA— along with their basic principles, limitations, and any potential sources of errors associated with de-livering the required data—forms an integral part of the AQbD process.

Once an analytical technique has been chosen, AQbD follows the same process as QbD:

identifica-tion of the critical method attributes that impact the results generated by the analysis; systematic assessment of any associated risks and variability; and implementation of a system of control. The

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systematic study of risk fac-tors may be supported by de-sign of experiments (DOE) or multi-variate analysis (MVA) tools and leads to the scop-ing of the design space or method operable design re-gion (MODR) for the analyti-cal method. This is the oper-ating area within which the ATP is consistently met. As with QbD, the entire AQbD workflow is held within a sys-tem of lifecycle management, ensuring a process of continu-ous improvement.

Applying AQbD to

particle size analysis

Rather than identifying a single set of measurement pa-rameters to produce analyti-cal data, an AQbD approach involves the development of a comprehensive understand-ing of how all influential fac-tors impact the output from an analytical method. The AQbD approach would there-fore prompt a more extensive experimental program during method development than the conventional approach.

Laser diffraction is a method of choice for par-ticle size measurement for many pharmaceutical products and can, therefore, be helpful in pro-viding some insight into the practicalities of the

AQbD approach to method development. Potential sources of error in laser diffraction particle size measurements can be classified as relating to in-strumentation, sampling, and dispersion.

Figure 2: A pressure titration with a high energy disperser suggests that stable particle size measurement is achieved at pressures in excess of 2.5 bar.

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Analytical Quality by Design

Laser diffraction is a mature technology and instrument design has been refined to a high degree of automation and accuracy. The errors associated with instrumentation, therefore, tend to be small, even at the extremes of the measure-ment range of the technique, which runs from 0.01-3500 µm.

Sampling is potentially a more

significant source of error,

especially for larger particles.

Sampling is potentially a more significant source of error, especially for larger particles. Sample size often has to be increased when mea-suring larger particles to ensure that a sufficient number of particles are measured to achieve the required accuracy.

Conversely, dispersion tends to be a greater source of error for finer particles. Appropriate dispersion ahead of measurement underpins the generation of particle size distribution data for primary particles in the sample, rather than any aggregates present. The strength of inter-particle forces increases with decreasing particle size, making complete dispersion more difficult for fine particles.

The two most commonly used techniques for dispersing a sample prior to a laser diffraction measurement are to either disperse the sample as a dry powder or to disperse it within an appropri-ate liquid. In case of dry dispersion, the sample is entrained in a pressurized air flow. Parameters that need to be considered in controlling the state of dispersion for dry powders include selection of the dispersion air pressure and selection of an

appropriate disperser geometry. Higher air pres-sures tend to lead to more energy being avail-able for dispersion, but also increase the risk of particle damage occurring during the dispersion process. The risk of particle damage can be miti-gated by lowering the air pressure or by selecting a different disperser geometry.

Figure 2 shows data from a dry powder

dis-persion pressure titration, in this case using a disperser geometry design to deliver a high dis-persion energy. A pressure titration is a plot of measured particle size as a function of the pres-sure of air flow and therefore tracks the effective-ness of dispersion as energy input is increased. This plot shows that stable particle size mea-surement is achieved at a pressure in excess of 2.5 bar, suggesting that these conditions may be appropriate for analysis. However, comparison with an orthogonal method (wet sample disper-sion) indicates that realistic particle size data are reported at a dispersion pressure of just 0.2 bar. This suggests that application of a high pressure causes milling of the sample. A possible decision from these experiments would be to measure the sample at a dispersion pressure of 0.2 bar and a conventional approach would incorporate this in a standard operating procedure (SOP).

An AQbD approach would, in contrast, focus attention on the fact that at 0.2 bar the gradient of this plot is noticeably steep, suggesting that with this set-up the operating range, the MODR, is very narrow. This in turn indicates that the method is unlikely to be inherently robust; it is associated with an intrinsically high level of risk.

Figure 3 shows a pressure titration using a

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extended investigation prompted by a more r i g o r o u s AQ bD a p -proach. Here robust re-sults are reported over a relatively wide pressure range, between 0–1.0 bar. The less energetic disperser design is as-sociated with a wider MODR and a reduced requirement to closely control pressure. Here then, a broader experi-mental program, cou-pled with some intel-ligent interpretation of the experimental data, delivers a

fundamen-tally more robust method that is more likely to perform well over the long term. This is the exact intention of AQbD.

Analytical instrumentation and AQbD

Instrument makers are increasingly aware of the benefits of AQbD for the pharmaceutical industry and the need to lighten the associated analytical workload through innovation. Recent advances in instrumentation and software help reduce some of the workload required to stream-line the implementation of AQbD. For example, certain analytical instruments have the function-ality to automatically run through a sequence of operating conditions. Such functionality allows analysts to build measurement sequences to fa-cilitate rapid experimentation and automate both method development and validation.

Figure 4 shows an SOP sequence for stirrer speed on the Mastersizer 3000 laser diffraction analyzer (Malvern Instruments) software, which could be used to efficiently conduct a stirrer speed titration as part of scoping the MODR for a laser diffrac-tion measurement based on wet dispersion. Such sequences, which are easily saved and recalled, are also useful during validation.

Other instrument features enable real-time as-sessment of the impact of data analysis factors on analytical output. For example, the optical prop-erty optimizer (OPO) for the Mastersizer 3000 enables analysts to explore the impact of optical properties on reported particle size. In combina-tion with the SOP player, this funccombina-tionality helps users to efficiently implement a DOE approach to comprehensively understand all aspects of the analysis.

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Modern instruments also offer tools that provide feedback on the quality of data being generated, en-abling researchers to critically assess measurement data and results during an analysis. These features can provide advice relating to the measurement process, helping to address the issue of control, which is such an important aspect of AQbD. Soft-ware for automated data review is also available to similarly provide verification that methods have been used correctly, by enabling the systematic cross-comparison of parameters and results.

Lifecycle management of analytical procedures

In going beyond simple SOP definition to create an MODR, AQbD facilitates a responsive approach to the variability encountered in day-to-day analysis. The greater control and flexibility this provides ensures

that analytical methods remain robust, reliable, and relevant throughout the lifetime of the product. AQbD also has the potential to reduce the risks involved in analytical method transfer, from the laboratory or pilot scale to commercial production. The root cause of failure of method transfer usually stems from in-sufficient consideration of the operating environment and a failure to capture and transfer the information needed to deliver robust measurement. The periodic assessment of the method’s performance coupled with in-depth understanding of the MODR forms the basis of continuous improvement of an analytical method throughout the lifecycle of a pharmaceutical product.

References

1. S. Chatterjee, “QbD Considerations for Analyti-cal Methods—FDA Perspective,” IFPAC Annual Meeting (Baltimore, MD, Jan. 25, 2013). PT

Analytical Quality by Design

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PharmTech Digital provides readers around the world with authoritative peer-reviewed research and expert analyses in the areas of process development, manufacturing, formulation and drug delivery, API synthesis, analytical technology, packaging, IT, outsourcing, and regulatory compliance.

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Pharmaceutical Technology Europe’s weekly electronic e-newsletter PTE e-Alert provides news, market developments, industry surveys and information on up and coming trade events.

PTE e-Alert

Equipment & Processing Report focuses on pharmaceutical manufacturing process and technology, providing manufacturing news, related regulatory issues, and current trends.

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The PT Sourcing and Management monthly e-newsletter is the authoritative source on sourcing and management within the pharmaceutical’s global supply chain.

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The ePT weekly e-newsletter delivers critical information on recent contract awards, company mergers & acquisitions, and fresh news of interest to a highly desired community of pharmaceutical manufacturing professionals.

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Viral Contamination

U

nlike with blood and plasma for which possible viral con-taminants are generally known, because the raw materi-als used in the manufacture of biologic drugs can come from animal, plant, and manmade sources, it is not pos-sible to predict all potential viral contaminants. Analytical methods, therefore, must be able to detect both known and unknown viruses. Traditional cell-based assays are effective but have limitations, in-cluding an extensive assay procedure time. Newer nucleic acid-based methods are much more rapid, but those implemented to date are generally designed for specific viral targets. Both biopharmaceutical companies and FDA, however, believe that new sequencing tech-niques capable of identifying multiple viruses can be adopted by the industry in the future.

No safety concerns

First, it must be stressed that the interest in new viral detection methods does not stem from any issues or problem cases related to the safety of biotherapeutics. “Biotechnology drugs are very safe from a viral contamination standpoint. The international standard ICH Q5A, which was promulgated in 1998, assures viral safety by requiring both testing of cell banks, raw materials, and bioreactor harvests and viral clearance using downstream purification pro-cesses,” says Kurt Brorson, a staff scientist for monoclonal antibodies with the Center for Drug Evaluation and Research (CDER) at FDA. Regardless of the analytical method, adds Ivar Kljavin, director of adventitious agent management with Genentech, because testing is trying to not only detect unknown viruses, but also do the impos-sible and prove a negative result, it is not sufficient by itself. “It is very important to realize that testing is crucial but only one part of

The Challenge of

Finding the Unknown

Cynthia A. Challener

Advanced analytical methods are speeding up the targeted evaluation of potential viral contaminants.

Cynthia A. Challener is a contributing editor to Pharmaceutical Technology.

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Viral Contamination

an effective solution for viral contamination pre-vention. It is absolutely imperative that steps be taken to minimize the risk of viral infection, such as heat treatment, viral filtration, and the tracking and tracing of all raw materials to their original sources in order to be able to identify potential risks,” he asserts.

Current methods effective but with limitations

The traditional test method is the in-vitro adven-titious virus assay, which uses various indicator cell lines for detection of viruses for in-process or lot-release testing of the bioreactor at the end of the run, according to Dominick Vacante, scientific director for virology with Janssen Pharmaceutical R&D. “The assay is very sensitive and can poten-tially detect one infectious virus particle. The limi-tation is that the virus must replicate in at least one of the indicator cell types and produce some type of effect that is detected by the readouts of the as-says, which are visual for cytopathic effects and/or hemadsorption or hemagglutination of specific red blood cells,” he explains. Problems do arise when a virus replicates but causes no signs of cytopathic effects, or is infectious but does not replicate in the cell types selected for the assay, which in both cases yields a false-negative result.

In some cases, the test article may interfere with the ability of a virus to infect the cells or display signs of infection, according to Kljavin. Cell-based

methods can also be variable; a virus that is de-tected in one assay may not be found when the test is repeated. “Equally importantly, it takes time for the viruses to replicate and grow, which leads to a very long test time of 14–28 days. A signifi-cant amount of product can be produced and sent downstream during that time, and if found to be infected must be disposed. The entire production facility, not just cell-culture areas, must be decon-taminated, which can lead to a disruption in the supply of the drug to patients, a situation that is unacceptable,” Kljavin states.

He again stresses, though, that cell-based assays are effective when performed in conjunction with other risk-mitigating steps like viral clearance vali-dation. The current issues revolve around develop-ment of new assays to test for viruses at the various sampling points that are more rapid, more sensi-tive, and broader. Gaining a greater understanding of how purification unit operations clear viruses, how robust they are, and how to best validate the clearance of different viruses are other measures that mitigate gaps in testing, according to Brorson.

Evolving technology

While ICH Q5A serves the industry and regulators well, Brorson notes that technology has evolved since 1998, leading to the development of differ-ent approaches, such as modular validation for ro-bust unit operations and the introduction of new assays for cell-line characterization, like genome sequencing-based methods. “ICH Q5A is silent on these new technologies since it was written before their introduction, and could stand to be updated with developments of the past 15 years,” he says. FDA has been following new pan virus detection methods/deep-sequencing methods for cell-line

Cell-based assays are

(19)

characterization, which are at the current time, according to Brorson, great for investigations and broad surveys of cell lines or raw materials. “What isn’t clear yet, though, is whether they have reached a state where they can be used in a routine QC setting.” FDA expects, however, that the situation could change over the next dozen years or so.

Nucleic acid-based methods

More simple and specific polymerase chain reac-tion (PCR) methods are currently used by many biopharmaceutical manufacturers. Each PCR test accurately detects a DNA sequence from a specific virus and is completed rapidly compared to cell-based assays (e.g., within one day vs. three to four weeks). Presently, however, PCR is not applicable for the detection of multiple viruses at once. Mas-sive parallel sequencing, or deep sequencing, on the other hand, is attracting a lot of interest be-cause it can be used to detect multiple DNA se-quences from different viruses.

In addition to deep sequencing, PCR combined with mass spectrometry (MS) and microarrays are considered advanced technologies for virus detec-tion. PCR with degenerate probes may also be in-cluded as an advancement of PCR, according to Vacante. “These technologies may improve virus detection by enabling the detection of a broad range of viruses, either in an unbiased manner as

with deep sequencing or through the detection of consensus sequences of many or all viruses in a virus family. The assays also by their nature pro-vide information on the virus detected and tax-onomy, including the virus family, subfamily, and genus, which may be helpful for quickly determin-ing where a contamination may have originated,” Vacante observes.

It is important to remember, however, that with these methods, only viral DNA sequences are de-tected, and not actual live particles, according to Kljavin. “These tests do not indicate if any live virus is present, only that a part of the DNA of the virus is present. The challenge then becomes how to respond if a positive result is obtained,” he explains. It is necessary to work backward and run other tests to determine if there is an actual infec-tion. “If no infection is found, then a decision must be made regarding how to proceed. Both industry and FDA will have to figure out how to go forward in such a situation,” Kljavin adds.

Real advantages

Both Genentech and Janssen have employed these nucleic-acid techniques when dealing with possible viral contamination. In 1993 and 1994, Genentech experienced contamination by the rodent parvovi-rus, or minute virus of mice (MVM). In 1993, the infection was detected using cell-based assays, but only after production continued for three to four weeks, thus the facility was contaminated and sig-nificant clean-up and production delays resulted. By 1994, a PCR method was developed, and the virus was detected before harvest from the biore-actor. “In this latter case, production was halted before further downstream processing progressed, and decontamination efforts were limited to the

Massive parallel sequencing

is attracting a lot of

interest because it can

be used to detect multiple

DNA sequences from

(20)

impacted bioreactor, and other normal operations in the facility continued,” notes Kljavin.

A few years ago at Janssen, in response to a sus-pected viral contamination, deep sequencing, and DNA amplification followed by MS, previously referred to as TIGER and now termed PLEX-ID, was used to show that there was no contamina-tion, according to Vacante. “Analysis of the effect observed in cell culture and extensive screening using the advanced tests provided convincing

evi-dence for the lack of a viral contamination or other biological agent,” Vacante adds. Using established standard operating procedures, the impacted lots were then retested and found to be actually nega-tive. The initial test result was then assigned “false-positive status,” and the product was ultimately released to the market (1).

Industry and agency activities

To help evaluate the current status of analytical technology with this goal in mind, a task force of members of the Parenteral Drug Association (PDA) that includes industry, government, and academia are preparing a white paper on emerging methods for virus detection. “This white paper describes both conventional methods and new technolo-gies, including the benefits and limitations of each and their application to biologic drugs,” Vacante

says. He also notes that a PDA interest group was formed to exchange ideas and practices, evaluate these technologies, and possibly develop best prac-tices and standards or standardized approaches for comparison of methods across different laborato-ries. FDA has been involved with both the white paper and the interest group, and Arifa Khan at the Center for Biologics Evaluation and Research has provided leadership regarding the evaluation of these new technologies for virus detection, ac-cording to Vacante.

CDER has also been involved with industry and other players in directed research on standardiza-tion and improved methods for validating viral clearance unit operations. “For example, CDER performed crucial lab work that contributed to the development of the first ever standard nomen-clature for virus retentive filters promulgated in PDA’s TR41, Virus Retentive Filters. We also laid part of the groundwork for ASTM E2888 Standard Practice for Process for Inactivation of Rodent Ret-rovirus by pH, and participated in the committee writing the standard. A challenge for industry is to implement these new standards, assays, and vali-dation approaches,” observes Brorson.

Reference

1. L.C. Hendricks et al., PDA J. Pharm. Sci. and Tech., 64(5), 471-480

(2010). PT

Viral Contamination

Be sure to check out the other ebooks available in PharmTech’s eBook Series.

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tBioprocessing and Sterile Manufacturing tSolid Dosage and Excipients

tAnalytical and Bioanalytical Testing (2013)

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CDER has been involved with

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(21)

Elemental Impurities

S

ince the publication by the United States Pharmacopeia

(USP) of their stimuli article on elemental impurities (1)

and the decision by the International Conference on Har-monisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) to develop a guideline for elemental impurities (Q3D) (2), it has become clear that the impact of the guidelines is not only on pharmaceutical companies but also on their extensive network of suppliers. Previously, there was no need to test drug products or related input materials for anything other than residual catalysts, and the required limits were typically in the range covered by inductively coupled plasma–optical emission spectrom-etry (ICP–OES) or atomic absorption equipment. Heavy metals have

been tested for as a group using wet chemistry (e.g., per USP <231>)

at a limit typically of 10 to 20 ppm total metals. Based on current proposals from USP and ICH, however, many products for which heavy metals data are required by regulators will need to be tested by ICP–mass spectrometry (ICP–MS) as of December 2015. A drug product that fails to comply with the elemental impurities limits and has to be discarded will cost the manufacturing company signifi-cantly more than a batch of excipient or API that has to be discarded or reworked. A final product batch failure may also impact the ability to supply the customer, thereby causing further complications for the business. In this article, the authors discuss the possibility of using a rapid ICP–MS screening technique for acceptance of input materials for drug product manufacturing that does not require full calibration curves or internal standards. Data generated by this method could also be used to support process risk assessments.

Rapid Screening for

Elemental Impurities

using ICP–MS

Jonathan L. Sims and Fadi Abou-Shakra

The official implementation of United States

Pharmacopeia (USP) <232> in December 2015 will require measurement of elemental impurities using inductively coupled plasma–mass spectrometry (ICP–MS). The authors describe a rapid, single-point calibration approach for ICP–MS analysis of raw materials used in drug product manufacturing.

The concept was tested on a range of ingredients used in over-the-counter cold and flu remedies.

Jonathan L. Sims _{is USP}

technical advisor and Fadi Abou-Shakra_{is product line}

(22)

Elemental Impurities

Materials and reagents

Ultrapure deionized water (18.2 MΩcm) from a Purelab Flex water purification system (Elga Lab-water) and ultrapure nitric acid (HNO₃) 60% (JT Baker) were used. Calibration standard solutions for quantitative analysis were prepared by succes-sive dilution of a high purity ICP-multi-element calibration standard (IV Stock 37, Matrix: 7% v/v HNO₃, Inorganic Ventures) to give 1 in 50,000, 1 in 100,000 and 1 in 200,000 dilutions. A calibra-tion standard solucalibra-tion for the Perkin Elmer Total Quant software feature was prepared from high- purity ICP calibration standards to produce a so-lution containing 10 microgram/L of aluminum, arsenic, barium, beryllium, bismuth, cadmium, co-balt, chromium, cesium, copper, gallium, indium, lithium, magnesium, manganese, nickel, lead, ru-bidium, selenium, sodium, silver, strontium, thal-lium, vanadium, uranium, and zinc. Additionally, the solution contained 4 mg/L of iron, potassium, sulfur, and phosphorous plus 10 mg/L of calcium in a matrix of 5% HNO₃. Test samples were com-mercially available laboratory grade materials (Sigma Aldrich) and were prepared in centrifuge tubes (TPP) gravimetrically at a concentration of approximately 2 mg/mL using 5% HNO₃ as dilu-ent. All plastic labware used for the sampling and sample treatment were new and used once only.

Instrument

All the determinations were carried out by ICP– MS. A PerkinElmer NexION 300 D instrument was used with a glass Meinhard nebulizer and baffled quartz cyclonic spray chamber and con-tinuous nebulization. For both quantitative and Total Quant analysis kinetic-energy discrimina-tion mode was used for all experiments with a

helium gas flow of 4 ml/min. Indium was used as an internal standard for quantitative analysis. The method for Total Quant measurement used peak hopping in the following ranges: 9–15, 19–39, 42–210, and 230–250.

Discussion

In this article, the authors compare results ob-tained by conventional ICP–MS assay using an internal standard with those generated from the Total Quant method, which is a software feature unique to the Perkin Elmer range of ICP–MS sys-tems for quantifying up to 81 elements in a sample by interpretation of the complete mass spectrum. Total Quant is used for semiquantitative analysis during method development; it can also be used for a final material characterization. To compare the two methods, a range of samples represent-ing active represent-ingredients and excipients used in over-the-counter (OTC) cold and flu remedies were ob-tained from a research chemical supplier. The test samples were not sourced from suppliers to phar-maceutical firms, and therefore, the data presented do not have any impact on any currently marketed product. These OTC medicines are typically used in high daily doses and, therefore, will have to comply with the oral specification limits for USP

<232> metals. In this paper, the authors refer to the limits proposed in Pharmacopeial Forum 40 (2) for materials useable up to 10g/day (3).

The Total Quant results obtained from a screen of 13 materials are presented in Table I_{(quantitative}

(23)

sigma-aldrich.com/safc

(24)

Elemental Impurities

six metals (ruthenium, rhodium, palladium, os-mium, iridium, and platinum), which are typically expected as residues from catalysis, are not in-cluded as they could not be detected in any sample by either Total Quant or conventional quantitative analysis. In most cases, the Total Quant result is consistent with the quantitative result, although some variability is evident. This variability is be-lieved to be due to the proximity of the detected lev-els to the methods detection limits, which should not be the case as we get nearer to the required USP <232> limits. This assumption is confirmed by the

recovery values presented in Table I_{for a spiked}

sample of aspartame. The Total Quant technique provided an accurate estimate of the content of

the target elements when the specific element was present in the standard and measurements are at concentrations closer to the required levels that a manufacturer will have to meet to comply with the current USP _{<232> proposals. The data suggest that,} in practice, the methodology can be used reliably to identify high levels of impurity in tested products. The reproducibility of the measurement process is shown in Table II_{, in which six replicate}

prepara-tions are compared with six measurements from a single preparation. The data prove that, where sig-nificant levels of elements are present, the sample-to-sample variability associated with Total Quant analysis is no greater than the variability associated with ICP nebulization itself.

Table I: Total Quant analysis of test materials. Conventional quantitative mentod analysis is shown in parentheses; ND is not detected in the quantitative method.

Element Arsenic Cadmium Mercury Lead Chromium Copper Molybdenum Nickel Vanadium

USP limit oral (ppb)1 ₁₅₀₀ ₅₀₀ ₁₅₀₀ ₅₀₀ not

defined 130000 18000 60000 12000

Aspartame 4(<1) 178 (107) 64 (47) 16 (6) 26 (44) 52 (30)

Caffeine (2) 5 (3) 20 (27) 31 (142) (12) 4(56) 3(13)

Guafenasin 26 (15) 15 (18) (38)

Quinine hyrodgen

chloride (HCl) (1) (10) 5 (1) 1 (42) 14 (15) 3(4) (32) 1(14)

Acesulfame-k (1) 9 (<1) 12 (<1) (10) 23 (4) 20 (31) (1)

Sodium Benzoate (2) (1) 3 (1) 175 (77) 67 (62) 17 (23) 21 (65) 56 (2)

Potassium Sorbate (1) (1) (1) 9 (4) 24 (51) 65 (2) 7 (2) 8 (28) 2(<1)

Sodium Saccharin 17 (20) 5 (1) 15 (8) 22 (21) 37 (82) 8 (3)

Sodium Citrate 13 (5) (1) (16) 574 (446) (132) 106 (74) 129 (112) 11 (27)

D Sorbitol (<1) 14 (11) (31)

L Ascorbic acid 1 (<1) (10) 55 (ND) (23)

Paracetamol (1) 24 (13) (33)

(R)-(-)-Phenylephrine HCl (1) (2) (75) 1 (3) 63 (66) 5 (318) 12 (44) 17 (74) 56 (55)

Recovery Check

Aspartame

Recovery spike 383 124 487 231 6703 63692 10195 6949 6409

Aspartame spike

theory 329 109 329 220 5491 54914 5491 5491 5491

% Recovery 116% 114% 148% 105% 122% 116% 186% 127% 117%

(25)

Conclusion

In the authors’ opinion, it is possible to validate a method for pharmaceutical raw materials ac-ceptance testing using a NexION ICP–MS instru-ment with a single-point calibration and Total Quant analysis for compliance with the require-ments of USP <232>. The technique is not an al-ternative for final release testing of drug products for arsenic, cadmium, mercury, and lead but is suitable for other elements specified in USP <232> and ICH Q3D.

The major advantage of using this approach is speed of analysis, because the single calibration so-lution is reuseable for an extended period of time

and will not need changing for different test ma-terials due to specification differences or for com-pliance with other regulations such as ICH Q3D. Additionally, the method screens all elements, and

so will provide an alert for other unexpected con-taminants in raw materials.

References

1. USP Proposed Chapter <233>, “Elemental Impuri-ties—Information,” Pharmacopeial Forum 36 (1), (January–February 2010).

2. ICH, Q3D Guideline for Elemental Impurities, Step 2b version (July 2013).

3. USP, In-Process Revision General Chapter <232>, “Elemental Impurities, Limits (USP 38-NF33 1S),”

Pharmacopeial Forum 40(2) (March–April, 2014). PT

Table II: Total Quant analysis of sodium citrate; ND is not detected.

Element Arsenic Cadmium Mercury Lead Chromium Copper Molybdenum Nickel Vanadium

USP limit oral (ppb)1 ₁₅₀₀ ₅₀₀ ₁₅₀₀ ₅₀₀ not

defined 130000 18000 60000 12000

Wt (mg)

Vol (mL)

Sodium Citrate 1 115 46.1 19 ND ND ND 560 ND 100 135 11

Sodium Citrate 2 111 48.1 17 ND ND ND 565 2 94 127 10

Sodium Citrate 3 111 50.0 18 ND ND ND 582 11 105 135 11

Sodium Citrate 5 88 49.4 ND ND ND ND 608 1 103 135 9

Mean 13 574 2 106 129 11

Std Deviation 7 19 4 10 8 2

%RSD 56% 3% 185% 9% 6% 22%

Sodium Citrate 6 rep 1 17 ND ND ND 573 ND 110 115 10

Mean 12 562 99 127 10

Std Deviation 10 19 9 8 2

%RSD 84% 3% 9% 6% 20%

(26)

Assay Validation

C

ytokines are important mediators that are involved in many different inflammatory responses and immune system reg-ulation roles within the human body, among a variety of different biological processes. Several are key biomarkers involved in a number of diseases, including asthma, Alzheimer’s, dia-betes, and cancer and many autoimmune conditions including lupus, Crohn’s disease, psoriasis, rheumatoid arthritis, and multiple sclerosis. These biomarkers—notably interleukins 1[beta], 2, 4, 6, 8, and 10, plus

granulocyte macrophage colony-stimulating factor, interferon-gamma and tumour necrosis factor-alpha—are commonly monitored by clini-cians in proof-of-mechanism, safety, and efficacy trials.

With so many different cytokines being monitored in a single study, it is important to be able to detect many cytokines in a single process to save time, cost, and the volume of specimens. This process can be achieved using multiplexed detection via Luminex-based technology, enabling biomarker studies to be accelerated. This technology was chosen because of its suitability in terms of reagent availability, sensi-tivity, and the matrix it uses, as reagents from the various platforms behave differently in different situations. But before such a procedure can be used in a real-world clinical setting, it must be fit-for-purpose validated to prove that it gives accurate and reliable results.

Validation study

In this validation study, an analytical method for the simultaneous de-termination of nine human cytokines (IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, GM-CSF, IFN-γ, and TNF-α) in human K2-EDTA plasma was validated. The technique involved the use of a commercial Milliplex MAP kit (Mil-lipore), which uses the company’s human cytokine and chemokine mag-netic bead panel. This panel includes 100 spectrally coded beads with a

Validation of a

Multiplex Bead-Based Assay

Rabia Hidi, Catherine Diot, Sebastien Melin, Jiyhe Jang-Lee, and Alain Renoux

The authors present a validation study of an analytical method for the simultaneous determination of nine human cytokines (IL-1β,IL-2, IL-4, IL-6, IL-8, IL-10, GM-CSF, IFN-γ, and TNF- α) in human K2-EDTA plasma.

Rabia Hidi is director

Biomarkers &

Biopharmaceutical Testing-Laboratory Services, rabia. [email protected]; Catherine Diot

is immunoanalysis team leader–

Laboratory Services,catherine. [email protected]; Sébastien

Melin is immunoanalysis

technician–Laboratory Services, sebastien.melin@ sgs.com; Jihye Jang-Lee

is general manager, Carson;

Alain Renoux is vice-president

(27)

unique ratio of two fluorescent beads, and a sandwich ELISA on the surface of the bead.

To carry out the validation process, first the calibra-tion standards must be prepared in assay buffer, accord-ing to the kit instructions. The validation quality con-trol (VQC) is then freshly prepared in human EDTA plasma, and the non-specific binding and wash plates blocked. Next, aliquots of each standard and VQC sam-ples are added to the appropriate wells, and a volume of assay buffer is added to the blank and VQC wells, along with serum matrix from the kit to the blank and each standard well. In addition, the specified volume of bead solution is added to each well.

Once this is complete, the plate is incubated for two hours at room temperature under agitation. The plate is then washed twice using a magnet to adhere beads to the plate wells, and 25 µl of detection antibodies added to each well. The plate is then incubated for a further hour at room temperature, again under agita-tion, followed by the addition of 25 µl of streptavidin– phycoerythrin to each well, before a further half-hour

of incubation under the same conditions. Finally, the plate is again washed twice using a magnet to adhere to the plate wells, and then 150 µl of sheath fluid is introduced into each well to resuspend the beads be-fore the fluorescence signal in each well is read using a Bio-Plex reader (Bio-Rad).

To run the test, the analytes were grouped based on the dynamic range, as some are present at higher concentrations compared to others, and this would mean having to apply different dilution factors. This grouping was done at the preliminary validation run, with validation quality samples being prepared accordingly, with a calibration range in the assay buffer of 3.20–10,000 pg/mL for each cytokine in the assay buffer, and a suitable range for each of the lower limit of quantification (LLOQ), low, mid, high, and upper limit of quantification (ULOQ) VQC samples in plasma.

Validation samples were tested at five levels, and precision and accuracy both intra- and inter-run were acceptable. The upper and lower limits for each

Table I: Determination of the lower limit of quantification and upper limit of quantification in human K

2-KDTA PLASMA †_.

Biomarker Concentration level Inter-run imprecision (%CV)

Inter-run inaccuracy (%RE)

Mean measured concentration (PG/ML)

IL-1β

LLOQ 6.26 -5.04 11.3

ULOQ 4.76 -4.17 1840

IL-2 LLOQ 15.05 0.00 10.3

ULOQ 3.27 -2.81 1730

IL-4 LLOQ 24.08 -58.33‡ 12.5

ULOQ 5.84 4.05 1540

IL-6 LLOQ 8.27 -10.24 7.36

ULOQ 5.77 -5.37 1940

IL-8 LLOQ 5.35 1.90 10.7

ULOQ 3.49 -5.06 1690

IL-10 LLOQ 8.93 -12.32 12.1

ULOQ 3.64 -12.56 1890

GM-CSF LLOQ 3.74 2.34 13.1

ULOQ 5.56 4.98 2950

IFN-γ _ULOQLLOQ 7.60_3.85 -2.60_-7.69 ₁₅₉₀7.50

TNF-α

LLOQ 5.01 -5.63 13.4

ULOQ 6.57 -8.59 1810

(28)

of the analytes were determined, along with the im-precision and inaccuracy between different runs, as shown in Table I. With the exception of interleukin-4, these were all at acceptable levels.

Short-term and long-term stabilities as well as freeze-thaw stability of the cytokines in human K2-EDTA matrix were assessed during the validation process. All biomarkers were stable for up to three cycles at room temperature except interleukin-1[beta], and all for four hours at 5 °C ±5 °C except for this interleukin plus IL-4. These two were, however, stable for 2.5 hours at this temperature. The long-term sta-bility was also assessed; all were stable for 96 days at –75°C ±10 °C, while only IL-1[beta] was unstable after 124 days of storage at this temperature. In addition, all were stable for up to three freeze-thaw cycles at –75 °C, with the exception if IL-1[beta], which retained stabil-ity through just one cycle.

Dilution linearity testing was carried out to deter-mine whether there was a matrix effect using the buffer or the diluent from the kit. The precision and accuracy on the spiked and diluted samples were both acceptable at the mid-concentration level spiked at 350 mg/mL, as can be seen in Table II with the exception of inaccuracy for interleukin-4 and GM-CSF. There was dilution lin-earity for all the other analytes. In the samples spiked at a high-concentration level, there was good precision

and accuracy across all nine analytes, indicating that the mid-concentration level problems observed with IL-4 and GM-CSF were likely the result of a technical issue during the running of the test.

Conclusion

These results demonstrate that the Nine-Plex Lu-minex assay for the determination of cytokines in human K2-EDTA plasma is validated according to the Organisation for Economic Co-operation and Development (OECD) good laboratory practice prin-ciples (ENV/MC/Chem (98) 17), and the European Union Directive 2004/10/EC. The validated method has subsequently been successfully used to analyse samples from clinical studies, applying fit-for-purpose acceptance criteria that were determined using this validation procedure.

The ability to assess nine different cytokines simul-taneously is a real advantage for those carrying out clinical studies that involve the measurement of bio-markers. Using simultaneous assessment of biomarkers (multiplex testing) significantly simplify the logistics of complex biomarker studies. In addition, significant savings in terms of costs, sample volumes, and time can all be made. The validation process proves that it is an acceptable technique to apply in such studies, which have real relevance to the clinical community. PT

Table II: Dilution procedure in serum matrix from the kit.

Mid concentration level spiked at 350 PG/mL Concentration level spiked at 5000 PG/mL Biomarker Imprecision (%CV) Inaccuracy (%RE) Imprecision (%CV) Inaccuracy (%RE)

IL-1β 4.38 17.81 2.01 -10

IL-2 2.3 1.84 2.91 -22.4

IL-4 4.25 44.83 2.8 -13.6

IL-6 2.85 -3.81 1.45 -9.2

IL-8 2.2 16.59 2.36 -16.2

IL-10 3.56 4.8 3.09 -4.2

GM-CSF 2.86 -39.95 3.47 -18.2

IFN-γ 2.57 24.32 2.34 -18.6

TNF-_α 2.3 23.14 2.05 -5.8

(29)

Data Management

T

he management of analytical data (i.e., acquisition,

analy-sis, storage, retrieval, and ultimate disposition) in mod-ern laboratories should be straightforward and robust, especially because of the maturity of modern computer systems and the applications that run on them, as well as the impor-tance of data to scientific organizations and businesses. In an ideal world, data would be stored in a nonproprietary format that could be read and analyzed by any required software application regard-less of when or how the data were generated. Complete and accurate metadata describing the experimental details and context would be captured and stored alongside the data, and users could locate and retrieve specific data with minimal effort. Unfortunately, this “data utopia” does not exist in modern laboratories—data are stored in proprietary file formats that can, and often do, change with new software versions affecting future readability; metadata are often incomplete, not captured automatically, and prone to errors and omissions; and the effort and time required to locate historical data can be high, sometimes making it easier to repeat an experiment rather than try and find the data of interest. The incompatibility of data formats, inaccuracy of metadata, and difficulty locating data plague the modern laboratory, resulting in inefficiencies, increased costs, and reduced innovation. The problem is not going away. Data are generated every day, and the increasingly networked nature of R&D through contract or partner relationships makes the impact of the problem all the more acute. Furthermore, technological ad-vances in higher throughput, increased sensitivity, and new tech-niques will only result in larger and more complex types of data being produced and consumed, thus compounding the growing data management problem.