Validation in pharmaceutical analysis

The ICH guidelines achieved a great deal in harmonising the definitions of the required validation characteristics and their basic requirements. However, they provide only a basis for a general discussion of the validation parameters, their calculation and interpretation. It is the responsibility of the analyst to identify parameters which are relevant to the performance of the given analytical procedure as well as to design proper validation protocols including acceptance criteria and to perform an appropriate evaluation. In order to fulfil this resposibility properly, the background of the validation parameters and their consequences must be understood. In this part, the general concept of an integrated validation is discussed. The interdependencies to other ICH guidelines and topics during drug development (e.g. impurities and degradants, stability and specification design) must be taken into account to define the required acceptance criteria. Evaluation of the results in order to prove the suitability of the analytical procedure must be based on the specification limits. Important parameters and aspects are discussed for the individual validation characteristics. In the following parts, these parameters will be discussed in detail. Examples will be given for their interpretation in order to facilitate the selection of parameters which are relevant to the performance and suitability of the given analytical procedure.

Author Keywords: Pharmaceutical analysis; Validation; Quality assurance; Acceptance limits; Specification limits

Thermal Validation in the Pharmaceutical Industry

Considerations in Selecting a Temperature Sensor

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The pharmaceutical industry is a highly regulated environment based on research, evidence, record-keeping, and validation. The term "thermal validation" is the process of validating / qualifying equipment and storage facilities to prove that they will create and maintain the temperatures they are designed for.
For those responsible, choosing the right temperature validation tool is decision #1 - and making that choice requires a thorough understanding of different sensor types. This paper will specifically focus on two common sensors: thermocouples and thermistors (see table below).
The following article will discuss the advantages and disadvantages of each sensor, especially as they are used in the pharmaceutical industry. But first, a brief definition of thermocouples and thermistors:

• A thermocouple is made of two dissimilar metals in contact with each other. The thermocouple works by generating a small voltage signal proportional to the temperature difference between the junctions of two metals.
  
  
• A thermistor is a resistive device made up of metal oxides that are formed into a bead and encapsulated in epoxy or glass. As temperature changes, so does resistance, causing a large voltage drop.

The follow table describes the stability, temperature ranges and gives brief details about the differences between thermocouples and thermistors.

	Thermocouple	Thermistor
Temp. Range	-270 to 1800°C (-454 to 3272°F)	-86 to 150°C (-123 to 302°F)
Sensitivity	Low	High
Stability	Low	High
*Time-savings	Lengthy set-up	Minimal set-up
*Sources of Error	Many	Few
*Accuracy	Low	High
Ideal Applications	High temperature oven profiling, Cryogenic freezing	Warehouse monitoring, Stability testing, Chamber qualification, Cooler and Freezer, Monitoring, Lab monitoring, Cold Chain monitoring.

* This comparison looks at a total data logging system, and not just the sensor.

Temperature Range: The Key to Selecting Sensors

Thermocouples offer the widest range of measuring capabilities, which admittedly makes them a suitable choice for extreme temperature applications such as oven profiling and cryogenic freezing.
However, in the range of -86 to 150°C (-123°F to 302°F), thermistors become an option, and for most applications they are the better choice. Thermistors are primary sensors, meaning that they operate independently, without the need for a second reference sensor.
It is important to note that other systems, including thermocouple systems, often use thermistors as the reference sensor.

Data Loggers & Temperature Sensors

The stated temperature range of -80 to 150°C (-123°F to 302°F) is just for the thermistor itself, and not for an enclosed Veriteq data logger. Veriteq data loggers are designed to withstand the range of -86 to 85°C (-123°F to 185°F) meaning that the loggers themselves can be placed in the temperature environment and left there. This makes them an ideal solution for chamber qualifications, stability testing, warehouse, cooler and freezer monitoring.
Veriteq's data logger used in the higher range of 85°C to 150°C (185°F to 302°F) requires an external thermistor probe that allows the connected logger to remain outside the high temperature environment.

Sensitivity: Of Voltage & Signal Size

The term sensitivity refers to the size of signal received in response to a temperature change, and is an important component of sensor accuracy. Thermistors are highly sensitive; in fact the name thermistor evolved from the phrase "thermally sensitive resistor."
Stuart Ball, an electrical engineer and author for www.embedded.com writes that "of all passive temperature measurement sensors, thermistors have the highest sensitivity."
In comparing thermistors with thermocouples, Ball goes on to say: "The voltage produced by a thermocouple is very small, typically only a few millivolts. A type K thermocouple changes only about 40 microvolts per 1°C (1.8°F) change in temperature."
With such a minute voltage to measure, it becomes difficult to distinguish an actual temperature change from noise. Enercorp Instruments Ltd., a provider of thermocouples and thermistors, speaks directly to this issue:

"The voltage produced is very small and amounts to only a few microvolts per degree Celsius. Thermocouples are therefore not generally used within the range of -30 to 50°C (-22 to 122°F)."

The graphs below show the increased sensitivity that a thermistor-based system detects as compared to a thermocouple system.

Stability: How Accurate for How Long?

Thermistors are very stable, which makes them ideal for portable applications such as warehouse and chamber qualifications. For example, Veriteq data loggers can be moved frequently without calibration, and still maintain an accuracy of +/- 0.15°C (+/-0.27°F).
To prove the point, Veriteq recently checked the calibration of 106 data loggers after a year of use in the field. Each logger was checked at the following calibration points: -20°C, 25°C, and 70°C. The results were impressive, showing less than 1% of the points to have any excess drift. Still, Veriteq recommends that data loggers are re-calibrated on a yearly basis.
Thermocouples, on the other hand, are known for low stability, which is why a pre-cal / post-cal is required with every use.

When a Sensor Saves Time: Set Up & Stability

A Veriteq data logger is a system in itself,easy to use, quick to set up and self powered. With on board memory, the data is not vulnerable to loss through power or network interruption.
Each data logger, containing a thermistor, is simply configured to the desired sampling frequency and then placed in the monitoring location. Following the test period, the data is downloaded. The system is very straightforward and doesn't require any stringing of wires. Validation without stringing thermocuouple wires reduces set up time and downtime in a high-traffic environment. The result is a significant time savings.
By contrast, a thermocouple based set-up is often time consuming, especially for high-accuracy applications requiring a pre- and post-calibration. For example, qualifying a chamber with a thermocouple system involves first putting all sensor ends (i.e. the hot junctions) inside a calibration unit and going through the pre-calibration process.
Following a successful calibration, the thermocouples are strung from the central data logging unit, to the chamber, through a door seal, and then taped into various positions. Care must be taken to keep a good seal on the door while minimizing damage to the thermocouple wire.
Once the data collection begins, all thermocouple sensors must still be moved to the calibration unit for post-calibration. Finally, it is not uncommon for thermocouples to fail the post-calibration, meaning that the whole process may need to be repeated.

Sources of Error: Cold Working, Cold Junctions, Calibrations

Being a self-contained unit means that Veriteq data loggers have less error sources to deal with - there are no wiring errors, no cold junction errors, and no errors associated with in-field calibration (see table below).

	Thermocouple System	Veriteq Thermistor System
Physical damage to sensor	"Cold working" degrades thermocouple wires as they are repeatedly bent, stepped on, or shut in chamber doors.	There is minimal risk because the thermistor sensor is protected inside the data logger
Non homogeneity Consistency of thermocouple wire and the environment it runs through	Always present to some extent	N/A
Cold Junction reference error Temperature deviation between cold junction reference point and the actual cold junction; includes accuracy of cold junction sensor	The single largest source of error	N/A
Pre & post calibration errors: Reference transfer calibration error; traceable temperature standard; environmental stability; movement of sensors	In-field calibration introduces many sources of error	Pre & post calibration is not required
Operator Error	High level of knowledge required to minimize errors	Less risk as the system is relatively simple
Analog to Digital conversion	Minor	Minor

Thermocouple systems have numerous sources of error, the most significant being the cold junction reference error. Goran Bringert, of Kaye Instruments, states the following:

"A change in ambient temperature is the most significant source or error in thermocouple measuring systems, particularly multi-channel systems with internal cold junction references"

Accuracy: Give or Take a Margin of Error

High accuracy is critical for temperature validations because of the 4:1 rule, which recommends that instruments be at least four times as accurate as the parameter being measured/validated. Therefore, Veriteq data loggers, with their accuracy of ±0.10°C (±.27°F), can be used to monitor/validate parameters as tight as ±0.60°C (±1.1°F).
As for thermocouple based systems, a leading provider claims to have a total system accuracy of ±0.28°C (±0.5°F). While this may be true from a theoretical point of view, it would require having optimal conditions available.
Other industry experts believe that ±1 to 2°C (±1.8 to 3.6°F) is a more realistic accuracy for such a system, meaning that it could be used to validate parameter specifications of ±4 to 8°C (±7.2 to 14.4°F), applying the 4:1 rule. In any event, very few people dispute the fact that thermistors are more accurate than thermocouples.

Conclusion

When choosing a system for performing thermal validations, the first question asked should be "what kind of sensor is being used?"
Thermocouple sensors should be avoided because they involve a lengthy set-up, numerous error sources, and marginal accuracy. It would be best to restrict thermocouple systems to applications involving very high or very low temperatures, simply because there are no other choices available at those extremes.
In contrast, thermistor sensors are ideally suited to high accuracy monitoring in the range of -86° to 150°C (-123°F to 302°F). The Veriteq thermistor based system is highly sensitive, stable, accurate and easy to use.
Using a thermister-based device for validation eliminates the many error sources associated with thermocouple systems and allows for a much quicker set-up time. In short, you save time, experience less downtime and obtain high-accuracy results.

V Model Validation Process-in the Pharmaceutical Industry - FDA Perspective

Summary
The objective of this paper is share Conceptual clarity while working on Life science SAP projects ( End to end, Solution Rollout, Development & Support etc) and try to take best practices out of this to other domain projects. To bring the importance of Validation, Compliance from Quality System point of view.
Author: Girish Deshpande
Company: Satyam Computer Services Ltd
Created on: 30 December 2008
Author Bio
Girish Deshpande has worked in leading Automobile manufacturing for eight years in area of Quality Assurance and has extensively worked as Senior Consultant in Quality Management, Plant Maintenance, and Document Management System for global clients in Pharmaceuticals giants in Europe, Steel Manufacturing units, Beverage bottler in China from eight years. The aim of this paper is to share V model & validation in Pharma from FDA point of view.
Table of Contents
Introduction ........................................................................................................................................................ 3
GxP Overview .................................................................................................................................................... 3
Key Regulatory Bodies................................................................................................................................... 3
What is CSV (Computer System Validation)................................................................................................... 4
V Model Concept ............................................................................................................................................ 6
Validation Process ......................................................................................................................................... 6
Document Tractability .................................................................................................................................... 7
Conclusion ......................................................................................................................................................... 7
Related Content ................................................................................................................................................. 7
Disclaimer and Liability Notice .........................................................................................................Introduction
The primary aim of this article is to share key concepts while one work with Life science SAP projects in particular to Pharmaceutical, Beverage, and Health care domain. Under stand and implement universally formed model while executing projects. Following are key theme
 GxP overview
 Know Important Regulatory bodies
 V model
 Importance of Validation
 Document Tractability
As most of you know that entire Pharmaceutical Industry (Finished goods, Intermediate products, Drugs & Substance manufacturing) deals with human & animal life, saving human. The pharmaceutical industry undertakes the development, production and supply of pharmaceutical products needed to save lives, prevent disease and otherwise assist in maintaining quality of life.
This industry is governed by Regulatory authorities and lot of emphasis on documentation. There is huge Research & Development investment with long lead time for product to come into market for commercial purpose once regulatory approvals are in place.
GxP Overview
The term GxP means GMP ( Good Manufacturing Practices) „x‟ includes
 GCP ( Good Clinical Practices )
 GLP ( Good Laboratory Practices )
 GDP ( Good Distribution Practices )
The pharmaceutical industry is regulated industry means pharmaceutical. Preparations must be safe and effective for patients & the general public. It must protect consumer. Adhere to GxP for compliance & Proof that any systems and activities are “fit for purpose”.
In nutshell the GMP covers all business functions which are closely associated with business process in major category People who follow certain Processes to make required Products with the help of administrative, Quality, regulatory Procedures & related paper work.
Key Regulatory Bodies
In major continents across globe, we have International reputed agencies who has worldwide presence who acts as Regulated bodies for Pharmaceuticals industry
 Food & Drug Admirations (FDA) –Relevant for US Market mainly
 European Medicines Evaluation Agency (EMEA) –For European Region
 Drug Controller General of India –For IndiaWhat is CSV (Computer System Validation)
 Computerized system validation (CSV) is the documented process of assuring that a computerized system does exactly what it is designed to do in a consistent and reproducible manner.
 The validation process begins with the system proposal / requirements definition and continues until system retirement and retention of the e-records based on regulatory rules.
 System definition artifacts that reflect these requirements can include, but are not limited to, the following:
o User Requirements Specification: What the system needs to do for its user(s)?
o Functional Requirements Specification: How each feature of the system functions?
o Design Requirements Specification: How each feature of the system is built?
o Hardware Requirements Specification: Minimum hardware required to support the system.
FDA Definition: “Establishing documented evidence which provides a high degree of assurance that a specific process will consistently produce a product meeting its pre-determined specifications and quality attributes.” (Source: FDA Guidelines on General Principles of Process Validation, 1987)
Significance of CSV
Main business reason behind CSV is to deliver as per requirements and to have minimum maintenance cost for a computer system. Documentation is one of the most important requirements of CSV. It is important for Pharma Systems to be CSV compliant to:
 Minimize regulatory actions.
 Maintain positive relationship with regulatory bodies.
 Expediting submissions to FDA / other regulatory and faster approvals by FDA.
 Avoiding product recalls and negative publicity.
Key FAD Regulations applicable for SAP Projects
Following are key FDA Regulations which are closely related with SAP Software development cycle.
CFR : Code of Federal Regulations ,Title 21 mainly deals with Food & Drugs published by US FDA
 21 CFR Part 11 ( Electronic Records, Electronic Signature )*
 21 CFR Part 210 (Current GMP in Manufacturing, processing, packaging)
 21 CFR Part 211(Current GMP for finished pharmaceuticals)
* The 11 th sub part is related with all kinds of electronic records & Signature for software project
Refer website for country specific regulatory bodies mentioned in reference...................Audit trail of changes
 What type of changes ( Creation, Modification, deletion )
 What record was & what it is now
 Who did it ( Unique identities)
 When it was done
Electronic Signature
 Irrevocable legal signature
 2 Elements ( User ID and Password)
 Password not viewable ( even by system administration )
Access Control
 User Profile
 Password
 Password encryption
Main Benefits of 21 CFR Part 11 are
 Increased speed of information exchange
 Cost savings
 Reduced data entry and errors
 Improved process control
 More efficient data transmission to FDA for review and approvals

Green Validation: Practical Strategies For Paperless Software Validation

INTRODUCTION
Software validation is a fact of life for highly regulated companies that leverage advanced technology solutions to drive mission-critical regulated business processes. Validation and verification is essential to ensure that these systems meet their intended use and include the proper level of security to protect data and prevent unauthorized access and changes. An essential requirement for all validated systems is that they must be maintained in a validated state over time. This means that validation is a “living” process that requires change over time.

For years, life sciences companies have struggled with the documentation burden associated with software validation. Over the past two decades, there has been much discussion about “paperless” validation. However, the idea of paperless validation as well as other paperless processes has largely been an elusive goal that has plagued enterprise technology. During the early days of document management system deployment, a key driver of these systems was the promise of the “paperless” office environment. After millions of dollars spent on enterprise technology, paper lives on!

Life sciences companies today face mounting pressures to deliver systems with enhanced security, traceability and control to ensure sustained compliance. In addition to these concerns, today's life sciences companies must operate within an environmental, social and economic context where environmental sustainability is a key element of overall business operations. More and more, companies are independently seeking ways to become better stewards of natural resources taking into account the needs of future generations. The overall premise of the “green” economy is to reconfigure business processes and infrastructure to deliver better returns on investments, while at the same time reducing greenhouse gas emissions, extracting and using fewer natural resources, creating less waste. Given this imperative, any improvement in operational efficiency, cost and risk are compelling business drivers to replace inefficient, wasteful paper-based processes with secure, electronic ones. In support of green initiatives, I have been promoting the concept of “green validation”. The term “green validation” refers to a new, more responsible approach to software validation that leverages GAMP methodologies and advanced technologies to promote a paperless validation environment. Now, more than ever, is the time to awaken the vision of green validation and move this strategy from vision to reality.

THE PROBLEM WITH PAPER
There is an old adage in the life sciences community which says “… if its not documented, it didn't happen…” This could explain in part the love affair with paper. Paper is convenient. Most people still prefer to read printed documents in spite of all of the technology we have deployed. Paper is necessary to maintain an audit trail of paper records required by current global regulations. (I am often amused when organizations spend millions on content management systems with 21 CFR Part 11 signatures only to print the paper documents out and sign them by hand.) Yet, what many people don't realize is that paper is EXPENSIVE. Consider the fact that recent studies have repeatedly shown that in most corporate environments, knowledge workers spend up to 40 percent of their time trying to find paper documents. An excessive amount of time is spent searching for and retrieving documents costing billions of dollars of wasted time each year in the US alone. If you consider the fact that according to a recent study, the cost of paper is about .003 cents per sheet. Thus, if a typical life sciences company purchases 10 million sheets of paper annually, the total cost is approximately $30,000. 95% of this paper will have to be disposed of and most will end up in filing cabinets. When you add up the cost of photocopying, printing, faxing, mailing, storage, and disposal costs associated with paper, studies reveal that the costs can skyrocket to nearly $500,000 per year just to manage paper.

As you are aware, validation is very paper-intensive. All initial validation documents and their subsequent changes must be tracked and managed in a controlled manner. In addition, software validation documentation must be comprehensive to support the “intended use” principle. Given the broad range of systems on the market today, one of the main challenges associated with validation is applying a consistent methodology across multiple systems. For commercially-off-the-shelf (COTS) software, this is particularly important. Most COTS vendors offer “validation test scripts” with their solutions. Given the varying levels of understanding of validation among the COTS players, companies must deal with the inconsistencies of the COTS-developed test scripts.

Consider the statement in the guidance for software validation “... computer systems used to create, modify, and maintain electronic records and to manage electronic signatures are also subject to the validation requirements…”

Also, 21 CFR Part §11.10(a) “…Validation of systems to ensure accuracy, reliability, consistent intended performance, and the ability to discern invalid or altered records…”

Beyond compliance, validation can offer significant business value and can be consider as somewhat of a “legal best practice” in providing traceability and accountability within business processes. FDA regulations are very clear in their expectations that organizations must adopt and follow very specific processes and procedures to ensure compliance. It is important to realize that regulations provide guidance and do not advocate the use of any specific technology to meet regulatory requirements. It is also important to understand that the U.S. FDA as well as other global regulations have embraced and even suggest the use of advanced technology to drive regulated business processes. It is a well established fact that many processes including validation are more effective if driven by technology. Paperless systems help to greatly facilitate compliance audits and help to reduce regulatory risk. From a validation perspective, it is time to move to the 21st century to promote “green validation”.

GREEN VALIDATION: PAPERLESS OR “LESS PAPER”?
Validation lends itself nicely to automation. However, when it comes to validation, there is a clear distinction between paperless validation and validation with less paper. Green validation does not necessarily mean “no paper”. Paper is here to stay. It is a reality and a fact of life. However, there are clear business and environmental imperatives for green validation. How is this achieved? The good news is that there are organizations developing validation toolkits and online electronic validation systems that allow you to track and manage requirements and validation protocols online to effectively produce validation document deliverables using an automated approach.

The concept of green validation includes integrated systems with built in validation best practices such as GAMP to drive validation efforts. Through the use of green validation software, you have the ability to apply validation principles and best practices to any validation project in a consistent, electronic manner. At the heart of the conceptual green validation system is a “requirements engine” that provides the ability to define validation user requirements and automate the tracaeability of the validation requirements to the validation test scripts. The automation of validation traceability will go a long way to save time and expense. Green validation software includes electronic workflows, electronic signatures, as well as requirements tracking and test protocol integration to help facilitate validation. Most importantly, green validation systems include integrated risk assessment to ensure that all validation efforts are conducted according to their defined risk.

With respect to validation project management, green validation systems should have the ability to allow validation project managers to track and manage multiple validation projects easily and provide “validation intelligence” or business intelligence dashboard functionality to allow project managers to quickly identify bottlenecks and address them to keep validation projects on time and within budget.

And finally, no green validation system would be complete without the ability to produce, manage, and track validation deliverables in a secure compliant manner. The system would include helpful reminders of key validation due dates and assess the impact of changes to help maintain the validated state.

TAKING VALIDATION TO THE NEXT LEVEL
Some may think why even consider the environment when discussing validation? As we all try to do more with less, it is about working smarter as well as efficient. Validation is a process that cries out for automation. Companies are spending excessively in terms of validating COTS software applications and creating reams of paper in the process. The same goes for custom solutions. In addressing these challenges of inefficiency and expense, it is prudent to also consider the impact on our environment because it is good business. Green validation systems take software validation to the next level. By leveraging advanced technology, companies can use less paper or paperless processes to produce validation documentation deliverables and maintain their systems in a validated state. Validation 2.0 is taking shape. The technology is here, and the time for green validation is NOW.

Drug target validation: Hitting the target

Caitlin Smith¹

Abstract

The route to new therapeutics often ends in costly failure. The secret of success is the rapid and accurate identification of drug targets with true potential, says Caitlin Smith.

David Szymkowski says drug failures can be due to poor target validation.

For the pharmaceutical industry, the Human Genome Project has proved to be both a blessing and a curse. Where potential drug targets were once hard to come by, the industry is now awash with them. This has left researchers with the unenviable challenge of sifting through the data in search of the elusive proteins that are instrumental in human disease.

Akin to seeking a needle in a haystack, this herculean task has boosted the importance of rapid screening technologies. Of the roughly 35,000 genes in the human genome, only a few have known functions. So the task of identifying and verifying a positive lead is key to effective drug development.

Drugs fail in the clinic for two basic reasons: they either don't work or they prove to be unsafe. "Both of these are often the direct result of sloppy early target validation," says David Szymkowski, director of biotherapeutics at the biopharmaceutical company Xencor in Monrovia, California.

Validation is a crucial step in the drug-discovery process. Most drugs are inhibitors that block the action of a particular target protein. But the only way to be completely certain that a protein is instrumental in a given disease is to test the idea in humans. Obviously such clinical trials cannot be used for initial drug development, which means that a potential target must undergo a validation process — its role in disease must be clearly defined before drugs are sought that act against it, or before it is used to screen large numbers of compounds for drug activity.

Deciding to develop a drug against a particular target is a big commitment in terms of time and money. Once a target enters a pharmaceutical company's pipeline, it can take about 12 years to develop a marketable drug. Each new drug that reaches the market represents research and development costs of close to US$1 billion.

"Reducing failures early in development is far more important than filling a pipeline with poorly chosen late-stage products likely to fail, and fail expensively," says Szymkowski.

Model interactions

Purifying proteins for functional assessment at Xencor

Computer models are a fast, relatively cheap option for initial screening of both targets and potential drugs. These models usually focus on how the two types of candidate structures interact with each other.

De Novo Pharmaceuticals in Cambridge, UK, has a suite of software for the process, covering virtual screens, docking programs and ligand-based design.

If the structure of the target protein's active site is known, the company's SiteExplorer can predict potential drug-binding sites, and can evaluate interactions between these sites and the drug candidates. If the structure is unknown, then its Quasi2 software will produce a virtual protein based on molecular features known to be important in binding in other targets. Drugs can then be designed against the model.

De Novo also offers software to aid the design of chemical probes used in target validation. The SkelGen suite of programs can then use these data to generate new chemical structures optimized for interaction with a target's active site.

The company is collaborating with GeneFormatics of San Diego, California, in a programme focused on inhibitors of the M10 family of matrix metalloproteinases, enzymes that are involved in cancer and inflammatory disorders. GeneFormatics is using proteomics to identify the target enzymes and characterize their active sites, while De Novo is running docking models and virtual screens of small molecules against the proteins.

Software that can model drug–receptor interactions is available from a number of companies including Tripos of St Louis, Missouri; Accelrys in San Diego, California; and Metaphorics in Mission Viejo, California. In addition, some software is available free to researchers at non-profit organizations, such as AutoDock 3 made by the Scripps Research Institute in La Jolla, California, and GOLD from the Cambridge Crystallographic Data Centre, UK. Molsoft in La Jolla, California, which makes the ICM molecular modelling software, last month released an ICM browser for the Apple Macintosh.

The Accelrys suite of structural homology programs identifies the possible function, fold family and three-dimensional structure of target proteins by comparing them with sequences and structural homologues of known function. Once the protein's structure is determined, functional information can be gleaned using different modules within Accelrys's Insight II program, which supports a number of processes including X-ray crystallography, nuclear-magnetic-resonance studies and protein engineering.

Target Engine from LION Bioscience in Heidelberg, Germany, aids target selection by offering the ability to analyse gene sequence and expression data, find homologous structures, map potential functional features onto protein structure, view related gene annotation and protein pathway information and use text mining to find functional relationships.

In biotherapeutics, proteins themselves are developed as active drugs. One software suite designed to help optimize protein function is Protein Design Automation (PDA) produced by Xencor. "We don't screen DNA sequences," says Szymkowski. "More specifically, PDA computationally screens massive numbers of amino-acid changes in a known protein structure." It then derives functional information from the three-dimensional protein structure and designs novel features into the protein to optimize its function.

Sense reversal

Xerion's XCALIBUR switches off target proteins by laser.

Another route to target validation hinges on disrupting gene expression to reduce the amount of the corresponding protein, and so identify the physiological role of the target. Examples of this technique include gene knockouts, antisense technology and RNA interference (RNAi).

In the realm of drug discovery, antisense technology — the use of short oligonucleotides to target specific messenger RNAs for destruction — was developed as a way of finding oligonucleotide-based drugs that interfere with gene expression, rather than with protein function. But the technology is currently enjoying greater success as a high-throughput method of target validation because it offers a highly specific and efficient way to inhibit the expression of potential target proteins in vitro and in vivo.

GeneTrove, the genomics division of Isis Pharmaceuticals in Carlsbad, California, is one of the companies active in this field. It is focusing on the untapped pool of potential therapeutic target RNAs for both target validation and drug discovery, says Nicholas Dean, GeneTrove's vice-president of functional genomics. It offers custom target-validation packages that include optimized antisense inhibitors against any target of interest and control oligonucleotides for testing in cell-culture model systems. It also applies antisense technology to target validation in vivo in animal models.

Biognostik, a biotechnology company in Göttingen, Germany, offers a drug-target validation kit that can be used in vitro or in vivo. It includes five target-specific phosphorothioate antisense inhibitors and two random-sequence oligonucleotides to control for nonspecific effects. It has also developed a sequence-design system called RADAR, which determines antisense oligonucleotides based on specificity, minimal nonspecific effects or protein binding, and the ability to be taken up into cells.

Sequitur, a functional-genomics company in Natick, Massachusetts, has a slightly different approach to rapid target validation. It combines an antisense library with high-throughput DNA microarray assays to test the effects of the antisense molecules on gene expression. The company's technology was used recently to validate a major therapeutic target for Alzheimer's disease. Sequitur also carries out target validation based on RNAi (see 'The silent treatment', page 343).

Custom phosphorothioate antisense oligonucleotides for research are available from firms such as Sigma-Genosys at the Woodlands, Texas; atugen in Berlin, Germany; and Integrated DNA Technologies in Coralville, Iowa. Gene Tools in Philomath, Oregon, offers morpholino antisense oligonucleotides, and Danish companies Cureon in Copenhagen and Exiqon in Vedbæk offer modified oligonucleotides based on 'locked nucleic acid' technology that can be used for antisense.

The proteomics approach

One disadvantage of doing target validation at the genetic level is that many genes produce several different protein isoforms, which can have subtly different functions (see 'A question of form', page 341). Post-translational modifications can also give protein variations. As a result, a developing approach in target validation is to focus on manipulating the activity of the potential target protein itself. "As the vast majority of drugs target proteins, validating targets is best done by modulating protein activity, not expression levels," Szymkowski says.

Proteomics — the study and manipulation of the protein make-up of a cell — is making it easier to distinguish and target just one specific form of a protein. This allows researchers to avoid unwanted changes in the expression of other proteins — another potential drawback of genetic manipulations.

Stefan Henning, director of functional biology at Xerion Pharmaceuticals in Martinsried, Germany, agrees that validation at the proteomics level is a powerful approach. "On a technical level, the development of protein microarrays, multidimensional liquid-based protein separation and technologies that manipulate protein expression and protein–protein interactions will have their impact," he says.

Xencor has developed ProCode, which enables researchers to study the functions of a cell's protein make-up. A ProCode library is a protein-expression library from any cell or tissue of interest, in which every protein (after translation) is tagged with a plasmid, a small circular piece of DNA containing its corresponding complementary DNA (cDNA). The library can be expressed in cultures of the appropriate mammalian cells so that proper protein folding and processing are retained. The expressed proteins can be screened for their interactions with potential drugs, and the cDNA tags allow easy identification of any protein that gives a positive reaction.

Xerion's XCALIbur carries out simultaneous identification and functional validation of potential drug targets. Using target-specific antibodies to identify the proteins and chromophore-assisted laser inactivation (CALI) to 'switch off' target proteins by photochemically modifying their functional sites, XCALIbur can validate specific targets for particular diseases or find new potential targets with disease-associated functions.

XCALIbur is incorporated into the Xstream platform, which takes a disease-based approach to target validation. It searches for hits from a suite of antibodies specifically created against the proteome of a diseased cell. The antibodies bind near to functional sites of proteins and contain dyes that are released by CALI, thereby inactivating the proteins' functional sites. If this inactivation has an effect on the disease, the protein is precipitated by the attached antibody and analysed by mass spectroscopy and database searches.

Validation in vivo

One of the most important tests for a potential drug is an assessment of its role in disease in an animal model. But animal models for certain diseases, such as psychiatric illnesses, are extremely difficult to develop.

"The greatest challenge in target validation is the procurement or development of the correct animal models for the human disease in question," says Bob Gordon, De Novo's vice-president of biology. "For example, there are few, if any, reliable animal models for stroke. So validation is effectively done in phase III trials in the clinic. Progress in this disease area is understandably slow and expensive."

In vivo target validation using gene knockouts, in which genes are deleted or disrupted to halt their expression, is a powerful method of predicting drug action. "Many of the targets for the top-selling drugs of the biopharmaceutical industry have been knocked out," says Arthur Sands, president and chief executive of Lexicon Genetics in the Woodlands, Texas.

This kind of target validation is based on the assumption that knocking out the gene for the potential target has the same effect as administering a highly specific inhibitor of the target protein in vivo.

"With the effective use of mouse knockout technology, expensive drug-discovery activities can be focused on the drug targets that are most likely to lead to breakthrough therapeutics," says Sands. Furthermore, target-specific side effects can be discovered before time and money are invested in drug design.

But mammals are not the only creatures in use — zebrafish have recently entered the fray as a model animal for some human diseases. The fish are more affordable, easier to keep, and faster to raise than mammals, giving a higher-throughput system. Drugs can also be tested for toxicity and their potential therapeutic activity against the target more easily than in mammals.

Perhaps surprisingly, genes that cause disease in zebrafish are similar to those in humans, for example in angiogenesis, inflammation and insulin regulation. The transparency of zebrafish embryos also makes them suitable for large-scale, high-throughput genetic and drug screens.

Zygogen in Atlanta, Georgia, has developed a transgenic zebrafish system called Z-Tag which can be used for target validation. The company can also make various zebrafish organs visible by tagging the tissues with fluorescent markers.

One of the most widely used models of human disease is the mouse, but working with mice can be both time-consuming and expensive. Lexicon Genetics has met this challenge by industrializing the generation of mouse knockouts, using gene targeting, gene trapping and mouse embryonic-stem-cell technologies. The result is the company's Genome 5000 programme, which aims to analyse 5,000 genes over the next five years — over 750 have already been done. Custom transgenic and knockout mice are also available from Deltagen in Redwood City, California, and memorec stoffel in Cologne, Germany.

Researchers are slowly but surely making progress in validating the targets revealed by the Human Genome Project. But proving that a target protein has a causative role in human disease remains a real challenge. "The most exciting technologies are, and will be, those that address the issue of elucidating causative roles of targets in human disease, as opposed to simple associations," says Aram Adourian, a senior director at the biopharmaceutical firm Beyond Genomics in Waltham, Massachusetts (see 'A whole picture', page 345).

More challenging tasks lie in discovering the effects of interactions between newly validated targets in both healthy and diseased models. Such complex information will require not only information systems to correlate multiple variables and outcomes, but also a sophisticated knowledge of protein–protein interactions under a variety of conditions. But for now, researchers are taking it one target at a time.

A Risk-Based Approach to Cleaning Validation of APIs

Abstract

Arisk-based assessment of cleaning validation of an Active Pharmaceutical Ingredients (API) facility is reviewed. The potential application of visible residue limits (VRL) in cleaning validation
is explained for both pharmaceutical pilot plant and manufacturing facilities. VRLs are the level down to which API residues are visible to a group of trained observers operating under defined viewing conditions.
The author describes the development of a VRL program in an API manufacturing facility including sample and viewing parameters. The effects of observer distance, ambient light intensity, viewing angle and residue appearance were quantitated and the best opportunities for success were defined. Potential applications of VRL implementation were identified in both pilot plant and manufacturing settings.

Introduction

Information regarding cleaning validation in facilities that manufacture active pharmaceutical ingredients (APIs) is limited (1 - 4). The objectives of cleaning validation efforts in the API area are the same as those in the pharmaceutical production area but the areas are fundamentally different. The API facility includes reactors, transfer lines and pipes, pumps, filters, centrifuges and dryers making cleaning validation more challenging. Although up to 90% of the total equipment surfaces are visible, many of the visible equipment surfaces are not within reach of the operator.
The areas that are not visible often represent some of the worst-case locations in the equipment such as low-flow areas or parallel flow routes. These surfaces cannot be visually inspected without the aid of remote access capabilities, such as a remote video system. It must be decided whether to test these areas either with such a remote video system, dismantle the equipment for direct visual examination, or monitor with an indirect test such as rinse sampling. Rinse sampling is by far the most convenient form for monitoring these remote areas on an ongoing basis.
A validated cleaning program based on quantitative visual inspections in conjunction with swab or rinse testing is possible. Acceptable visible residue limits (VRLs) can be established in conjunction with and compared to swab results. Assuming the swab results demonstrated a validated cleaning procedure, if the results are in agreement, then the VRLs may be used going forward. This is the same argument that has been successfully used to defend the use ofrinse sampling established in conjunction with swab results.
The use of only visual examination to determine equipment cleanliness was proposed as far back as 1989 by Mendenhall (5). He found that visible cleanliness criteria were more rigid than quantitative calculations and clearly adequate. The FDA, in their "Guide to Inspection of Validation of Cleaning Processes," limited the potential acceptability of a visually clean criterion to use between lots of the same product (6). LeBlanc also explored the role of visual examination as the sole acceptance criterion for cleaning validation (7). The adequacy of visible residue limits continues to be a topic of discussion.
Visible cleanliness is the absence of any visible residue after cleaning. Although this is a seemingly straightforward definition, a number of factors influence any determination. The most obvious is the observer. Not only the observer's visual acuity, but also training on what to observe, influences the outcome of a visual inspection. The levels of illumination in the inspection areas and shadows caused by the equipment influence what is seen. The distance and the angle of the observer from the equipment surface also have an effect. Finally, the individual residues that comprise a given formulation affect the overall visible residue limit.
Fourman and Mullen determined a visible limit at approximately 100 μg per 2 x 2 in. swab area (8) or about 4μg/cm2. Jenkins and Vanderwielen observed various residues down to 1.0 μg/cm2 with the aid of a light source (9).
For this study, the visible residue limits of active pharmaceutical ingredients were determined.
Observers viewed residues under viewing conditions similar to those encountered in both a pilot plant facility and a commercial manufacturing facility.

Visible Residue Parameters

Pilot Plant Study
Since the determination of a visible residue limit is, to a large extent, subjective, the variables associated with studying visible residue were defined, and then experimental parameters for the study were established. The parameters considered were: residue, surface material, light intensity, distance, angle, and observer subjectivity (10).

Steam Sterilizer Validation Requirements Per The New Standard ISO 17665-1:2006

For decades, steam sterilization (autoclaving) has been an integral part in the manufacturing, cleanroom, and laboratory processes for the medical device, pharmaceutical, biologics, and human tissue/HCTP industries. It has been a common industry practice to validate steam sterilizers using the published guideline ISO 11134 Sterilization of health care products — Requirements for validation and routine control - Industrial moist heat sterilization,¹ issued in 1994. In late 2006, AAMI released the document intended to supersede 11134, with ANSI/AAMI/ISO 17665-1:2006 Sterilization of health care products — Moist heat — Part 1: Requirements for the development, validation, and routine control of a sterilization process for medical devices.² While other steam sterilizer guidance documents do exist,^3,4 it is anticipated that the new 17665 standard will be recognized by the FDA and will be commonly employed to validate autoclave processes. The good news to manufacturers or other users of these guidelines is that many of the current validation practices are the same in the new document. This article will outline the basic requirements for steam sterilizer validation via the halfcycle overkill method, and list some of the differences between the two documents.

REQUIREMENTS PRIOR TO VALIDATION
The 17665 document makes it clear in numerous locations that the user’s quality system must adhere to ISO 13485:2003 Medical devices — Quality management system — Requirements for regulatory purposes.⁵ So if a user wishes to claim full compliance with the new 17665 steam standard, then their quality system must also be in compliance with ISO 13485, including items such as preventive/periodic maintenance and regular calibration for the sterilizer, documentation, change control, purchasing, etc. When compared with the previous steam document, the new 17665 also has more information on product and process characterization, sterilizing agent characterization, installation qualification/IQ, and operational qualification/OQ. The new document also states more clearly that a fully compliant validation is not just a series of successful halfcycles,but is the full complement of successful IQ, OQ, and PQ.
Sterilization agent characterization will be simple for most users — moist heat/steam at 121 or 132 °C, and cycle selection (gravity, prevacuum, etc.). Process and equipment characterization means defining and documenting items like the sterilizer cycle parameters, products (or product families) to be sterilized, load configurations and limits, placement of biological indicators or chemical indicators (BIs/CIs), process tolerances, and equipment identification. Much of this type of information would be recorded in well-written validation protocols or validation final reports. Biological indicators often use spores of the bacterial species Geobacillus stearothermophilus at a titer of greater than 106per BI, although other species or titers are sometimes used.
The new 17665 document also has more information on IQ and OQ. It defines IQ as “obtaining and documenting evidence that equipment has been provided and installed in accordance with its specification.” Autoclave installations commonly document items such as the sterilizer identification numbers, location, line voltage and amperage, water supply piping and pressure limits, steam line requirements, filtration, chamber size, structure and support, piping materials, software certification, manuals, drawings and documentation, and calibrations (temperature, pressure, and timer). The sterilizer must be installed in such a manner to facilitate any necessary maintenance, repair, adjustment, cleaning,and calibration.
OQ is defined as “obtaining and documenting evidence that the installed equipment operates within predetermined limits when used in accordance with its operational procedures.” Autoclave OQs commonly test or verify items such as cycle operation and programming instructions, safety and alarm testing,error reporting, empty chamber temperature profiling and chamber temperature limits/specifications, air removal testing, leak testing, temperature control anomalies, full cycle full-load temperature profiles (if proposed fullcycle exposure time is known), and determination of any hot or cold spots withinthe chamber.
The product definition and process definition sections of the new document list things such as product specifications, product families, packaging, re-sterilizationissues, package moisture, stability and potency of container products, re-usablecontainer systems, process challenge devices/PCDs, sterility assurance level/SAL,BIs and CIs, and bioburden determination if necessary. PCDs are described asproducts or items that provide a known resistance to the sterilization process.They are commercially available or may also be created from the user’sproduct line by inserting spore strips, spore dots, inoculated threads, etc.into items or locations that are determined to be the most-difficult-to-sterilizeproduct or location in the load.
There are many other activities or decisions to be made prior to or during the IQ/OQ, that are not necessarily detailed in either standard. Items such as:

• Obtaining calibrated temperature recording devices or thermocouples
• Ordering supplies such as BIs, CIs, Bowie-Dick test packs, packaging materials, etc. and noting if adequate laboratory facilities are available
• Determining worst-case validation load and worst-case test product or PCD. The protocol or final report should contain a written rationale describing how the loads and product(s) were selected
• Selecting cycle type: 121 or 132 °C, gravity or prevacuum cycle, etc.; and determining if drying time needs to be qualified
• Is product bioburden testing necessary?
• Is product resterilization to be allowed and what are the requirements for resterilization?
• Is product stability or shelf life testing necessary for the user’s products?
• Does packaging testing or packaging validation need to be included with the protocol?

VALIDATION – PERFORMANCE QUALIFICATION
AAMI TIR #13 states “Sterilization process validation is a documented procedure for obtaining, recording, and interpreting the results required to establish that a process will consistently yield product complying with its predetermined specifications.” For the purposes of this article, the primary specification will be sterility. The performance qualification/PQ or microbiological qualification is a series of tests that establishes that the installed and properly operating sterilizer will process the users desired chamber loads to achieve the specified sterility assurance level/SAL. It must be remembered that the load is part of the validation — that is, if the user makes significant changes to the load at any point in the future — then re-validation may be necessary. The previous ISO 11134 document gave relatively little guidance information and few specifications for conducting the test cycles necessary to qualify the user’s proposed fullcycle exposure time(s). The new 17665 steam document varies little from the previous standard in respect to the minimal PQ information that is provided. The 17665 describes bioburden validation methods and the more commonly used halfcycle “overkill” method. It should be noted that at the time this article was prepared, the proposed guidance document that is to accompany ISO 17665-1 was not yet available. This guidance document may provide more advice on microbiological qualification issues (ISO 17665-2 Sterilization of health care products — Moist heat — Part 2: Guidance on the application of ISO 17665-1). For this article, the general requirements for an overkill cycle PQ will be reviewed.
While many activities are required to complete the PQ, the primary goal for the commonly employed overkill validation is this: the user needs to complete three consecutive successful halfcycles in order to qualify their proposed fullcycle exposure for routine processing of sterilization loads. In our case, successful means all BIs are killed (no growth upon incubation) for the three consecutive halfcycles. If, for example, there was no BI growth for the three test cycles at ten minutes exposure at 121 °C, then a 20-minute exposure at the same temperature would be adequate for routine daily processing, assuming all other aspects or requirements of the IQ/OQ/PQ are successful, documented, reviewed, and approved.
But a description of the PQ needs much more detail than this. Validation protocols vary in format from company to company, but most will capture similar information for the final report. An example of validation protocol and final report sections would be:

• Title page with approval signatures
• Purpose, background information, or general goal(s) of validation
• Scope with more specifics about methods, cycles, facility, SAL, products and load, exclusions, etc.
• References with published standards and company SOPs
• Equipment, supplies, validation loads, BIs, etc.
• Rationale for selection of products, load, cycles, PCDs, etc.
• Procedure or methods (more details on this below)
• Acceptance criteria which list the pass/fail requirements
• Deviation report which lists any unexpected results, with potential effects on the validation, along with accept/reject rationale
• Results and conclusions which assign a pass/fail decision to each acceptance criteria, summarize study, and include any requirements for revalidation
• Attachment which lists any data sheets, diagrams, certificates, temperature records, etc., for inclusion with final report
• Approvals section for final report.

To conduct the halfcycles, the user assembles the worst-case validation test load, temperature loggers, BIs/PCDs, and CIs if necessary. The temperature loggers and BIs are seeded throughout the load to represent various chamber locations, keeping in mind any cold spots or previously determined most-difficult-to-sterilize locations. For small chambers, as few as five or six BIs and temperature loggers may be needed. Ten is a common sample size for many chambers. Large, multi-pallet-sized chambers may require many more samples per run. The sterilizer is programmed for one-half of the proposed full-cycle exposure time. Upon completion of the test cycle, the BIs are immediately removed and incubated, and the test load must be allowed to return to normal temperature prior to starting another test cycle. Temperature recorder data is downloaded and printed immediately to determine if any unusual temperature conditions existed. Information is entered on thedata sheets (data sheets that would have been one of the attachments to the written protocol), and all temperature records and data sheets are retained for the final report. BIs are checked regularly throughout the incubation period, and include positive control (unprocessed) BIs which must show growth. As stated before, all processed BIs must show no growth in order for the validation runsto be considered successful.
Final reports should contain: 1) all sterilizer run data or recorder charts, signed and reviewed; 2) all temperature recorder data, signed and reviewed; 3)all data sheets with BI, CI, or any other test results, reviewed and signed;4) any deviations recorded and investigated, with final disposition; 5) results,conclusions, and discussion; 6) calibration documents for any measuring instrumentsused during the study; 7) the approved full-cycle parameters and acceptable placementlocations for BIs for normal processing; and 8) manufacturers’ certificatesof analysis for any items such as BIs, growth media, growth promotion test cultures,etc. Including digital photographs of sterilizer, load, PCD, etc. can be quitehelpful for an auditor who may be reviewing the report at a later date. The completedfinal report packet must then be routed for review and signed for approval.
POST-VALIDATION
There are still issues to be addressed when all activities seem to have been completed. The sterilizer must be added to a regular and documented calibration program. The sterilizer must be included in a regular and documented periodic/preventive maintenance program. And the sterilizer must be added to the validation schedule for its annual requalification. The user needs to verify that all personnel that will be using the autoclave are trained using applicable operation and safety SOPs. Untrained staff should not be allowed to run the sterilizer. Approved products, loads, cycles, and load limit information must be readilyavailable to all operators. SOPs for daily processing must list all requirements for data that is to be reviewed and retained from the sterilizer runs, with logbook, filing system, or archive for run records. SOPs must also address items such as 1) segregation of processed and non-processed product, 2) storage requirements for processed products if necessary, 3) notification of management or maintenance if sterilizer malfunctions or if recorder chart lists any errors, cautions, or warnings, 4) immediate notification of management for BI test failure, including investigation and product quarantine procedure as appropriate, and 5) resterilization requirements if resteril-ization isto be allowed.
In summary, there seem to be no drastic or revolutionary changes in making the transition from ISO 11134 to ISO 17665. The new 17665 steam document provides more information and more guidance in some areas, while leaving other areas (such as PQ) relatively unchanged. While users would be advised to obtain the 17665-2 guidance document when it becomes available, it is anticipated that manufacturers will not find any great difficulties in applying the new standard.
References

1. ISO 11134:1994. Sterilization of health care products — Requirements for validation and routine control — Industrial moist heat sterilization.
2. ANSI/AAMI/ISO 17665-1:2006. Sterilization of health care products — Moist heat — Part 1: Requirements for the development, validation, and routine control of a sterilization process for medical devices.
3. AAMI TIR No. 13-1997. Principles of Industrial Moist Heat Sterilization.
4. PDA Technical Report #1. Validation of Steam Sterilization Cycles. Parenteral Drug Association.
5. ISO 13485:2003. Medical devices — Quality management systems — Requirements for regulatory purposes.