Most pharmaceutical executives, if asked, would say that their companies work very well across individual functions, I imagine. They would say that no one can develop drugs without thorough cooperation throughout the discovery and development process. After all, they would ask, we have all these interdepartmental teams, dont we?

Indeed they do have those teams, but a team doesnt create respect, trust, efficiency, or productivity by itself. And standing in the way of cross-functional nimbleness are the kings and queens of the pharmaceutical fiefdoms and their loyal subjects. Too often, its my good over the greater good. Its my fiefdom, right or wrong.

While all sponsors eventually get out good therapeutic products, the industry remains plagued by chronic inefficiencies. Clinical development has many sources of inefficiency, and one of them is the failure of the diverse professions involved in clinical research to work together productively on a consistent basis. Certainly there are particular projects, or particular leaders, or particular moments, in which people do get along well. But these are moments, and do not represent standard practice.


Most interdepartmental activities (project teams, process change projects, technology implementations, acquisition teams) show little tolerance for pressure, unexpected events, disagreements, or changes in management direction (in other words, life). We see teams, carefully constructed with the best of intentions, all too frequently dissolve into recrimination, passive-aggressive withholding, and hallway politicking when the going gets tough.

And this isnt just about teams. It is about the very organizational structure of clinical development itself. Obviously clinical development needs physicians, clinical operations staff, CRAs, data managers, software programmers, statisticians, and medical writers. What we dont need is for each group to place its allegiance first to their department, second to their profession, and last to the company trying to improve human health.

Then you have one of the common methods of process adaptation in vogue today: the creation of roles, as distinct from jobsessentially a superset of responsibilities assigned to higher performing individuals without any increase in compensation or diminution of their original responsibilities. By proliferating roles without letting go of profession-based structures, you have double the bureaucracy and double the pressure without really making an improvement.


Organization charts are the language of a company. A company speaks through these documents. It tells us what is important to them and what is not important, what it values, and how well it understands itself. Too often we see companies organizing for failure. The first clue comes when you ask for the organization chart and are told that human resources wont let you see it. We know of several companies where managers cant even see the organization chart of their own department. If this is the case, you know the company language has lost its tongue.

What are common ways that companies organize for failure? Organizing to protect egos is organizing for failure. Organizing to prop up someones headcount to justify their title is organizing for failure. If you cannot achieve at least logical intimacy among functions, much less true interconnectedness, then you are organizing for failure. If you organize around visionaries instead of managers, you are organizing for failure. But one of the most dangerous trends in pharmaceutical companies today is organizational fragmentation.


Warring fiefdoms is one thing. War within the fiefdom is much worse. There is a growing tendency at some pharma companies to respond to process problems by further fragmenting their organization chart into smaller and smaller pieces. The thinking is that professional specialization will somehow inspire higher performance (ironic, at a time when CRA specialization by therapeutic area is nearly universally rejected in favor of regionally based generalists). 

Examples of fragmentation in clinical departments are moves like:

	organizing support functions into their own department.

	breaking up the monitoring function into several specialized jobs.

	breaking up clinical data management into micro-constituencies (programmers, database managers, data managers, data analysts). 

The worst symptom of fragmentation is when the pieces are sprinkled hither and yon in odd ways organizationally.

Fragmentation is so damaging, because when you create a micro-profession you compound the essential problem we are describingthe creation of tribes who define themselves by who they are not. The more tribal we are, the more distrustful and disrespectful we are, by human nature. 

Worse yet, each new fragment (say, clinical site document specialists) has to create its own department. And what does that mean? It has to have its own meetings, its own representative on the interdepartmental team, and its own career path and job ladder. The micro-profession becomes self-fulfilling and self-perpetuating. A tactic designed to innovate roles ends up instead creating yet another principality, with full regalia. In sum, instead of a source of efficiency, it is a cost-generating machine.


This is not meant as a polemic against organizational innovation. Rather, I encourage companies to examine their initiatives in terms of their output. Are objective measures of performance improving? Can managers and workers alike say there is less finger-pointing and more respect?

One method of organizational innovation that breaches borders is to lead with focus. Ask yourself, what is one thing (or two things) which our company most needs the organization (clinical development as a whole) to accomplish in the next two years? Figure that out and organize around those objectives, not around disciplines or roles. If the job of clinical development is to get this drug (or three drugs) to submission, then thats what you need to focus on. If clinical development needs to develop this one drug for sure, and needs to change its processes to electronic trials, then those are the two things you should focus on. Nothing else. Organize around these projects and dont chicken out. 

Ongoing professional development can always be fed by the many ample means of professional education and communication which exist for every discipline. You dont need to re-create that in your company; organize around what you are trying to do, not who you are.

If people are organized around a sense of purpose, and only so, you are likely to see much greater success because people need to learn to trust and respect each other in order for the work to get done. Imagine if Major League Baseball was organized by position: all the second basemen in one department, the catchers in another, the third base coaches in another. And each day they were asked to come together as a team and win a ballgame. Thats what we try to do every day of the year.

Aretha Franklin was the Queen of Soul. The keys to her kingdom were R-E-S-P-E-C-T. If we all follow Arethas way, avoiding mistrust and fragmentation, then maybe all of clinical development can be one productive land, and even a nice place to work, combining professional and corporate success.            

Articles

Process Improvement

Interdepartmental politics can suffer from competition and mistrust, but for clinical trials to be truly efficient these obstacles need to be replaced by respect and purpose.

My Fiefdom, Right or Wrong

Feature Article

Information Showcase

Many observers of the computer revolution have noted that old concepts and ideas are frequently reborn with a twist, and relabeled new concepts. For example, the Internet phenomenon is to many simply a return to the dumb terminal days when computer operators used terminals that were little more than television screens to access large computers located elsewhere. This month we look at two related and new examples of this rebirth phenomenonone that some say may be as important as the Internet itself, in the long run. In fact, these new trends may eventually have an impact on clinical trial data analysis. The new concepts are called grid computing and utility computing. To understand them, we must first review what has come before, specifically the notion of time-sharing.


In a now famous paper written in 1965, Gordon Moore (co-founder of Intel) noted that the effective computer processing power had been growing exponentially and was likely to continue in that direction for some time. (An online copy of the original paper can be found at ftp://download.intel.com/research/silicon/moorespaper.pdf.) Remarkably, his observation of exponential growth from 1965 has remained true, with an overall doubling period now estimated at 24 months. This means that the top of the line workstation you purchase today with a 3.06-GHz Xeon Intel processor will be surpassed by a 6-GHz processor when your kids are going back to school in 2004. Over the years whenever theoretical barriers loomed that threatened this relentless march, computer scientists would develop new methodologies of chip development that would allow computer chips to contain more and more raw processing power.

Computers were very different back when Moore first wrote about them. In 1965, IBM had just launched the IBM 360, an enormous computer housed in rooms larger than a gymnasium. The gigantic IBM 360 computer had less processing power and memory than todays Palm Pilot.


Despite the relatively primitive nature of a computer in those days, a networking phenomenon arose to unleash its potential. In the 1950s and early 1960s, mainframes were expensive, difficult to maintain computers that could process only a single job at one time. The computer was a shared resource for many individuals. The most common method of sharing was to run batch jobs that occupied the entire processing power of the computer until they finished. An operator would be able to prioritize jobs in a queue, and kill jobs that threatened to crash the computer.

Many computer tasks could not be run in batch mode, because they required interactive user input. For a trivial example, consider the original adventure computer gameAdventure (for a full history and downloadable, PC-based copy go to 

www.rickadams.org/adventure/a_history.html

In this game, the computer presents a description of a location inside a cave that requires one of a few possible responses. After a 10-second pause, the player types an answer, the computer outputs a response, the player answers, and so on. In fact, computer calculations occupy the minutest fraction of actual elapsed time in this and other software. A 12-hour session (not much for Adventure fanatics) of Adventure used a trivial amount of the computers processing power (measured as CPU time), but required sole access to a hugely expensive resource for half a day. In addition, the computer processor sat idle during the loading of data, printing of results, and other taskswhile people waiting to use the computer lined up.

The answer to this conundrum was to somehow share the computer so that many users could run programs during the time that the computer was waiting for a response or loading data. A concept known as time-sharing was developed to provide a continuous, smooth experience for multiple users on a single computer sharing the idle time in each others jobs. Time-sharing, and its related network structure, was revolutionary in many ways. They made it possible for multiple users to access a computer at a distanceeach user could sit at a terminal attached to the mainframe by the network and use the computer. Furthermore, users could work with the computer interactively by telephone, using a modem. The modem in those days used the speaker and earpiece of the telephone to pass audible signals back and forth between a remote computer and a local terminal.Time-sharing evolved from a concept in 1959 to reality in 1964 when it was launched at Dartmouth University on May 1. Within a few years, the Dartmouth time-sharing computer was being used nationwide at high schools offering computer science classes. MIT and Bell Labs soon followed with a mainframe time-sharing system called the Multiplexed Information and Computing Service (Multics). Companies soon began to sell time on time-sharing computers for commercial uses as well.

Computer folks often speak of CPU (central processor unit) time as cycles, referring to the cycle time of the processors clock. What time-sharing did was to use the wasted cycles of the mainframe computer by distributing it among other users. In effect, time-sharing provided a computing utility for those who couldnt afford to have their own computer. This is not unlike what the electric company does for those who cant afford to own their own power plant.

Those with a business orientation might be wondering how Dartmouth and others charged the various users for the computer. Actual elapsed time was no longer a relevant measure, so the time-sharing computer owner charged by the processor CPU time used. Each user received a monthly bill listing the dates and times of their CPU usage, along with a charge. This was the beginning of utility computing.


Three parallel trends in computing began to converge to shape the progress of the computer revolution. The first trend was that of the machines themselves. Time marched on from those original mainframes to minicomputers and eventually to the personal computer. The second trend in computing was networking. In parallel with the development of computers, networking of computers began to progress from terminal-computer connections to interconnections of computers within an institution to dedicated, direct, inter- and intracontinental computer connections. Eventually, the Internet was developed, first for military and academic uses (ARPANET, CSNET, BITNET), and later expanded for public use. 

The final influential trend in computing was the evolution of software. Software was first designed for use on a single computer, typically a mainframe and later a personal computer. The software was initially used directly at the terminal, but in the case of mainframe and minicomputers it was eventually used at a distance through terminals. With the development of the personal computer and workstation computer came the concept of client server software. In this model of software, a central server program (typically with access to a data store) awaits requests from multiple client programs distributed across a network. The client programs initiate a transaction (say, data entry and data analysis) and the server program performs an action (say, storing or retrieving the data). Client server programs made use of the computing power of the networked workstation while providing for common, centralized access to data. Because data stores were often far beyond that found on workstation computers, client server programs used the strong points of the local and central computers.

A good example of a client-server program would be Microsoft Outlook in a large company. The overall email storage is typically performed by Microsoft Exchange, but the email is viewed, forwarded, or replied to by the client Outlook software on each individuals machine. 

With the advent of the World Wide Web, the client server model is being replaced with the Web browser. The evolution of powerful, low-cost servers and the cost of supplying, updating, and maintaining client programs gradually led back to a centralized application/ centralized data store. Now, the Web browser acts as a common client for many different programs. More than a dumb terminal, the Web browser provides a standardized, sophisticated viewing and manipulation tool for working with centralized applications and databases. For example, a Web version of Microsoft Outlook provides most of the functions of the Outlook client, but requires no local software other than a Web browser. This characteristic enables universal accessemail can be checked in airports and business centers at a moments notice. Most notably, the Web browser requires minimal local application maintenance and provisioning costs.


The current buzz in computing is grid computing, which is in some ways a return to the days of olde. Predictably, the sophistication of computer analysis and software has increased substantially and offers the ability to attack very computationally intensive problems. Models for analyzing these problems are very sophisticated, but they require massive amounts of computer memory. As with many problems, the individual steps in the computations can be performed in isolation. Therefore, it is possible to distribute these computations among several processors on the same computer (so-called parallel computing). Better yet, the computations can be distributed among several or even many computers. 

Grid computing is a concept involving the coordinated cooperation of many computers in a single effort or problem solution. The use of the term grid is a reference to the electrical grida complex maze of power supply and transmission lines through which power is distributed to users. Similarly, grid computing involves the centrally controlled distribution of a problem to a number of computers. In grid computing typically each computer works on a piece of the problem, using spare processing cycles when idle. Alternatively, the grid aspect can involve data storage on many distributed systems. In many circumstances, both distributed storage and computational processing are involved in a grid system. When a given section of the problem is complete, the distributed computer uploads the solution to the central grid controller and receives another piece of the problem to work on. 

There are a number of different models for using grid computing, ranging from tightly managed to open. Tightly managed grids consist of computers on a corporate local area network. Proprietary information would never leave the LAN, and the project could be closely monitored. The most open grid would be one where computers from anywhere in the world might participate, with no particular affiliation. Examples include the Search for Extraterrestrial Intelligence (www.seti.org), the search for the next largest Mersenne Prime (

), and the several anthrax and smallpox drug design projects (some of which have been made an option on the Google toolbar). Grid projects are also underway in which a consortium of companies participates on a particular project, sharing their spare cycles. 

Grid computing shares a great deal, philosophically, with time-sharing. Time-sharing allowed the sharing of a single, expensive resource among many users by maximizing the usage of CPU cycles. Grid computing is emerging today because, for computationally complex or data intensive problems, network bandwith is relatively less expensive than processing capacity. An alternative to grid computing for these problems would be leased time on supercomputersan idea that has also reappeared. These concepts all share the common need to gain access to significant computer processing power on demand (a slogan that IBM has adopted in their recent advertisements).

Grid computing has significant appeal for a number of different reasons. First, grid computing makes it possible for a corporation or consortium to work on a data and computation intensive task that would typically take months to years to solve, and complete the solution in days to weeks. Secondly, the grid-computing concept allows companies to maximize the use of their rapidly aging assetstheir networked computersby allowing them to work on grid-based problems when they would otherwise be displaying a screensaver.

Although grid computing is still in its infancy, a number of pharmaceutical companies have begun to use this methodology in drug discovery. These include problems around analysis of protein folding, receptor-ligand interactions sequence alignment, gene identification, gene homology, computer-aided drug design, high-throughput screening, molecular modeling, gene and protein expression mapping in health and disease, and combinatorial chemistry.

Although grid computing emerged from academia, commercial enterprises have jumped into grid computing, providing technology and know-how to customers. Some have created new business model for this, around the concept of utility computing.


Utility computing involves the use of computer processing power and data storage on demand and, typically, pay as you go. Large companies like IBM, Sun, and HP have vast capabilities of computers, data storage, and networks that are frequently underused. Those companies can sell that capacity and the use of software programs to other companies through a utility model. Much as we pay our water or electric charges on a pay-per-use basis, utility computing would provide enterprise level computing infrastructure to anyone, at the exact moment they needed it and for the time that they needed it. For projects that require occasional, intensive bursts of computational or data storage capacity, the utility computing model can provide it for them.Utility computing is really a back to the future concept. Like grid computing, it is very similar in philosophy to the time-sharing mainframe, although more complex to manage. The utility computing infrastructure needs to be able to accept jobs, distribute the work among an array of computers, collect the results, calculate charges, and possibly distribute paymentsall with minimal human intervention.

Is grid and utility computing relevant to clinical trials? Generally, the computational power required to analyze clinical trials may require short periods of intense computer use (analysis that can run all night on a server, for example). The effort required today to set up a grid-computing project is too large for this kind of computing. However, it is likely that setting up and managing grid projects will become easier and more direct. Software has been developed that can manage the distribution of a grid computing problem to many different computers. One can imagine a time when setting up a grid computation will be no more difficult than doing the same computation on a single computer. In addition, we are beginning to ask more sophisticated questions of clinical trials. As we consider adaptive trial designs, group sequential analysis, computerized trial simulations, and in silico drug testing through organ systems and whole body simulations, it is quite easy to see how the demands for processing power may begin to enter the grid arena. Pharmacogenomics is another area where linkage between SNPs and pharmacodynamic responses in populations may require massive, sustained efforts that can best be accomplished through grid computing.

Again, many of these uses will require long periods of standard computer usage, punctuated by intensive periods of computational complexityan ideal scenario for utility computing.

The vision of many in grid computing is that eventually all users will have access to a gridavailable whenever neededthat would provide a utility-based supercomputer capability for complex problem solving. So, next time you sit down at your PC, remember that it could become a part of a massive network of computing power, for sale to those who need it.            

Technology Viewpoint

Two of the latest concepts in computing are new twists on old ideas?which could be the eventual path for clinical trials data processing.

What?s Old Is New Again

The European Union knows how important clinical trials are both to the health of patients and to the health of the pharmaceutical industry in Europe. So the last few weeks have seen intense European regulatory activity both at strategic and tactical levels in a bid to ensure that patients can continue to benefit from high-quality medicines from a competitive and innovative European industry.


At the strategic level, senior European Union officials came out in early July with what is intended as an evolving document for the future of the industry. The document is grandly titled A stronger European-based pharmaceutical industry for the benefit of the patienta call for action.

 This represents the outcome of two years of reflection on a dilemma that goes back much further. The question is how to promote private industry medicines innovation without bankrupting public social security agencies? Or from the other perspective, how to keep spending on medicines in Europe within reasonable limits without killing off European pharmaceutical research? 

To say the EU has found a complete solution to the problem it perceives would be false. The underlying tensions in Europe, where each member state holds its own purse strings for spending on medicines, while the EU tries to establish an industrial policy, continue to baffle the brightest minds in Brussels (and beyond). 

But to say that the EU has made no progress at all in its thinking would also be false. The document contains further evidence of a growing consensus within Europe on the merits of medicine research, and the need to prevent medicine research from relocating abroad. It firmly states In order to stop the process of erosion, Europe must act now if it is to retain its attractiveness as a location for industry in the years to come. 


Specifically on clinical trials, the document unequivocally recognizes, in a section headed Incentives for Research, that clinical trials are critical to pharmaceutical research. They are vital to public and health and represent a considerable investment for the pharmaceutical industry. It notes that the specially appointed expert group that has been carrying out these reflections for the last two years (known as the G10, because it consisted of ten key representatives of member states, the pharmaceutical industry, and the national health care agencies) has rightly stressed the need for better co-ordination between member states on clinical trials.

The paramount consideration in trial design must be the well-being of subjects, the document goes on. But there is scope for better European coordination, for simplification and harmonization of the administrative procedures governing trials, it accepts. The regulatory framework on clinical trials needs to be adapted, it states.Some of this adaptation is already under way, of course. The new EU clinical trials directive, as the document acknowledges, contains a provision setting up, for the first time, a European clinical trials database, to help communication between regulatory authorities to enable them to improve their oversight of trials and provide for enhanced protection of patients. 

And much has already been achieved to ensure that the EU facilitates trials where the potential pool of clinical trial subjects is small, the document claimsciting work carried out or in progress in particular with orphan medicines and for pediatric indications. The incentives to produce orphan drugs (including 10-year marketing exclusivity, fee waivers, and provision of scientific advice) have generated 140 designations for new orphan medicines since the entry into force of this scheme in 2001. 


But the truth is that there are still almost insuperable limits to what the EU can do to improve the situation significantly. Because the fundamental problem is that most EU member states keep drug prices (or reimbursement levels) very low, industry is starved of funds for new drug development. And as long as the member states retain this competence (and they show no signs of readiness to cede it to the EU), the EU can do little more than offer pious expressions of hope that member states should take a more generous view of drug pricing and reimbursement. Member states have clear competence to take national measures in order to control healthcare expenditures, the document candidly admits.

On the basis that half a loaf is better than no bread, the affirmations of the value of clinical trials and of pharmaceutical research have been immediately welcomed by the European pharmaceutical industry. There has also been a more muted welcome for the expressions of good intention on areas more susceptible to EU interventionsuch as speeding up assessments of applications for marketing authorizations, promoting virtual institutes of health to stimulate and organize health and biotechnology research in Europe, and raising the concept of a European center for disease prevention and control.


Another part of the half a loaf, as far as clinical trials are specifically concerned, is the range of EU activities, now underway, aimed at making tactical improvements to the conduct of clinical trialsfor the sake of the patient, and for the sake of the clinical trials sector itself. Unfortunately, not all these tactical exercises are necessarily seen as beneficial by the clinical trials sector.


Take, for instance, the current efforts of the European Agency for the Evaluation of Medicinal Products to boost the profile of its inspections sector. This department is responsible for coordinating the verification of compliance with the principles of good clinical practice (GCP), good manufacturing practice (GMP), and good laboratory practice (GLP).

The sectors tasks include coordinating any GMP, GCP, or GLP inspections requested by the Committee on Proprietary Medicinal Productsthe EMEAs senior scientific bodyin connection with the assessment of marketing authorization applications or related assessment procedures. In a new presentation of its inspectorate function, the EMEA explains that inspections may be necessary to verify specific aspects of the clinical or laboratory testing, the manufacture and control of the product, or ensuring compliance with GMP, GCP, GLP, and quality assurance systems.

A widely held view within the clinical trials community is that better EU coordination of inspections could improve the way trials are inspected, by standardizing the approach in the most professional wayand thus eliminating some of the national variability that can plague an internationally conducted trial. But the optimism is balanced by an equally widely held fear that the exercise contains a risk of compounding rather than clarifying the approach of inspectors.

So the clinical trials community is watching closely to see what the out-turn is as the EMEA sector organizes and chairs regular meetings of European Union GCP and GMP inspectors. The sector is involved in coordinating GCP inspections for the EUs centralized procedure for obtaining marketing authorizations. And through the work of the GCP inspections services group, which focuses on harmonization and co-ordination of GCP related activities at EU level, the sector helps prepare new and revised guidance on GCP topics, coordinates advice on the interpretation of EU GCP requirements and related technical issues, and helps develop EU-wide procedures relating to GCP inspections. The GCP inspections services groupwhich the EMEAs inspection sector chairsmeets four times a year, with representatives of the GCP inspectorates of Switzerland, Iceland, and Norway; observers from the central and eastern European countries (eight of which will become full EU member states next May); and representatives of Collaboration Agreement of Drug Regulatory Authorities in European Union Associated Countries. As to the effectiveness of these efforts, the jury is still out.


Again in a bid to make life both easier for the industry andin the longer termsafer for patients, the EMEA has also just set out in some detail the way it charges for its services in assessing marketing authorization applications, including conducting inspections of good clinical practice. The guidance is limited to applications through the centralized procedure that the EMEA operates. It does not cover routine GCP inspections of clinical trial sites initiated by the competent authorities of the member states themselves, who make their own arrangements for reimbursement with the company concerned.

The EU rules specify a flat-rate fee for each inspection, plus travel expenses incurred by the inspectors for inspections conducted outside the EU.

 But it is possible that more than one inspection is requested by the authorities in the context of assessing a single application, and the applicant is then liable for more than one inspection fee. The EMEA clarification, in particular, concerns how to determine what constitutes a single, distinct inspection, and thus how the total of inspection fees is calculated.

A single inspection, says EMEA, is one that covers a particular clinical trial activity relating to a product for which an application has been made, carried out at a specific clinical trial-related site, and conducted on a specific occasion. Any other inspection concerning any additional clinical trialrelated activity and/or site is considered to be a further, distinct inspection, even if it relates to the same application.

To make it absolutely clear, EMEA also points out that a single responsibility or set of directly related responsibilities involved in the conduct of clinical trials constitutes a single clinical trial activity. A physical location that contains one or more clinical trial facilities (in a separate building) at the same address constitutes a single clinical trial site.

Although no one wants to pay for inspections, they are a necessary evil. At the very least, knowledge of where some of the costs are to be incurred should help in planning the financing of clinical studies.


The European Forum for Good Clinical Practice (EFGCP) is continuing to make sense of another important tactical exercise now under way: the European Commissions guidance documents in support of the EU Clinical Trials Directive (2001/20/EC), which have recently been finalized (see this column, 

EFGCP has been exploring partnerships for implementing the directive, at a meeting in Brussels in June, in collaboration with the European Cancer Managers Research Forum, the European Commission, and the European Organisation for Research and Treatment of Cancer. The EFGCPs aim is to get all parties involved in European clinical research to establish a shared platform for the implementation of GCP, both at European level, and in the 15 current (and ten future) member stateswhich are supposed to have introduced the directives provisions into their national legislation by May this year, so the directive can be brought into force in May 2004. EFGCP wants to make sure the new rules create a competitive and quality based European clinical research framework that guarantees the best in medicinal development for public health and Europes citizens. 

As EFGCP points out, particular focus needs to be placed on clinical trials and translational research, connecting European academic excellence with innovative research-based industry. This first EFGCP step in building partnerships of this type was intended to focus on the coordination of the implementation of GCP in cancer research, across European research centers, and across sectors. 

But one of the central questions raisedand still not answeredis how efficient clinical trial authorization processes that protect potential research participants while ensuring the efficient development of medicines can be implemented in Europe. The entire sector remains anxious that the way the EU member states put the rules into effect will not make it easier to conduct international trialsand could still make them harder. In tactical terms, the next year, as the member states adapt their national rules, is going to demonstrate whether those anxieties are justified. And in more strategic terms, the next decade is going to reveal how far the EUs attempts to boost EU medicines research manage to keep the industry alive and activeand able to supply the new drugs patients need.


1. Communication from the Commission to the Council, the European Parliament, the Economic and Social Committee, and the Committee of the Regions, July 2 2003 (soon to be published in the 

2. Council Regulation (EC) No 297195 (as amended) Articles 3 (4) and 5 (4) (human and veterinary sectors respectively), as amended by Council Regulation (EC) No 2743/98.            

View from Brussels

The EU has nailed down its strategy for strengthening its clinical trials industry, but it still isn?t clear how it will meet those goals.

Strategy and Tactics for European Clinical Trials

Responding to enormous pressures to shorten time-to-market and reduce overall R&D costs, pharmaceutical companies have been making significant investments in technology. Reliance on technology to speed clinical trial data collection and analysis is growing. Increasing use of technology and FDAs increased regulatory scrutiny make it critical to comply with 21 CFR 11 requirements when creating, using, and maintaining electronic records and signatures.

This article will specificaly discuss the issues faced when addressing 21 CFR 11 for clinical trials datathat is, how to secure and manage clinical trial data in a manner that requires no changes to workflow and is unobtrusive to personnel working in clinical research, biostatistics, and regulatory affairs. The real-world case study analyzes the way a mid-tier biopharmaceutical company implemented a standardized solution to secure their file-based data.


Before 21 CFR 11 became effective, clinical data was simply recorded and maintained in accordance with predicate rulesin this case good clinical practice (GCP). The process was generally paper-based, with forms for recording subject data. These forms would ultimately be archived and maintained as original records. As the use of technology grew, it became common to transcribe this data and store it electronically in the form of data files. While the data capture and subsequent retention process was usually done in a controlled manner, it would not meet the stringent requirements imposed by 21 CFR 11. Thus, the Electronic Records, Electronic Signatures regulation motivated many companies to revisit the way data is generated, collected, recorded, reviewed, approved, and stored.

As part of this analysis, companies have realized that they possess an amazingly complex clinical trials technology architecture spread across clinical sites, contract research organizations, clinical laboratories, and sponsors. Although many people assume that most data exists in secure, large-scale relational databasessuch as electronic data capture, clinical data management, and adverse event systemsthe fact remains that the majority of electronic subject data continues to be file-based. This stems from a variety of factors, such as the continued use of legacy systems that have an underlying file-based backbone, statistical analysis programs that rely on file-based queries and reports, paper-based CRFs that are subsequently scanned for ease of information transportability, and the need to transfer data between noncommon systems, using a common transport vehicleflat files. 

The abundance of file-based data complicates the move toward compliance because files by their very nature are designed to be easily accessible to users and applicationsa concept that runs counter to the 21 CFR 11 requirement of tight controls on the security and accessibility of data. Compounding this problem is the fact that electronic data files are used for different purposes in different ways by different groups throughout the clinical trial process. This requires a careful balance between the needs of the business and the requirements of the FDA.


An additional challenge in controlling data that exists in the form of a file is the wide variety of locations where these electronic records exist so that both humans and systems have access to them. For example, many companies import the bulk of their subject data into a clinical data management system (CDMS) from an electronic data capture system (EDC), leveraging file-based extraction and manipulation tools. The files may be stored locally without version control. The biostatistics department may then use additional file-based analytical tools (SAS, Excel, or custom-developed) to process and analyze file-based subject data that then been extracted from the CDMS. These files are usually copied to unprotected working folders on either a local hard drive or a file server. Following this highly regulated analysis phase, report files need to be managed consistently with the 21 CFR 11 regulation combined with numerous other file-based reports that are part of an NDA submission. Each of the files requires the appropriate controls, including

	Audit trails that record any modifications throughout the entire life cycle of the file

	Maintenance of previous versions of files

	Storage of files in a controlled environment throughout the entire records retention period. 

As a result of the number of ways that these clinical data files are analyzed and manipulated, many firms began their quest for compliance by mistakenly looking for technology to solve individual problems. The solutions often either address specific parts of the regulation or focus on a specific component of the data files life. Because vendors of commercial software frequently address compliance for data that exists withinbut not beyondtheir applications, implementing point solutions may introduce add-itional regulatory challenges such as multiple copies of records, incomplete audit trail information, and security loopholes. At best, the result is a number of 21 CFR 11 point solutions with large gaps between them.

People who address compliance throughout the entire life cycle of this critical data should reach the logical conclusion that the regulation requires that they eliminate, or at least minimize, all windows of opportunity that permit tampering with data. In fact, failure to address the continuous protection of data may be worse than failing to address the regulation at all, because it doesnt provide end-to-end compliance traceability and can lead to a false sense of compliance security.


A specialty pharmaceutical company asked us to help make their clinical trials data 21 CFR 11compliant. To that end, we found their data handling to be typical of many organizations.


	Their subject data was a collection of data files that were generated, analyzed, and maintained by various processes. The data files included SAS program files, SAS data sets, Excel exports, PDF reports, XML interface files, and configuration files.

	While looking at their processes to determine regulatory priorities, we quickly learned that they didnt want to change either the way they were working or the software they used to analyze their data.

To ensure that the pharmaceutical company could leverage its existing software and processes and, at the same time, secure regulated file-based data for its entire life cycle in accordance with the regulation, we needed to implement universal and centralized storage to allow efficient access to all types of files.

Our analysis led us to implement a solution that consisted of a centralized database with the characteristics of a file server. That approach allowed us to address compliance by using a single repository throughout the entire life cycle of the recordand it enabled the company to retain its existing software, procedures, and data in its original format. That eliminated the need to contend with copies of files residing on local hard drives. The solution included the following features: server-based installation, centralized Oracle database, and zero footprint client computer access.

 All software components reside on a common application and database server; all file transactions use existing data transport protocols. Server-based installation also allows implementation and use without modifying or disrupting existing infrastructure and processes.

 All files and metadata reside in an Oracle database. This enables optimized and enhanced search functions, and it provides functionality necessary to support the regulatory requirementsfile versioning, audit trail capabilities, and complete life cycle protection, including archiving.

 No software is installed on any client computer, eliminating many traditional software installation concerns. It also streamlines the configuration of source applications, which reduces the need for revalidation. 


To ensure the successful deployment of the solution, we used an inventory of existing data and software to build an implementation plan that provided an overall picture of what needed to be done and how to do it. 

Although the scope and detail for any project will differ, the categories below are a representative sample of the steps to be performed during the planning and implementation process. 

 As with any new process or technology, it is important to understand and document the expected outcome. Because the desired outcome of 21 CFR 11 compliance has been adequately defined for many years, previously developed requirements documentation needed minimal revisions. The requirements also addressed side benefits not related directly to compliance, such as minimizing changes to source applications and broad applicability of the solution.

Assess and purchase server hardware and software.

 The existing data was used to determine the disk capacity and processing requirements of the server hardware and Oracle software. This exercise was accomplished jointly by infrastructure and database personnel.

Install and validate the server-based software.

 After all required components were purchased, the hardware and software were installed and documented using predeveloped IQ/OQ scripts. IQ/OQ scripts are often supplied by product vendors. 

 An important step in any implementation is to ensure that users understand how the software works. For this implementation, it was equally important to make sure that all users were sufficiently knowledgeable about the regulation.  

 The inventory process identified all files used to support the clinical trial process. Because the files originally resided across a collection of computers, and there were many duplicate files, it was neither advantageous nor necessary to migrate all of them. It was important to systematically identify the files to be migrated, where they would be stored, and when the transfer would take place. As always, it was important to document the results.

Configure source software applications to work with the server-based solution.

 Each application generating or using the data stored in the compliant repository had to be looked at to determine whether any configuration changes were warranted. The solution implemented typically required minimal configuration of the source applications. The most common change was the reassignment of the default folder paths for the creation or reading of files.

 An important component of the implementation was to develop and execute test plans and scripts and to document the results. Other areas documented were design, configuration, and summaries of activities and results. 

Because clinical trial data must be maintained for many years, it was also critical that the solution allowed data to be archived to durable media such as CD, DVD, or network storage devices while maintaining 21 CFR 11 compliance. The archiving process selected for this pharmaceutical company secures the data in such a way that it can be restored using a file digest or unique fingerprint, ensuring that the restored file has not been tampered with while outside of the active file repository. Additionally, after a file has been archived, the associated metadata continues to be searchable, allowing the software to be used as a long-term data management solution that enables historical datato be restored and reanalyzed when required. 


As the clinical trial process continues to migrate toward a completely integrated electronic model, careful consideration must be given to the role that 21 CFR 11 will play. Many companies are currently taking the first step by evaluating their current technology architecture, which is often mainly file-based. The key to demonstrating compliance for this type of regulated data lies in minimizing the windows of opportunity for modifying data when it is not under audit trail controls. 

Maintain files under tight 21 CFR 11 control for their entire life cycle.

 Address security, audit trails, and archiving throughout the records retention period. 

 that addresses the requirements of the regulation without disrupting existing workflow.

 to the overall process so that existing users and applications, such as analytical tools, can continue to access the files.

Now that FDA is enforcing its Electronic Records, Electronic Signatures rule many pharmaceutical companies are reconsidering their data systems.

21 CFR 11 Compliance for Clinical Data

Bayesian isn?t the most popular statistical method yet, but it is gaining ground in a number of clinical trials areas.

Applied Clinical Trials-08-01-2003

My Fiefdom, Right or Wrong

Information Showcase

What?s Old Is New Again

Strategy and Tactics for European Clinical Trials

21 CFR 11 Compliance for Clinical Data

Bayesian, Likelihood, and Frequentist Approaches to Statistics