The European Union's (EU) implementation of the Clinical Trial Directive (CTD) into laws, regulations, and administrative provisions represents one of the most demanding changes faced by pharmaceutical companies operating in Europe in the past 30 years. Although the main objective of the EU CTD was to define a more homogenous and consistent regulatory environment that offers maximum protection to participants in clinical trials (an area comprised of some 450 million people), industry experience shows that some old processes have not been decommissioned, but new ones have been added. Most disturbingly, provisions of the EU CTD are being interpreted inconsistently by the member states. Success in implementing the directive should, however, encourage transparency of information and decision making across the EU. 

Interestingly, from a multinational company's perspective the EU CTD has catalyzed the overhaul of company processes and fostered a cross-departmental dialogue. For example, better communication between clinical operations/management and manufacturing because of the need to embed the qualified person (QP) in the clinical trial process has helped align the processes and procedures used in clinical trial activities, specifically between Phase II/III and Phase IV. In addition, improved collaboration and communication has been achieved through a structured training program for all staff involved in global clinical trials. 

Implementation of the directive has also provided opportunities for more synergy, less duplication, and more clearly defined roles and responsibilities within cross-functional departments. 

Although Roche's operations have long conformed to strict Good Manufacturing Practice (GMP), the role of the QP in the release of commercial and investigational medications has contributed to "personalizing" this procedure, making it more transparent to those involved in trial management. 

Similarly, the newly created QP for pharmacovigilance supports transparency in this critical area and gives a "human face" to the demanding task of risk–benefit assessment. Although one of the goals of the EU CTD was to facilitate faster access to novel therapies through harmonization of administrative regulatory requirements and define binding timelines for the review and approval processes, evidence that this goal can be reached still needs to be produced. So far little, if any, simplification or acceleration of administrative processes has been observed. 

An improved alignment and collaboration concerning regulatory requirements is still needed at the EU level and even more so across member states. In some areas there has been a positive increase in transparency and structure. However, improvements need to be made in a number of areas, including: 

Reversing additional administrative burdens.

 Suspected Unexpected Serious Adverse Reaction (SUSAR) "traffic" has substantially increased, and ethics committees and investigators complain of being overloaded with information of little value to help them in making an independent assessment of risk–benefit. 

Changing Investigational Materials Plan (IMP) labels.

 Definitions of legal representatives and sponsors have been changed "mid-stream" by some member states. 

Increasing transparency across the EU regarding approval criteria for trial design or protocol

. More transparency has been achieved when it comes to the administrative aspects for obtaining clinical trial application (CTA) approvals. 

Establishing a clear and uniform definition of what constitutes an investigational medicinal product

. Because of economical considerations, definitions differ from country to country, which hampers both industry and nonindustry sponsored studies. 

Creating better risk assessment algorithms to allow for tailoring of regulatory requirements in relation to the complexity of the planned research

. For example, the need for a complete IMP data package for studies that explore new formulations. Failing to do so will result in such studies being placed outside the EU. 

Reducing impediments surrounding administrative aspects of a trial

. At present, obstacles relating to issues such as legal representation, sponsorship, and insurance can become so huge that they cause delays or render a study impossible. 

Agreeing on an EU-wide "birth date" for updating national CTA dossiers

. Under present rules, these deadlines are highly variable between countries, which results in a duplication of effort. 

Harmonizing the timetable for CTA submissions

. Currently, some CAs only allows CTA submissions on certain dates. 

Easing the availability of mock-up labels.

 This refers to labels used for CTA submissions. 

Training not only helps ensure people involved in clinical trials know what to do; it also lets them know why they are doing a given task. Together, communication and education help create a successful relationship between departments and clinical teams, and provides a better assurance that the EU CTD is implemented to the best practice standards and achieves the best possible results. In addition, training is the best communication tool and provides an ideal opportunity to share knowledge acquired during clinical trial experiences. 

On the positive side, clinical trials are still being conducted in the European Union in comparable numbers and scope. One concern, however, is feedback from academic sponsors that their trial activities have been hampered,which has delayed or even made some studies impossible to launch. The "modalities about so-called noncommercially sponsored trials" will hopefully redress this situation. However, solutions still need to be found to eliminate unnecessary regulatory hurdles that do not add to improved protection of trial patients or the quality of clinical data, regardless of the affiliation of a sponsor.  

Furthermore, we must find ways to improve the dialogue between stakeholders—industry, authorities, and academia. In fact, all these stakeholders share a common objective, which is to provide safer and better medicines faster to patients. There are still many unmet medical needs that must be addressed. In the clinical development and regulatory field a key factor of success will be a continuous commitment to process improvement shared by sponsors (academic and industry), investigators, and regulators. 

is global head of systems and process improvement, pharma development quality (PDQ), with F. Hoffmann-La Roche Ltd., Grenzacherstrasse 124, CH-4070 Basel, Switzerland, email: 

 is global head of pharma development quality (PDQ) with F. Hoffmann-La Roche Ltd., Basel, Switzerland.

*To whom all correspondence should be addressed.

Articles

Guest Commentary

To realize the goal of the directive, member states need to collaborate and make improvements.

Impact of EU Directive on Clinical Development

Events around high-profile brands such as Vioxx or Baycol highlight the importance of timely and accurate assessments of safety and tolerability. All medicinal products carry risks in addition to their possible benefits. A judicious decision on whether and how to develop a new medicine can only be made if both benefits and risks are addressed. The purpose of this article is to provide the nonspecialist an introduction on the methods, terminology, and thinking behind the clinical assessment of safety and tolerability.  

Conceptually, a clinical trial is a straightforward enterprise. A select group of individuals is given something one wishes to learn more about, i.e., the investigational product. Another group is given something one knows enough about to use it as a reference or comparator. Both groups are carefully watched or monitored. All other things being equal, differences between the groups—if large enough not to be explained by chance—are attributed to the investigational product.  			

What sounds simple in principle, as many readers will be painfully aware, is not so simple in practice. This is particularly true for assessments of safety and tolerability. Whereas in most cases efficacy assessments have a clear direction and focus, safety and tolerability assessments resemble the proverbial search for a needle in a haystack. 

The corner stone of a clinical risk assessment is the adverse event (AE). Put simply, an AE is any change in health status other than the hoped for treatment benefit. Not showing a positive effect is not considered an AE in a clinical trial since it is the purpose of the trial to find out if there is a treatment benefit. Adverse events may pertain to: 1) clinical laboratory abnormalities in body fluids (e.g., blood, urine) or other biological samples; 2) abnormalities detected during technical investigations (.e.g., electrocardiogram, X-ray); 3) signs identified during a physical examination (e.g., depressed tendon reflexes); 4) symptoms recorded from a patient history (e.g., nausea, weakness, difficulty in thinking). AEs are not always "bad" and may: 1) provide evidence of a compounds absorption; 2) provide a parameter against which to titrate a dose; 3) allow identification of new indications (e.g., minoxidil and hair growth); or 4) provide leads for the development of new compounds (e.g., sulfonamides and sulfonylureas). 			

Recording of adverse events frequently begins with the signing of consent forms and ends at a certain lag period after ending participation in the trial. Depending on the nature and number of subjects enrolled in a clinical trial, hundreds or thousands of AEs may be recorded and reported. Many of these will be purely coincidental or related to the underlying illness. Thus investigators are usually asked to assess whether they believe the AE is related to the medicine under study or not. An AE believed to be causally related to a medicinal product is referred to as an adverse drug reaction (ADR).  

ADR may describe an association between a single medicinal product and an AE, between two medicinal products (e.g., drug–drug interaction) and an event, or between one medicinal product and a cluster of events (syndrome). Contributory factors (i.e., environmental conditions, concomitant illness, co-medication or hereditary predisposition) play an important role in the manifestation of ADRs. Aggravation of a medical condition existing at baseline also constitutes an adverse event, and thus a possible ADR. One classification that has proven useful for the assessment of ADR involves ranking the observed reactions on a scale ranging from idiosyncratic reactions to those from identifiable and predictable intrinsic toxicity (i.e., known toxicology of the compound). Idiosyncratic reactions are sporadic, generally not reproducible, and not due to a mechanism specific to a certain medicinal product, e.g., 1) hypersensitivity reactions and 2) reactions attributable to an auto-immune disposition. However, not all ADR can be linked to a plausible explanation even after a comprehensive and detailed analysis. 

The underlying principle of a risk assessment is observing the unexpected. Any discrepancy between the expected occurrence of an AE and the actually observed event rate could constitute a signal. The expected occurrence rate of an AE is based on the assumption of either 1) a known effect of the medicinal product (or other members of the same class) on the occurrence of an AE or 2) independence between occurrence of the AE and exposure to the medicinal product. In clinical studies, the occurrence of the AE in the control arm constitutes a proxy for the background risk of the event. This  may be validated by additional data from other studies (i.e., estimates of incidence or prevalence of AE in a similar patient population as the one studied). Such validation is particularly important in circumstances where the frequencies of an AE appear unusually low or high among those allocated to a control regimen.  

Analysis of AE is a multistep process. Initially, the crude expected event rate is compared to the observed number of events, i.e., the primary comparison is between the number of cases (i.e., events) and noncases (i.e., nonevents) in the subject cohorts. In a second step specific attributes of the AE may be compared, such as severity, duration, time of event or details of presentation. A quantitative signal assessment requires three parameters: 1) the background risk of the event in the reference population, 2) the total number of patients exposed to the medicinal product, and 3) the number of events recorded in the course of exposure. This allows an estimate of the incremental incidence of an AE as a function of exposure. For infrequent medical conditions the expected number of events to be seen in a single or group of studies remains low and a maximum of one to three cases could be accepted as possibly coincidental. For very rare AEs, such as agranulocytosis or toxic epidermal necrolysis, coincidental occurrences are so unlikely that a single report constitutes a warning and requires further investigation. This emphasizes the need to characterize events accurately to avoid misclassification that can potentially lead to incorrect labelling. 

AEs are appraised both on the patient level (with a more qualitative review) and on the project level (with a quantitative bias in the appraisal). Aspects reviewed when appraising an AE in a singular individual include:  

 What confirmatory and supportive information is available characterizing the event (laboratory measurements, etc.)?  

 Was the individual really exposed to the medicinal product?  

 Did the event or signs of its onset occur before or after exposure? To quantify a time course it is useful to document the time between the beginning of exposure and the time to the last administration. What was the lag time between the exposure and the event? How long did the event last? Did the AE occur after discontinuation of the medicinal product? If so, how much later? Adverse events may be triggered by discontinuation (abrupt or otherwise) of a medicinal product, e.g., rebound reactions. To what dose(s) was the patient exposed? What was the last dose before the event was observed? What is the cumulative dose since beginning exposure? Was the plasma concentration of the medicinal product or its metabolites measured and elevated?  

 Has the individual experienced similar events before exposure to the medicinal product or related products? Does the individual show any attributes known to predispose to the AE?  

Subsequent occurrences/response to the event.

 Was the medicinal product discontinued or the dose reduced? Did the observed event subside thereafter? If the medicinal product was continued, did the event subside or ameliorate with time? Was a dechallenge and rechallenge performed? Did this support a causal relationship between the medicinal product and the observed event? Is tolerance to the adverse reaction observed? Were treatments for the AE initiated? If so, which? How did patients respond to the treatments?  

Appraisal of the AE on the study or project level

Aspects reviewed when appraising an AE on large numbers of individuals include:  

 The probability of observing an AE (with a given incidence) depends on the background incidence in the studied population and the number of individuals exposed (see Table 1). Has the specific event been reported before in individuals exposed to the medicinal product? If so, how often? What is the background rate of the event in the studied population? It is difficult to detect an ADR for an AE that also occurs commonly in populations not exposed to the drug. What is the cumulative population exposure for the medicinal product (patient × years)? What is the longest period of exposure? Identification of an ADR associated with long-term administration of drugs for a chronic disease can be  challenging.  

Probability of Observing an Adverse Event  

 What evidence is available from other studies (preclinical) linking the medicinal product to possible adverse events (e.g., mechanisms, metabolites)? Have similar events been described for other compounds in the class or similar modes of action?  

 Are other explanations of the AE other than the medicinal product possible (precipitating therapies, underlying disease, other concomitant illnesses, diagnostic procedures known to cause the observed event, spontaneous events without identifiable cause)? Are drug–drug interactions a possible cause for the AE?  

 What is the percentage of patients in whom the event is classified as mild, moderate or severe? Are there any imbalances between the investigational product and comparators?  

 Did the event occur equally across all patient subgroups? Are certain attributes (risk factors) associated with an increased or decreased occurrence of the event? (e.g., high vs. low dose, elderly vs. not elderly). Although age itself is not an independent risk factor for ADRs, the risk of developing adverse drug reactions is linked to age-dependent factors such as polymedication, multiple diseases, and changes in pharmacokinetics or pharmacodynamics.  

 Did the event occur concomitantly with other events, i.e., are these indicative of an underlying syndrome (e.g., medication-induced SLE)? The occurrence of specific events both as serious and nonserious events may reflect the same underlying pathology, differing only in quantitative expression (i.e., two serious events and 32 nonserious events with a distinctive imbalance between the medicinal product and comparators). Thus, it is important to assess all events of a given nature (irrespective of severity). 

The risks assessment of a pharmaceutical agent is not an absolute quality, but is meaningful only in a given context, i.e., highly dependent on the benefits the agent is expected to confer to a given target patient population. Authorities appraise the risks associated with a medicinal product based on the specific nature of the AE, the number of individuals exposed,  and the number of events (i.e., to account for multiple events occurring in an individual), the indication for which the medicinal product was administered, doses associated with the AEs, routes and timing of concomitant medication, degree of association of the medicinal product and the event, concurrent illnesses, reversibility of the AE and time until resolution, outcome of a possible dechallenge and rechallenge, as well as the demographic characteristics of the affected individuals. The quantification of the risks of a medicinal product is based on both the frequency (how often do the ADRs occur) and the magnitude of the undesired effects (degree of discomfort, severity of complications). Rare serious reactions, although striking, have a small impact on cumulative risk. In contrast, less dramatic but more common reactions are more likely to impact the overall risk–benefit assessment. The acronym "SNIP" succinctly summarizes key attributes that regulators are looking for: Strong, New, Important, and potentially Preventable. Examples of preventable ADR include: 1) allergy to the medicinal product or to similar medications, 2) overdose because of inadequate serum drug concentration monitoring, and 3) accumulation due to lack of dose adjustment in patients with impaired drug clearance.  

A key outcome of a systematic evaluation of the ADR profile of a medicinal product is the identification of strategies to mitigate risk, i.e., precautionary measures suited to reduce both the incidence and severity of possible ADRs. Possible  measures include monitoring of patients (e.g., regular LFT); co-administration with food (e.g., cyclosporine with chocolate milk); dose adjustment (e.g., in elderly with low muscle mass for digoxin) or avoidance of a product in patients with increased genetic risk, relevant concomitant illness or requiring a co-medication known to interact with the medicinal product; splitting of doses or alternate day dosing (e.g., aspirin); slower or smaller dose escalation steps; and 

co-administration with another pharmaceutical agent that may increase or decrease the absorption, metabolism or excretion of the medicinal product (e.g., probenecid to slow elimination of penicillin) or that otherwise reduce the incidence or severity of the AE (e.g., anti-emetics and chemotherapy). Providing guidance on such measures in the package insert reduces the risk of a medicine and improves the risk–benefit ratio.  

The safety assessment of a medicinal product is an ongoing, dynamic enterprise that never ceases during a product's active life cycle. The probability of detecting all possible relevant AEs of a drug during premarketing development is moderate (Table 1). This is particularly true in complex situations involving drug–drug interactions, or when the event rates or severity are affected by other factors. Reassuringly, with diligent pharmacovigilance previously unrecognized, clinically significant ADRs are frequently detected and corrective measures initiated soon after commercialization.  

1. ICH tripartite guidelines. The Extent of Population Exposure to Assess Clinical Safety for Drugs Intended for Long Term Treatment of Non-life Threatening Diseases, Adopted for Step 4, 27 October 1994 . 

2. A.C.G. Egberts, R.H.B Meyboom, E.P. van Puijenbroek, "Use of Measures of Disproportionality in Pharmacoviglinace," 

3. M. Hauben and X. Zhou, "Quantitative Methods in Pharmacovigilance," 

4. Reviewer Guidance Conducting a Clinical Safety Review of a New Product Application and Preparing a Report on the Review. US FDA CDER Good Review Practices, February 2005.  

 is global brand medical director dyslipidemia & diabetes with Novartis Pharma AG, Lichtstrasse 35, CH-4056 Basel, Switzerland, +41 61 324 6229, fax +41 61 324 5119, email: 

 He is also a member of the ACT Editorial Advisory Board.

Feature Article

Instructions for evaluating adverse event data and guidelines for taking the proper course of action

Assessing Safety in Clinical Trials

Regulatory submission solution addresses the needs of smaller biotech and pharma companies

 (Whippany, NJ) recently released eCTDXPress Aspire, its Web-based eSubmissions software package. The electronic regulatory submissions package is targeted toward growing biotech and small pharmaceutical companies. The software enables smaller organizations the ability to create and manage submissions in-house to ensure they are correctly implemented and validated.  

eCTDXPress Aspire is fully scalable, a convenient feature for companies anticipating future growth. Other features include life cycle management capability, on-site maintenance and support from Image Solutions, and the availability of ISI consultants for regulatory operations submission help—a good way for employees to gain knowledge and experience in building eCTDs in-house. The eCTDXPress Aspire package includes eCTDXPress Compiler, which helps ensure submissions are built to agency specifications, and eCTDXPress Manager, a central eCTD repository. 

eShowcase

eShowcase: eCTDXPress Aspire

Phase I package adds formulary accountability, recruitment, lab, and EDC features

 (Montpellier, VT) has added formulary accountability, recruitment, clinical lab, and EDC components to LabPas CT, its software package designed for Phase I management. LabPas CT 2.5 deploys PDAs on clinic floors for scanning patient and collection vessel barcodes and RFIDs to eliminate error potential. It provides real-time electronic data entry for collection times, comments, dosing, vital signs, and adverse events, and can adapt to changing protocols.  

Enhancements in the latest version of LabPas CT allow users to track and manage the entire fomulary chain including accountability, distribution, reconciliation, returns, and destruction. The package also allows users to manage subject information such as biometrics, and handles scheduling and study assignment tasks. Also, the new clinical lab component of LabPas CT integrates clinical trial results into the study database, and the software exports clinical study data in a variety of formats for easy eCRF creation. 

eShowcase: LabPas CT 2.5

Recently, at a sponsor's request, we audited a Phase I unit under consideration for conducting a relatively intensive study that included multiple lung biopsies. Subjects who completed the study could earn up to $5000 in compensation for participating and undergoing the potential clinical risks of the biopsies. 

Five-thousand dollars represents more reimbursement than we are used to seeing for studies we audit. The sizable amount caused us to contemplate a rarely discussed but almost certain to occur phenomenon: Subjects participating in this study probably would not realize the full $5000. 			

Study subjects won't realize the full amount because they will receive an Internal Revenue Service Form 1099 from the Phase I unit, and they will have to pay taxes on the dollar amount indicated on the 1099 when it is added to other income they earned during the calendar year. Depending on a number of personal income and expense factors, the $5000 might shrink to $4000 or less. 

When a potential subject is considering the value of the $5000 versus the risks of the lung biopsies and other study-related tasks, perhaps he/she should also consider this benefit–risk ratio in light of the actual dollar amount he/she might realize. It would therefore be prudent to inform potential subjects that taxes may have to be paid on the $5000. 

Of course, if some of the $5000 is spent on parking, baby sitting, or other legitimate study-related expenses, these items could be used on tax return forms to offset a portion of the study compensation income. 

The tax will have the greatest impact on those with the highest income and have the least impact on those with no other income. Nevertheless, the surprise of having to pay income tax on the $5000 probably will be greatest for those with the lowest income. If the stipend for a clinical study is small, say $50, then neither rich nor poor subjects will be greatly impacted by federal and state taxes. 

There are other considerations regarding the $5000. Some ethicists would assess this payment as "coercive," particularly for low-income persons. Others prefer to place the payment into a free enterprise/willing adult framework. In either case, net after-tax realizable income is applicable to the discussion of payment ethics. 

Informed consent content should include an accurate and thorough description of all relevant factors that might influence a potential subject to enroll or not enroll in a study. Most subjects probably do not initially consider their tax burden on earned income when they read and discuss consent. 

Fuller disclosure of net monetary benefit in informed consent is the right thing to do.  

The authors can be contacted at: GCPA, Inc., 12208 Fairfax Station Road, Fairfax Station, VA 22039, (703) 988-9080, fax (703) 988-9082, email: 

 DrPH, MBA, is president of GCPA Incorporated and a Member of the 

 MBA, RN, is vice president of GCPA Incorporated

A Closing Thought

There are a number of factors potential subjects need to consider when deciding whether to participate in a clinical trial, including an often overlooked matter that this month's authors examine: taxes.

Informed Consent Considerations

System enables IRB members to review AEs in near real-time from anywhere in the world

(Wilmington, NC) just released a customizable, global event management and adjudication system for quick review of safety and endpoint-driven data from large clinical trials or registries. The secure, Internet-based system provides broad access to adverse event data, particularly in studies with multiple information sources and ones that need review by a board of independent physicians.  

GlobalView EventNet provides access to data in near real-time and allows IRB members to examine the data at their own convenience from any location around the world. The board members can also request follow-up information or confirm adjudicated events through an online interface. GlobalView EventNet also sends automatic email alerts to prompt and encourage timely review. The system electronically compares each IRB member's decision and documents them per established guidelines.  

System enables IRB members to review ?s in near real-time from anywhere in the world

eShowcase: GlobalView EventNet

The  need for special protections for vulnerable populations participating in clinical studies has generated controversy and uncertainty as policy makers and research advocates seek to prevent abuses while also permitting needed studies. A recent report from the Institute of Medicine (IOM) lays out important safeguards for all prisoners participating in clinical studies. Calling for extended federal regulation of all research involving prisoners, however, opens the door to broader legislation expanding standards and oversight procedures for human subject research overall. 

Forty years ago, prisoners were widely used in clinical studies, including drug and vaccine trials. That ended in the 1970s when revelations surfaced about paying prisoners to participate in testing, some involving exposure to toxic treatments. This led to the development of stricter policies under Subpart C (research on prisoners) of the "Common Rule," which governs all research funded by or monitored by federal agencies. Today most research involving prisoners is behavioral or epidemiological and has to provide direct benefit to study participants; few prisoners participate in studies sponsored by pharma companies, which largely have taken trials offshore. 			

Even so, most media reports on the IOM study recalled past abuses and painted the report as re-opening the door to prisoner exploitation, spurred by industry's mounting demand for warm bodies to populate mushrooming clinical studies. Such comments testify to continued low public regard for the human research enterprise and for the ability of public review boards and government agencies to monitor research activity and prevent abuses. A 

editorial (Aug. 23, 2006) did take a broader view by recognizing that prisoner testing could benefit inmates as well as the general population—if "carried out carefully" with more federal oversight. 

In fact, the IOM report on "Ethical Considerations for Research Involving Prisoners" [available at 

] outlines a program to provide more comprehensive safeguards and oversight measures for studies involving prisoners with an eye to improving participant well-being. The aim is to assist the Office of Human Research Policy (OHRP) in the Department of Health and Human Services (HHS) in clarifying ethical and legal issues related to vulnerable research populations. The OHRP, with input from the Secretary's Advisory Committee on Human Research Protections (SACHRP), has been examining options for updating policies governing prisoners, as well as children, the elderly, mentally impaired, and other groups that may lack the resources and independence to objectively evaluate the risks and benefits of participating in a research study. 

Broader concern about prisoner research policies emerged after OHRP issued guidance in 2003 calling on sponsors to seek institutional review board (IRB) rereview of a protocol if an individual becomes incarcerated while participating in a clinical trial. Opposition to this approach from SACHRP members and IRB confusion pointed to the need for a wider review of the "ethical underpinnings" of research involving prisoners, explains OHRP Director Bernard Schwetz. The SACHRP said we need "more than band-aids to fix Subpart C." 

The IOM report suggests that prisoners could benefit from participation in some Phase III clinical trials, so long as study protocols are fully reviewed and monitored by IRBs and that at least half the subjects are noninmates. The committee is "not necessarily encouraging more research involving prisoners," explains Schwetz, but wants to ensure that proper oversight is in place for those studies that could benefit prisoners. 

The report emphasizes the importance of ensuring voluntary informed consent, adequate standards of care, and privacy protection for prisoners. It also calls for establishing a collaborative review approach with input from prisoners on protocol design and expanding the definition of "prisoner" to include restricted individuals in community settings, as well as those incarcerated. 

The report also acknowledges that much research involving prisoners now takes place outside current federal regulations, which do not extend to the Department of Justice's Bureau of Prisons or to state prison authorities. To remedy this situation, the panel calls on Congress to establish uniform guidelines and a national oversight system for all human research programs that enroll prisoners. 

In discussing the IOM report at its August 1, 2006, meeting, SACHRP went further and proposed that legislation setting standards for prisoners should extend to all human subject research, including independently funded studies that fall outside the boundaries of the Common Rule. SACHRP plans to further discuss strategies for bringing all research under the federal umbrella at its next meeting in November. 

Even without legislation, many of the IOM proposals related to studies on prisoners may affect clinical research policies more broadly. A key recommendation is to establish a detailed public database to track all studies involving prisoners and to ensure that such research programs are open, transparent, and accountable. The poor record of pharmaceutical companies in registering active studies on the 

 Web site currently is a hot topic in the legislative arena, and support for a prisoner research database could weigh in on the broader debate. 

Another important IOM proposal is to shift to a risk–benefit framework and away from today's category-based model for evaluating research proposals for prisoners. Current rules permit prisoners to enroll only in studies on the effects of incarceration, on health conditions specifically affecting prisoners, and other narrow areas. Instead of checking that a study fits a set category, the IOM panel believes it is more appropriate for researchers and IRBs to weigh the potential harms and benefits of each specific research proposal based on the level of risk, benefit to the individual, and potential knowledge gained. 

Such a risk-based approach reflects current thinking that with proper safeguards, prisoners could participate in studies with greater than minimal risk, provided there is potential benefit to the individual. This and other issues similarly arise in OHRP deliberations on policies governing research with children. A SACHRP working group has long been examining topics related to appropriate research involving young patients: privacy protection, the need for special advocates on IRBs, whether young patients have the capacity to give informed consent, and appropriate compensation for trial participants—all relevant also for research with prisoners. Another SACHRP working group seeks to define what makes an individual or population "vulnerable," what are adequate safeguards, and what issues might interfere with informed consent. 

Although it would take years for Congress to agree on any legislation expanding standards for human subject research, the IOM report may have a more immediate impact. At a minimum, IRBs and members of the research community will read it and become more aware of the issues and requirements for research involving prisoners. And it may prompt a new look at how the federal government should manage these issues. Broader federal oversight of biomedical research also would expand the scope of OHRP's responsibilities and raise the issue of establishing a federal agency outside of HHS to oversee these issues.  

View from Washington

Confusion over policies governing prisoners points to the need for clear, uniform safeguards for all research.

Subject Protection Issues Gain Broad Support

Over the past year many data managers have expressed concern about their ongoing roles and livelihoods with the increasing adoption of EDC/eClinical. Add to this concern the following statement: "A wired planet will destroy the need for data management on a project-by-project basis. [EDC] will obviate the need for data management,"

  which was made by a workshop leader at the 2006 Annual DIA meeting. The workshop leader also suggested that massive data manager overstaffing exists at various pharmaceutical companies, and added that radical reform is warranted.  

Certainly statements such as these do little to allay the concerns of data managers, and may be based on the false assumption that technology  eliminates jobs; often, in fact, technology merely  changes the nature of work, largely in an emancipatory fashion. Data managers can and should play a pivotal role in continuing to add value to their companies by helping them transition to the "Brave New World" of EDC/eClinical and realize the promise of these new technologies in overall cost reduction. 

Data management (DM) has been defined at a high level as encompassing all the disciplines related to managing data as a valuable resource, including acquisitions, database administration, storage, backup, security, and quality assurance. Significantly more complex definitions exist and encompass elements such as reporting and even analysis. What is common is that DM as a discipline may be said to have data quality assurance as its primary function. 

Within any given organization, these activities may be performed by a dedicated group or by various individuals within distributed, disparate groups—usually as a secondary function. It is important to note that DM activities are generally performed across all quality research projects, even if the role or department of "data management" does not formally exist. Thus, two frames of reference exist with respect to DM: dedicated and distributed—which will have important ramifications for successful EDC/eClinical implementation. 

Irrespective of the frame of reference and subsequent view of DM (whether as a dedicated or distributed function), the set of objectives sought can be operationally defined in research as those activities that ensure the data and its database(s) are: 					

accurate—it represents the data submitted

precise—the data are clear, unambiguous, and serve to answer the research question

compliant—it meets various FDA and ICH requirements

timely and accessible—assuming the foregoing is addressed, the data are readily available for various degrees of review and analysis.

If the above prime objectives are met, then data quality will be assured, and thus the data will have been well managed. 

Adoption of EDC/eClinical technology has the potential to impact DM work performed during a research initiative, such as work related to process and workflow changes as well as the essential nature of the work itself—with the former in respect to when, and the latter in respect to what. 

Adoption of EDC/eClinical technologies affords companies the opportunity to engage in process re-engineering for maximum effectiveness and return on investment. Simply put, these technologies change the timing and flow of work. A simplified representation may be seen in Figure 1. 

 Figure 1. Adoption of eClinical technologies allows companies to re-engineer work processes for maximum effectiveness and investment return.			

Shifts in when the pattern of work burden is required are derived from technology's impact on the amount of work needed at any given point in the process. For example, in a traditional paper-based methodology, the process of data collection through to "clean" data availability in the database may be expressed as in Figure 2. This is essentially an adynamic methodology at point of collection, with a reactive process requiring significant human intervention postreceipt, and involving potentially lengthy delays as data correction forms are generated, logged, sent, received, actioned, and new data is entered—whereupon the process begins anew. Additionally, it must be performed for each case report form received. Expressing the same workflow in the EDC/eClinical environment yields the type of dynamic feedback described in Figure 3. 

Figure 2. Traditional data collection is a reactive process requiring significant human intervention and potentially lengthy delays. 			

The EDC/eClinical approach is proactive in that DM personnel, bearing in mind their prime objectives, create an environment where high data quality may be assured before the collection of any information. This is accomplished through specification prior to data collection, validation, and edit checks (via the data dictionary), whereby personnel collecting data can be given dynamic feedback as to its acceptability (within range, date, type, etc.) at the point of entry, which lends itself to a management by exception approach. Thus the burden of work shifts from a reactive per-instance back-end process to a proactive per-project front-end process. 			

Changes in the pattern of work provide indicators of potential changes in the nature of work. Given that the example in Figure 2 indicates that the traditional methodology is essentially reactive and conducted on a per-instance basis, it can be expected that such an approach results in a high burden of tactical work over a prolonged period of time (as seen in Figure 1), where the greater majority of the work is performed after study deployment. Conversely, the eClinical work burden is shifted, and the shift gives rise to a change in nature. 

Figure 3. In an EDC/eClinical-based data collection environment, the focus shifts from a reactive, per-instance process to a proactive, per-project one.

The EDC/eClinical approach shifts the burden of work to predeployment, and from reactive per instance to proactive per project. In so doing, the work is not merely shifted in terms of time/conduct, but also in its very nature: from tactical-emergent based (i.e., designed to deal with day-to-day issues as they arise, such as the receipt of error laden CRFs) to strategic-objective based (i.e., a highly refined predeployment plan designed to attain specific goals over an extended period—for example, the development of a comprehensive data dictionary with sophisticated validation/edit checks). 

Thus, EDC/eClinical can and does change rather than remove the role of the Data Manager—indeed, in a very positive fashion in some cases. As Zielinski

  put it, writing in late 2005: "An intelligent outcome of EDC's ability [is] to minimize the mindless work that results from using paper CRFs. [Data managers] in these roles focus on issues that require thought and expertise, rather than spending time doing largely clerical data clean-up." Thus emancipated from the mundane, data managers faced with EDC/eClinical adoption need to understand that their role will become strategic-objective oriented. New skills may be required, but not necessarily new people. Significant cost efficiencies can only be obtained with process changes that account for the changing nature of work. 

Some contend that "EDC is not a data management position. It is mainstream and it is enterprise wide."

  And indeed they have a very good point. In order to be truly successful, EDC/eClinical adoption must be visibly and publicly supported by senior management. But even recognizing this fundamental truth, data managers can still add significant value, and with the dedicated DM model, be in the best position to do so. 

Two primary opportunities emerge for the thoughtful data manager: their own definition of their role and EDC/eClinical system selection advice. 

It is a maxim of business that if you do not define your role, someone else will for you. With the skills and expertise of many data managers, a proactive stance is required in order to avoid the imposed definition of "R.I.P." Where DM exists as a dedicated function, data managers have enormous value and can continue to contribute. Strategic-objective orientation lends itself poorly to the distributed DM model. By its very nature, the distributed functional model means that the individuals have other primary tactical roles, and thus are not well positioned to take on a broader outlook on the project or the enterprise as a whole. 

Data managers that exist as a dedicated primary function, however, are ideally positioned to reinvent their role to the mutual benefit of both themselves and the organization—the nature of their work will change, but their essential goals of accurate, precise, timely, and accessible quality data will not. 

Companies utilizing the distributed DM functional model may actually find some difficulty in adopting EDC/eClinical—after all, it is one thing for senior management to mandate a methodological change and quite another to actually make it happen. Who is cognizant at a detailed level of all aspects of the clinical initiative's strategic goals, objectives, and tactical challenges at all phases and the process changes that need to be broadly implemented if not the data manager? 

Given their cognizance of data quality objectives, data managers are well positioned to assess and advise on EDC/eClinical system selection. The baseline characteristics of the system's collection instrument will ideally permit and accommodate the following: 

 a distributed technology not dependent on specific hardware or software considerations: a zero/ultra-thin-client system. This is an important fundamental element, as it will decrease costs and management burden significantly and concomitantly improve data accuracy/quality, timeliness, and representativeness. 

Sponsor/CRO data accessibility/timeliness:

 a system not exclusively dependent on a batch processing validation/edit check methodology whereby entered data is inherently "old" (i.e., not current since last processing run). Data should be processed and made available within the system for review and feedback in the shortest feasible time, which is usually measured in milliseconds, versus the days or weeks it takes with batch processing. 

 an instrument whose underlying system is capable of directing the data collection of the clinician at the site level rather than acting as a largely passive recipient of data with a reliance on human agency to remain cognizant of subsequent required work/procedures, yet is flexible enough to accommodate an individual company's workflow as it changes over time. This will assist in accuracy, precision, and timeliness of data collection. 

 the assessed systems comply with current (21 CFR 11, etc.) and emerging regulatory (CDISC) and GCP requirements. 

EDC/eClinical technologies have promised much by way of cost savings. Some have chosen to interpret those savings as being derived from wholesale reductions in staffing levels, including data managers. Companies that are fortunate enough to find themselves with dedicated data managers, however, may be at a distinct advantage in selecting and designing appropriate and efficient EDC/eClinical systems and in facilitating process change cost efficiencies. 

It is incumbent upon data managers, however, to proactively acknowledge the changing nature of their work, define their own roles, and continue to add value through strategic thought and expertise to their organizations—in short, to embrace, pursue, and be a vital part of the EDC/eClinical Brave New World: "O brave new world / That has such people in't!" (

1. J. Anderson, Waife & Associates, as quoted in "R.I.P. Data Managers?" by M. Uehling, 

2. A. Zielinski, "Data Managers' Workflow with EDC—The Real World, The Ideal World," 

3. P. Brown-Stafford, Quintiles, as quoted in "Data Efficiency—The Wave of the Future," J. Park (ed.), 

PhD, is chief marketing officer & principal scientific advisor with MedNet Solutions Inc., Carlson Parkway, Suite 605, Minnetonka, MN 55305, (866) 258-2735, 

As more companies adopt eClinical technologies, data managers must redefine and update their role.

Data Management: R.I.P. or Brave New World?

It is a little over a year since the Hurricane Katrina disaster. We have been reminded of the horror of those days through vivid pictures documented in the press and on TV and the Internet. The following quote by Cora Christian, MD, reminds us of the work that is still to be done in the research community: "Drug development and hurricanes have much in common...what takes years to build can be destroyed in only a moment" (DIA Annual meeting, June 2005 ). What we must ask ourselves is: What have we learned over the last year from this disaster? 

While Katrina is uppermost in our minds, it is important to recognize the increasing risk of any disaster to society. Threats of terrorism, pandemic flu, tsunamis, and earthquakes are indeed real and potentially far reaching, yet our industry has done little to prepare. If we are to improve and learn from disasters, we must not wait to be told the right thing to do but rather act prospectively and establish practices that do the right thing. 

Hurricane Katrina is one vivid example of how unprepared our clinical research community is in the wake of such a disaster. There are three lessons that we can learn from Katrina. Although the following examples may be minor compared to the lives, homes, and businesses that were lost, displaced, and destroyed, we have to start somewhere to right the wrongs of practice without spirit. For if we do not make any attempt at change, then we are setting ourselves up for greater failure in the next disaster. 

Human subject protection reaches far beyond informed consent

. In a time of disaster, policies such as HIPAA that were intended to protect us indeed hindered us. After Katrina, many subjects in ongoing clinical trials were unable to communicate with their Investigators. Even if communication was established, Investigators had no access to treatment assignments, as most records (even electronic) were de-identified for confidentiality purposes.   

Due to lack of planning, most sponsors and study sites had no access to subject identification since all records were "securely" maintained within institutional walls. Therefore, we must plan. We must write policies that allow flexibility as we refocus on the true meaning of subject protection. 

Small but positive improvements to provide this flexibility are underway in Louisiana. One large institution has designed a software system that allows remote but secure access to personal identification parameters to all persons enrolled in clinical trials. The system is only accessible to three individuals identified in the institution's disaster preparation plan. 

An equally thought-provoking option has been the use of universal subject identification numbers, similar in practice to the social security numbering system in the United States. Aside from rapid subject identification in times of disaster, this identifier could help mitigate another form of risk: an individual participating in multiple studies simultaneously. 

. This point easily parallels our earlier observation of subject protection. The communication plans of sponsors, sites, IRBs, and institutions were woefully underdeveloped for a disaster. IRBs and clinical study sites must become more diligent in their planning, seeking out nonlocal contact information for study participants. A few IRBs now require subjects to be given contact information in the form of an identification card. 

Sponsors could better prepare by performing risk assessments of study sites based on geographical location and consider radio communication processes for subjects postdisaster. An additional proposal includes a universal toll-free phone number as a regulatory requirement for investigational product labels. Subjects are likely to evacuate with all types of medication, including investigational products. As a result, a phone number affords them a means of communication regardless of their ultimate location. 

Of course, significant regulatory action would be required to enforce this type of change and other planning would be required to ensure success. Even so, a small, relatively innocuous act by sponsors could have far-reaching effects toward improving human subject protection. 

. Rarely do we have subject populations with a sample size of "1"—think about your last clinical trial. Taking this idea further, any successful industry truly embraces the "entire village" concept. 

Members of our village include our study participants, our drug development teams, our clinical study sites, our ethics committees, and our regulators. For our industry to succeed, the village must succeed. 

We learned that surviving a disaster took a village approach. We expect to leverage this sense of community spirit in many ways. We are recycling used study binders for local schools. Academic facilities and institutions are partnering in unprecedented ways. Study sites have partnered with one another as back-up locations in times of need. We have reorganized local clinical research chapters and planned social events. And, ultimately, we find ourselves discussing and highlighting the true contributions we make to the betterment of society. 

I wonder how drug development might improve exponentially if we only apply these three small lessons on a more global scale. It is true that small things can become larger. Let's remember, that hurricane began as only one wave. 

 MEd, is managing director with Aureus Research Consultants, LLC, 2237 North Hullen, Suite 301, Metairie, LA 70001, (504) 833-1528, fax (504) 833-1567, 

The importance of human subject protection, clear communication, and community spirit are among the issues emerging from the tragedy.

Hurricane Katrina: What Have We Learned?

Clinical Trials: A Practical Guide to Design, Analysis, and Reporting 

This is a general introduction to clinical trials co-edited by Duolao Wang, a lecturer in statistics at the London School of Hygiene, and Ameet Bakhai, a cardiologist at Barnet General & Royal Free Hospitals in London. On the whole, I have a poor opinion of edited books, which often have patchy coverage and an uneven style. This book succeeds against the odds. 

I speculate that the first reason is that many of the contributors—despite the fact that many institutions are represented—come from southeast England, whether from the local London medical schools or GlaxoSmithKline in Harlow. This has no doubt made it easier for the editors to keep in contact with their contributing authors. The second reason is that at least one of the editors is a co-author on every chapter. 

Whatever the explanation, the result is an easy-to-read text with good coverage of topics and fairly uniform presentation. 

I think that it would be fair to describe the book as "broad but not deep," in contrast to the John Matthews book

  which might be described as "profound but narrow." (Wang and Bakhai's work is also targeted at the nonstatistician, whereas Matthews' intended readership was statisticians.) However, as Stuart Pocok points out in the preface, "The book contains over 300 references, facilitating a more in-depth pursuit of each topic if desired." And in fact some of the chapters do point to deeper issues. 

The book is split into 38 chapters divided into five major sections: Fundamentals of Trial Design, Alternative Trial Designs, Basics of Statistical Analysis, Special Trial Issues in Data Analysis, and Reporting of Trials. 

Inevitably in a book with such extensive coverage there are some things with which I disagree. For example, chapter 18 ("Significance Test and Confidence Intervals") gives the following baffling example: 

"Suppose that it is necessary to measure the average systolic blood pressure (SBP) level of all males aged 16 years in the UK in 2005...we can conduct a survey (or sample) of 500 males within the population..." (p. 186) 

This example is not only irrelevant (a health survey used to illustrate statistical inference for clinical trials), it is likely to mislead. Clinical trials are not about representative inference but about comparative inference, being experiments. 

This error is compounded by what follows in chapter 19 ("Comparison of Means"). In order to illustrate various statistical tests, a trial in 24 patients with chronic airways limitation is considered and the following three questions are posed: 					

At the start and end of the study are the mean FEV1 values seen in both treatment groups as expected from the overall population of similar subjects?

Is there evidence of a significant change in mean FEV1 from baseline in either treatment group?

Is the posttreatment mean FEV1 or mean FEV1 change within the active treatment group significantly different from that in the control group?

Of these three questions, the first is illogical. If the values are different the patients are not similar. This may seem like a mere quibble, but once one thinks about it carefully one realizes that it points to a misunderstanding about clinical trials. 

Question two is pointless. What useful inference could one draw about the effect of treatment from the answers? (Unfortunately many trialists try nonetheless to do so.) 

Question three is the one that matters. To be fair to the authors, we do find on page 207: 

				"In a comparative clinical trial, the primary objective is to evaluate the efficacy and safety of a drug compared to a control..." 

And the authors do proceed to answer their question. 

Nevertheless, I felt that there could have been more stress on the inferential purpose of clinical trials throughout the book. 

However, it would be churlish and misleading to end this review on a negative note. A great many topics are usefully and helpfully covered, and chapters 18 and 19 are clear at the technical expository level. This is a useful addition to the introductory literature on clinical trials. Many wishing to get an entry into understanding clinical trials will find it an extremely helpful guide. 

An Introduction to Randomized Clinical Trials

An insightful review of Remedica's 2005 Clinical Trials: A Practical Guide to Design, Analysis, and Reporting

Applied Clinical Trials-10-01-2006

Impact of EU Directive on Clinical Development

Assessing Safety in Clinical Trials

eShowcase: eCTDXPress Aspire

eShowcase: LabPas CT 2.5

Informed Consent Considerations

eShowcase: GlobalView EventNet

Subject Protection Issues Gain Broad Support

Data Management: R.I.P. or Brave New World?

Hurricane Katrina: What Have We Learned?

Broad Introduction to CTs

CDISC Standards Energize EDC

Deploying Mobile Devices in Clinical Trials

Adopting Orphans: Who Does it Best?