Historically, the selection of countries and investigators for clinical trials has been based on a combination of unsubstantiated feasibility questionnaires and legacy familiarity with a core group of investigators. In this vein, the determination of the number of countries/sites and subject recruitment forecasting traditionally has been based on assumptions that all sites start at the same time and perform similarly. This leads to overpromising to deliver within timelines, as the variability in initiation and performance among the sites has not been accounted for. The result is familiar to everyone: Most trials are running behind schedule in terms of enrollment targets and other milestones. 

This article introduces a more informative approach to site selection based on the analysis of past performance and how the review of epidemiological and demographic data can help identify the "golden site profile." The prestudy phase is a great opportunity to use current information and past experiences with similar studies to objectively pressure test site selection and performance assumptions. Furthermore, the article showcases how this data can be used to forecast subject recruitment timelines and measures, such as CRF page volume and CRA/monitoring and data management resource requirements, to predict and prevent overstaffing and waste as well as understaffing and delays. Indeed, it's not enough to be smart at the start. There is a clear need for continuous proactive mitigation of project-related risks across the entire lifespan of the trial. 

Generally, disease indication and study design drive the degree of variability in observed recruitment rates. Less complex designs in more common therapeutic indications with fewer treatment options increase the investigator's familiarity with trial procedures and increase the pool of potential subjects. 

The distribution of recruitment rates across sites is likely to be asymmetric. This may result in the minority of sites recruiting the majority of subjects, leading to deviations from the planned subject demographic profile in the final analysis population. If sites that recruit higher numbers of subjects per month can be identified (golden site profile), then potentially the recruitment rate of chosen sites can be made more symmetric and subject recruitment can be more evenly distributed across sites. High recruitment by each site is beneficial in terms of the number of sites required (and hence the budget) to meet recruitment timelines. However, it is important to ensure adequate site resources to cope with the increased volume of work and the need for early monitoring to capture subject evaluability issues early so that data quality remains high. 

The development of this golden site profile begins, where possible, with the evaluation of historic data, preferably from protocols with similar inclusion/exclusion criteria. The objective is to look at aspects of sites that would appear to predict higher recruitment rates. If historic data from similar trials are not available, then trials from within the same therapeutic area or similar diseases may provide indicators. Even when historic data come from very similar trials, it is important to recognize the limited applicability of the data and the need for a study-specific feasibility assessment using the initial assessment of the golden site profile as a sampling frame. 

The primary aim of the feasibility assessment should concentrate on confirming/refining the golden site profile against which potential sites can be compared during the subsequent site identification process. This is achieved through provision of a detailed protocol synopsis (under a confidentiality agreement) together with a series of questions relating to:  

site location and subject referral networks.

site makeup (e.g., site resources, necessary equipment).

anticipated subject recruitment and screen failure/drop-out rates.

competitive environment (e.g., the number of other studies being concurrently conducted in the therapeutic area).

reimbursement rates (it is sometimes useful to ask the investigator to specify the level of reimbursement that he or she would expect to recruit a subject into the trial. Although budgets should not be set based primarily on investigator feedback, the information is useful in assessing likely site interest moving forward).

For protocols with key inclusion and exclusion criteria, it is useful to assess potential recruitment through a series of questions, beginning with the general subject population of the investigator site and drilling down to the specific population for the proposed trial. This helps the investigator to more accurately assess likely recruitment rates, as it mirrors the investigator thought process during the trial. It is acknowledged that the accuracy of the data collected for recruitment and withdrawal rates will depend on the level of trial experience of the investigator and also on the level of dependency of the investigator upon advertising for subject recruitment. For investigators selected to potentially participate in the trial, these data will be scrutinized further at the prestudy visit. 

The feasibility assessment process should be flexible to allow for refinement and checking of the golden site profile, especially for the more complex therapeutic areas and/or study designs. In these situations, it may be necessary for follow-up interviews to ensure investigator understanding and to allow for a reassessment of predicted recruitment. 

The greater the variability in response to questions assessing recruitment rate, the greater the number of responses to the feasibility assessment required and the greater the number of questionnaires that need to be sent out. Once the golden site profile has been confirmed, the feasibility assessment can evolve seamlessly into site identification, where sites are contacted and their responses assessed in comparison to the profile. Those sites attaining the standard set by the golden site profile can have their prestudy visit scheduled (where the answers to the questionnaire are validated and additional information is sought by the attending CRA). Those sites that are just below the standard can be reserved until the end of the site identification process. 

Underperformance in terms of actual recruitment compared to the response to the recruitment question in the feasibility assessment and/or prestudy visit is expected. The final assessment of site numbers and timeline projection should take this into consideration. Where data from the same sites and/or similar studies are available, the response to the feasibility assessment for this previous study and the actual recruitment can be used to provide an indication of the level of discounting. Another important factor is the time taken to obtain regulatory approval and site contracts. Once the countries and the number of sites within each country have been determined, these lag times and the discounted recruitment rates can be modeled to make any adjustments to site numbers required to give confidence in achieving recruitment timelines. 

Continual remodeling during trial recruitment is also critical to identify and act upon deviations from the planned recruitment timelines and the impact of this on workload through changes in CRF volume and/or drug supply, as well as changes in the demographic profile of the final analysis population. 

So, how have these concepts been applied? Consider the following example. A stroke study required sites to be identified. The review of the historical data revealed three recent, similarly sized, large Phase III studies. The site distribution by region was: Asia Pacific (AP), Central and Eastern Europe (CEEU), Western Europe (EU), Latin America (LA), North America (NA), and the Rest of World (RoW).  

Figure 1. Recruitment rates from a recent stroke study of the top 10% of investigators. 

The majority of investigators who participated in the three studies were in Europe and North America (258 out of 390 unique investigator names and addresses). The largest number of investigators were located in the United States. The median and interquartile ranges of the recruitment rates (subjects per site per month) within each region showed that Central and Eastern Europe had the highest recruitment rates followed by North America and Western Europe (see Figure 2). However, a graph plotting the recruitment rates (subjects per month) of each site sorted in descending order separates the top 10% of investigators (see Figure 1). These 40 investigators recruit at least one subject per month. 

A review of these top 40 investigators revealed similarities. The most actively recruiting investigators are:  

located in more densely populated cities/countries

specializing in neurology with an emphasis on geriatrics

practicing within a large or general hospital

located in countries/cities with an older population.

Figure 2. Use of historical data allows for a summary (Median and Interquartile Range) of recruitment rates for stroke studies by region. 

These findings allow us to conclude that the successful recruitment of subjects in a similar stroke study rests on the ability to identify investigators who fulfill the above criteria. 

The next case study illustrates how the recruitment information in a Phase III oncology study is modeled to forecast site numbers, recruitment timelines, CRF volume, resourcing, and endpoint occurrences. Feasibility surveys were distributed by locally trained and experienced CRA staff to a number of potential sites identified jointly by Covance and a client from past oncology studies. Investigators were provided with a confidentiality agreement followed by a protocol summary and targeted feasibility survey designed to facilitate discussions between the investigators and their local CRAs. Sites were subsequently ranked into three categories based on:  

past performances in this oncology indication

The final list of selected sites was then prepared by assessing the impact of the inclusion of each site/country on timelines. 

A projection of cumulative subject recruitment was derived from the estimated site activation times at each site within each country and the recruitment estimates provided by each investigator at each site so that the final timelines and number of sites required could be agreed upon by project team members. 

The first critical milestone for the project was the randomization of the first 80 subjects into the study so that the DSMB could review the safety data. Two projections were prepared based on the time for each site to be activated and each investigator's estimate of recruitment—one projecting the completion of the randomization of 650 subjects and the other the randomization of the first 80 subjects. As the study progressed, the actual recruitment rates at each site were used to project their own future recruitment potential. These revised recruitment rates were then used to reproject the randomization of the 650 subjects as well as the first 80 subjects; CRF flow; monitoring and data management workloads; and drug demand on a site, country, depot, and study level. 

The first subject was randomized at the end of June 2004, and by the end of August 2004 it was apparent that the 80th subject would be randomized by October 22, 2004—five weeks ahead of the original schedule. The ongoing reprojection allowed the project team to ensure that all forms were retrieved and processed in a timely manner so as to avoid or mitigate any potential delays to the DSMB review. 

Though arguably a luxury problem, the faster than originally anticipated recruitment of subjects presented a new set of challenges, specifically an increase in the demand for drugs coupled with the volume of work now being compressed over a shorter period of time. The ongoing and regular reprojection of subject recruitment on an individual site level has allowed and continues to allow the project team to ensure that there are sufficient amounts of drugs to meet the recruitment needs by shipping them to the depot and then from the depot to the site. In an extreme situation, sites can briefly and temporarily put a pause on recruitment to ensure that all subjects randomized into the study have access to the drug. 

High recruiting sites were identified and their recruitment trends observed to ensure data quality was maintained and that there were sufficient monitoring resources to retrieve the data. As a result, three sites—which had originally estimated randomizing between no more than 12 subjects per year but actually randomized 16 or more subjects within six weeks of activation—were identified and managed by capping recruitment on a site level; all three sites were also audited. It became apparent in October 2004 that the randomization of all 650 subjects could potentially be completed by the time the sites in the slowest regulatory approval country were expected to be activated. This prompted a decision in January 2005 to cancel the last Investigator Meeting, as there appeared to be little benefit in activating these sites. 

A projection of the time to all endpoints occurring (hence clinical cut-off declared) based on the actual and projected subject recruitment (see Figure 3) and the sample size calculations in the protocol was prepared. The actual number of endpoints is compared against the projected number to ensure that the timeline for clinical cut-off can be more accurately predicted and that the study is progressing according to the expectations described in the protocol. Fewer than expected endpoints occurring may result in the time to clinical cut-off being extended and more data being monitored and processed. Conversely, more endpoints than expected may result in a shorter time to clinical cut-off and less data to monitor and process.  

Figure 3. Overall projected recruitment with Confidence Intervals (CI)-a range that shows the likely range of outcome-including capping of sites/countries (date of update: December 10, 2004). 

The CRF flow and the monitoring and data management workloads are then derived from the subject recruitment and endpoint forecasts. Subject recruitment and endpoint forecasts also allow the derivation of laboratory kit volume, investigator budget payments, and drug demand. 

The need for accurate, proactive trial planning and trial delivery of high-quality data—on time and without surprises—has never been greater. The competitive environment for subjects and site resources, together with the need to bring medicines to market sooner, is driving accelerated recruitment timelines. 

Articles

Feature Article

In the age of international trials, data drives the selection of golden sites and investigators to get it right.

Data Based Predictions

Recently enacted legislation calls for federal agencies to devise a system in three years that will expand public access to data from clinical trials. That may not be fast enough for some policy makers, researchers, and drug safety advocates. A long delay in releasing less than stellar results from studies on the anti-cholesterol drug Vytorin (ezetimibe/simvastatin) has raised an outcry. And a recent article in the 

 has reignited concerns about the loss of valuable information from never published trials on antidepressants—evidence of the so-called "waste basket" effect.  

Similar issues have been fueling demand for greater access to study data to increase research transparency, reduce reporting bias, and better inform patients and practitioners about more safe and effective treatments. The study disclosure bandwagon took off four years ago when a group of leading medical journals agreed to reject articles discussing results from clinical trials that were not registered in a public database. The journal editors sought to deter sponsors from hiding unfavorable clinical data and to give reviewers access to protocols and full results as a check on accuracy. 

The policy also aimed to rebuild public trust in the biomedical research system and to provide reassurance to patients that "their altruism would see the light of day," commented Christine Laine of the 

, at a January conference sponsored by ExL Pharma. 

To further these goals, the Food and Drug Administration Amendments Act (FDAAA) enacted last September requires sponsors to register most clinical trials on the 

 Web site operated by the National Library of Medicine (NLM) at the National Institutes of Health (NIH). Previously, FDA registration was required only for drugs to treat serious or life-threatening conditions and did not include medical devices. Now more products are covered, and the listings have to provide more detailed information on each study. 

Implementing this requirement has been an enormous task for FDA and NLM. In the last weeks of 2007, new trial registrations doubled from about 250 to nearly 500 a week, as sponsors raced to meet a December 26 deadline. Some 12,000 registered studies also had to be modified to include additional data elements, reported Nicholas Ide, chief architect of the NLM Web site, at the ExL Pharma conference. The updates involve adding more information on studies (primary and secondary outcomes, start and completion dates); subject recruitment criteria; and study sites and contacts. FDA still exempts most Phase I studies from registration, but the World Health Organization does not—one of the many inconsistencies among proliferating registration requirements around the world. 

While drug trial sponsors have to post required data within 30 days of FDA study approval, the rules are very different for medical device makers. Those manufacturers convinced Congress that it would stymie innovation to disclose device study details during the investigative period. FDAAA thus prohibits posting medical device study information prior to market approval. Some large medical device companies now would like leeway to permit earlier registration, but that would involve amending FDAAA. 

There are lots of new requirements governing clinical trial listings, but the more contentious FDAAA requirement is to link study registration to resulting safety and efficacy data. Sponsors have been posting some research results voluntarily in response to the rising clamor for more transparency in study outcomes, many through a Web site launched by PhRMA (Pharmaceutical Research and Manufacturers of America) in 2004.

  The new legislation codifies and expands this activity. 

The first step, which already is in effect, links 

 registrations to public information on the resulting product. This includes FDA's drug approval package, documents discussed by advisory committees, public health advisories, NLM Medline citations of published articles, and the product's approved label in the NLM's DailyMed database. 

By September 2008, the results database also has to include "basic results" from clinical trials supporting approved products. A sponsor must provide baseline characteristics of study participants, primary and secondary outcomes, point of contact for scientific queries, and information on sponsor agreements with investigators that could restrict their ability to discuss or publish trial results. This disclosure must be made within 12 months of trial completion, which occurs when investigators stop seeing patients, not when all the analysis is done. 

The next requirement is to establish a process for including adverse event reports in the results database. FDA has to propose new rules by March 2009 for listing information on serious and frequent adverse events. If the agency fails to devise a new policy, the law reverts to a default position that requires sponsors to post most adverse events. 

The most problematic requirement is for sponsors to provide summary information on study results. By September 2010, FDA has to define how technical and nontechnical ("plain language") summaries should be constructed so as not to mislead the public and to avoid any appearance of being promotional. 

Implementing all these requirements is a "huge task," observed Terry Toigo, director of FDA's Office of Special Health Issues, at a November conference on FDAAA sponsored by the Food and Drug Law Institute (FDLI). There are different posting requirements for ongoing studies and for newly launched clinical trials, she noted, adding that a unique identifier system for FDA IND submissions and for clinical trial registration is critical to being able to link all the information. 

Regulations will have to spell out what protocol information is needed in providing full results, how quickly this additional information has to be submitted after product approval, and what kinds of disclosures would be considered false or misleading. Informed consent rules have to be revised to advise subjects about future data results disclosure, and guidance is needed on how to deal with study outcomes that differ from initial protocols. 

Although registration does not apply to most Phase I studies, it might cover early trials in patients, as opposed to healthy volunteers. It's also unclear whether bioequivalence studies for generic drugs should be registered and whether sponsors have to post study results for products that never come to market. FDA and NIH will hold public meetings and sponsor a pilot study to examine best ways to verify the accuracy and quality of submitted results data. 

Certification of compliance is a major headache. The law says that companies have to certify compliance with trial registration and results reporting requirements in applications and submissions to FDA, as well as in NIH grant applications. This is generating a vast volume of paperwork because sponsors are interpreting the policy to cover all IND supplements—they want to err on the side of caution to avoid the stiff penalties attached to violation of disclosure rules. 

Journal publication is another thorny issue. The law provides little leeway for sponsors to delay disclosure pending publication of articles stemming from a clinical trial, and journal editors are not sure how the tighter rules will affect them. Meanwhile, sponsors continue to fear that detailed disclosure will divulge proprietary research information and that the release of data out of context could raise unnecessary public alarms. But too slow disclosure in the past and attempts to sweep unfavorable results under the rug have undermined the credibility of such objections. 

Disclosure advocates believe that access to prior research data and negative results will benefit all parties and open the door to more and better meta-analysis. Innovator firms find the new requirements for establishing better trial tracking and monitoring systems may be burdensome but that such systems can improve companies' corporate compliance with global research requirements. 

Expanded federal disclosure requirements also promise to strengthen FDA pre-emption of diverse state registration requirements. However, this protection does not go into effect until national disclosure standards are fully implemented in three years, making it necessary for industry to comply with local rules already in effect, such as in Maine. 

Clinical research disclosure policy clearly has moved far away from its original purpose back in 1997: to help seriously ill patients enroll in clinical trials. The broader aim now is to ensure that research outcomes data is available to help patients and health care professionals make treatment decisions. But while transparency is a worthwhile goal, Toigo commented last fall, it's important to consider the potential public health consequence of providing this vast amount of information. 

1. Erick Turner et al., "Selective Publication of Antidepressant Trials and Its Influence on Apparent Efficacy," 

, 358 (3), 252–260 (January 17, 2008). 

2. Pharmaceutical Research and Manufacturers of America Web site: 

View from Washington

FDA, NIH, and sponsors all struggle to implement complex registration and data access requirements.

Research Disclosure Rules Raise Questions

A common document at many clinical sites is the memo or note to file (NTF). When used properly, an NTF can be a positive practice. A useful NTF has the following parts: A problem is identified, a procedural change is identified for preventing recurrence, and this procedure is then instituted. In the event of an FDA or other regulatory inspection, the inspector may still leave a citation for the initial problem, but the change in procedure mitigates the citation and provides the site with a strong response to the finding.  

	Some in the clinical trials community, however, seem to think an NTF is a panacea for all things that have gone wrong. Make a mistake? Then write an NTF and stick it in the regulatory binder or subject case history. The practice has become so ubiquitous that new CRAs and study coordinators sometimes think that they are a regulatory requirement. But this is a misconception. There is nothing in FDA's regulations or guidance documents that requires sponsors and clinical sites to use NTFs. Nothing.

	And many think that an NTF indicates a corrective action-with a quick one written without regard to correcting the problem. Sometimes, NTFs are even generated well after the deviation has occurred and all is considered right with the world-this isn't the case. In fact, FDA recently reprimanded a sponsor for after-the-fact memos.

	In a Warning Letter dated October 23, 2007 (

www.fda.gov/foi/warning_letters/s6551c.htm

), FDA wrote: "Our investigation found (the sponsor) failed to take any action except to generate numerous memos to file after all the subjects completed the study." The Warning Letter then noted at least 89 memos were generated after a monitoring visit. Instead of writing NTFs, the sponsor's time is better spent qualifying the site and training study staff.

	Documenting a mistake means absolutely nothing during an FDA inspection. What requires documentation is the corrective action taken and whether the action worked. If an effective quality system is in place prior to subject enrollment, then the sponsor, monitors, investigator, and study staff will each understand how the study will be monitored and how discrepancies will be communicated and corrected. Sponsors cannot depend on postmonitoring visit letters to secure compliance in serious situations.

	During my own auditing experience, I have noticed that NTFs are frequently a contentious issue between monitors and study staff. I have seen trivial NTFs placed in regulatory binders at the request of inexperienced monitors. In addition, some study coordinators have developed a habit of writing NTFs instead of developing good recordkeeping practices. All an NTF accomplishes is documenting poor performance. And ineffective work seldom impresses FDA. 

	Clinical trials are hard work and require professional cooperation to quickly address queries and genuine findings that need correcting. Once an NTF is written and becomes a study record, it cannot be retracted. The result is a lose–lose situation for everyone. These NTFs are a road map for any inspector and air all of the site's faults.

	A better solution is to develop a quality system from the clinical study's beginning that includes training on monitoring and data correction that everyone understands. Sites should document the actual corrective action and keep NTFs few and far between.

Senior Consultant Biologics Consulting Group, Inc. email: 

A Closing Thought

Carl Anderson, senior consultant for Biologics Consulting Group, addresses the frequent overuse of Notes to File and concludes that documenting a mistake means absolutely nothing during an FDA inspection.

Note to File (NTF) is Not an FDA Panacea

The start of 2008 has brought new moves to make a reality out of the European Union's rhetoric on promoting genuinely pediatric medicines. Just one year into the new regime that requires companies to file special pediatric clinical trial plans with virtually all new products, the results are already starting to show through—not yet in terms of products validated for pediatric use, which will understandably take a little longer. But it is making real progress in terms of a functioning system that should, eventually, improve health care for kids, as well as providing some new challenges for the clinical trials community.  

In line with the deadline set by the new rules, companies are now routinely submitting pediatric investigation plans—programs aimed at generating the necessary quality, safety, and efficacy data through studies in pediatric populations to support authorization of the medicine for use in children. 

The work of the Agency's newly established scientific committee to review pediatric questions is now getting into full swing with regular monthly meetings. At its January 2008 meeting it adopted initial opinions on pediatric investigation plans for four products—Pfizer's Latanoprost, in ophthalmology, and three Merck Sharp and Dohme products: Losartan, in cardiology; Montelukast, in pneumology; and Caspofungin, for infectious diseases. 

For obvious reasons, not all new products are required to submit a pediatric investigation plan. Already, at the end of 2007, the Agency issued a class waiver for treatments for a long list of conditions that hardly or never occur in children—ranging from breast carcinoma, menopausal disorders, age-related macular degeneration to Alzheimer's Disease, vascular dementia, and amyotrophic lateral sclerosis. 

Companies can also apply for individual exemptions from the requirement to conduct trials in children for individual products that are not on the 2007 list. At its January meeting, the Agency decided to accord a product specific waiver to Pfizer for lasofoxifene tartrate (for the treatment of osteoporosis in postmenopausal women at increased risk of fracture) on the indisputable grounds that the disease or condition for which the product is intended occurs only in adult populations. 

This is the fourth such product specific waiver to be granted, and follows Novartis Europharm's Everolimus for renal cell carcinoma and pancreatic neuroendocrine tumor (exempted on the same grounds as the Pfizer product) and AstraZeneca's Atacand Plus and Takeda's Blopress—both for essential hypertension—on the grounds the products do not represent a significant therapeutic benefit over existing treatments for pediatric patients. 

A number of further key deadlines were reached at the start of the year. Some of them were geared toward maximizing information available to authorities on the current status of pediatric trials. By the end of January 2008, for instance, holders of marketing authorizations were obliged to file information on all pediatric studies they had completed by the beginning of 2007, when the new legislation came into force. 

There is also now an ongoing obligation on marketing authorization holders to submit details shortly after they complete any other studies they sponsor on products used in the pediatric population. And EU guidance has now been provided on the type of data that EU member states have to start collecting on existing uses of medicines in the pediatric population. This will allow them to communicate it to the Agency by January 2009 as part of the efforts being put into establishing a list of priority pediatric needs. 

The Agency is also working on an updated priority list for studies into off-patent medicines to ensure that funds from a new round of EU research support will be directed into research for which there is a high need in the pediatric population. 

During January, the European Medicines Agency (EMEA) also agreed to a strategy for setting up the pediatric network envisaged by the new legislation. This is intended to embrace all the national and European networks or centers currently focused on pediatric studies, so as to build up competences and cooperation at the European level and to avoid duplicative studies. The aim is not only to benefit the pediatric population but also to provide a source of information and expertise for industry. 

To match the legislation's overall aim of fostering high-quality ethical research on medicines to be used in children, the network intends to strengthen scientific, technical, and administrative competences in performing pediatric clinical trials; to make more efficient and profitable use of facilities; and to develop common methods of working, particularly to boost quality assurance. In addition, the network could help in patient recruitment. 

Some of the tangible outcomes scheduled to emerge from the process include scientific and operational quality standards, training and education standards, scientific exchanges, and specific research on trial methodology. 

To put the new European network into place rapidly, a coordinating group is to be set up within the EMEA consisting of representatives of pediatric centers and networks in Europe, patients or parents, and ethics committees, as well as academics and EU officials. It is expected to maintain strong links with other expert groups already established by the Agency on good clinical practice in clinical trials, GCP inspections, and pharmacovigilance. 

The start of the year has also been marked by a remarkable echo from the past. In January, the EMEA recommended the marketing of a product with an active ingredient so damaging on its first appearance a generation ago that it triggered much of the European medicines legislation that has appeared in the last 30 years. Thalidomide, which caused serious birth defects in the children of women who took it during pregnancy as an antinauseant, is now on the brink of being launched by a UK company, Pharmion, for the treatment of multiple myeloma. 

The renaissance of this medicine is a compelling testimony to the increasing sophistication of clinical trials. The Agency concluded that the benefits of the product, in combination with melphalan and prednisone, outweigh its risks for the first-line treatment of multiple myeloma for patients over 65 years of age or who cannot be treated with high-dose chemotherapy. It was satisfied that clinical studies have shown that adding thalidomide to such a combination can prolong survival time by about 18 months in newly diagnosed multiple myeloma patients over 65 years of age, as compared to patients who received conventional chemotherapy. 

However, because the drug is teratogenic, the Agency consulted representatives of thalidomide victims and myeloma patient groups from across the EU to develop measures that can effectively minimize the risk of fetal exposure. It has approved a risk management plan that includes actions intended to prevent pregnancies in women being treated with thalidomide and prevent exposure of unborn children to the medicine. For example, all women of child-bearing age who are treated with it must undergo pregnancy tests before, during, and after treatment, in addition to using selected and effective contraception. 

Treatment will be initiated and monitored only by a doctor who has experience in the treatment of multiple myeloma, and a clear warning will be printed on packs indicating that the product results in birth defects and fetal death. In addition, prior to launch in each member state, the company will provide health care professionals and patients with educational materials about the treatment-related risks and the precautions required to ensure safe use. 

 is a freelance journalist who specializes in European health affairs and is based in Brussels, Belgium. 

View from Brussels

Some of the tangible outcomes expected to emerge from a pediatric network include scientific and operational quality standards.

Making Reality of Pediatric Rhetoric

Industry sponsors have long focused their attention on accelerating cycle times and on reducing drug development inefficiencies. There is no shortage of opportunities to streamline activities—from protocol design to CRO and site identification, to subject recruitment and statistical analyses—inefficiencies abound. But up until now, attention and initiatives aimed at achieving efficiency improvements have centered on activities within drug development phases. Scant attention has been paid to the breakdowns that occur as clinical data and operations transition from one research phase to the next. As such, between-phase inefficiencies may offer new opportunities for biopharmaceutical companies to accelerate drug development cycle time, improve overall performance, and lower costs.  

The impact of between-phase improvements in efficiency could be substantial. Between development phases, there is no defined timeline in which key decisions have to be made. The treatment period is fixed within a given research phase. As a result, the opportunity to drive efficiency within phases is limited by the amount of time it takes to run a study. 

Transition efficiencies between phases also may be easier to achieve, as they are largely controlled internally. Within-phase efficiency gains rely heavily on improvements in relationships with external service providers—a more difficult area to glean process improvements. 

Based on discussions with drug development executives in pharmaceutical and biotech companies, there are three broad opportunity areas to streamline inefficiencies during phase transitions. These between-phase opportunities are inextricably linked and play a critical role in driving success within drug development phases. The three areas are:  

According to the executives interviewed, transitional inefficiencies are in large part due to mistakes drug developers make in gathering inappropriate and incomplete inputs into decision making late in the process and in failing to anticipate downstream needs. Also, companies fail to build the appropriate level of internal consensus and alignment around key decisions. 

"The Phase I to III mentality is a hindrance to efficiency by keeping drug developers thinking more about the means than the end," says Evan Loh, MD, vice president of clinical research and development at Wyeth. "Companies generally know the goal but fail to provide the necessary input to optimize decision making according to specific deliverables. Lacking that, companies may face an interpretation nightmare trying to decide if a compound is or is not fit to move forward." 

External inputs are cited as particularly important to phase transitions. "Unnecessary delays can occur between phases if external input into decision making from scientific leaders and regulatory agencies is not sought early, when the trial is being designed," explains Mark Bach, MD, PhD, vice president of worldwide clinical research operations for Merck & Co. "If a company wants to register its drugs globally, then misunderstandings about the regulatory environments in various parts of the world can cause delays." 

Several executives suggest that companies are seeking more input from and expending more time on regulatory agencies during phase transitions as a way of managing risk. "Time spent on between-phase interactions with the FDA on special protocol assessments has been escalating while the scientific advice process of the European Agency for the Evaluation of Medicinal Products continues to take the same length of time," says Alison Lawton, Genzyme's senior vice president of global regulatory affairs, global policy programs, and corporate quality systems. 

A number of interviewees noted that the uncertainty around reconciling multiple and diverse scientific and regulatory input adds another element of inefficiency. "There is no commitment by regulatory agencies to offer joint advice," explains Dan Bollag, Genzyme's vice president of regulatory affairs for biosurgery. "We literally have to make a formal appeal to each agency." 

Executives from several drug companies report that often their early phase studies are designed without later phase study programs in mind. As a result, frequently their companies have had to resort to modifying and expanding later-stage programs to cover for areas missed earlier. 

"When it's necessary to look at Phase II results before designing a Phase III study, the key challenge is to do neither too much nor too little advance preparation," explains Bollag. "Research sponsors usually go to one of two extremes: They may not do any thinking about Phase III until all Phase II data is on their desk, or they may spend a lot of time figuring out what Phase III trial to do and implement regardless of what the Phase II data tells them." 

Executive interviewees most often cite the challenge of analyzing and interpreting the clinical data correctly. Failure to do so between phases can have downstream repercussions. 

"The speed that companies achieve in making internal decisions between phases depends heavily on the quality of information obtained during earlier trials," says Mike Friedman, senior director of biostatistics at Genzyme. "A failed Phase III trial can be at least partially caused by collecting the wrong information or an insufficient amount of data in Phase II." 

"If companies look for something greater than 'x' and get something less than 'x,' that allows for more interpretation and shades of gray," says Wyeth's Loh. "Unexpected outcomes can't be controlled, but they can be anticipated so that sponsors don't get blindsided or start applying post-hoc caveats to study data to justify the leap into the next study phase." 

A key to minimizing phase transition inefficiencies lies with anticipating where problems will occur, developing contingency plans, and responding proactively. Doing so cues up organizational resources to handle situations as they unfold. 

"Operational preparation involves laying the groundwork for studies at risk. Failing to do so could result in wasted time and effort," says Merck's Bach. "The advantage is that you're prepared to make a decision the moment the study data arrives." 

According to Loh, when it comes to Phase III, the right type of drug supply can be a huge time saver. "It's vital that large, treatment-testing studies utilize a commercial formulation of a drug throughout its duration so there's no question about bioequivalence. But manufacturing that formulation can take months or even years," he says. "Ideally, the organization has to begin planning its commercial formulation before initiation of later stage pivotal trials." 

Several interviewees noted the importance of coordinating ethics committees and boards of health dispersed widely around the globe. "Review and approval times vary widely from country to country," explains Loh.  "The FDA has a 30-day review cycle, but in countries like Latin America and Asia, approval times are nine to 18 months. Some countries are not going to participate if a sponsor wants to complete the trial in under a year. If Japan, China or India is left out and the sponsor wants the drug approved there, it will need to conduct a separate trial just for that country in order to gain regulatory approval," he said. 

There is wide consensus among executive interviewees that the hallmarks of rapid and efficient between-phase development activity include: more effective, timely, and informed decision making and consensus building; appropriate and comprehensive inputs and forward-looking data analyses and interpretation; anticipatory and contingency planning. Wider adoption of information technologies and clinical data interchange standards and the use of flexible trial designs also are noted as drivers of phase transition efficiency. 

"Information technology has certainly sped up post-trial data analysis," says Genzyme's Lawton. "Continuing industry-wide work on data interchange standards will further streamline global regulatory agency data review and sponsor-agency communications." 

Loh notes that Wyeth's two stage "Learn and Confirm" approach to drug development helps mitigate between-phase inefficiencies in the traditional development process: "Efficiencies are gained by doing better planning up-front, and this allows us to use other methodologies in the learn phase to get answers quickly—such as adaptive trials and adaptive randomization." 

"Historically, the goal of research was to develop drugs that regulatory agencies will approve, and the goal of marketing was to develop drugs that consumers and physicians want to use. But these goals need to be better aligned. With adaptively designed trials, these kinds of decisions can be made earlier in development, possibly avoiding between-phase time," says Merck's Bach. 

"Adaptive clinical trials, particularly seamless Phase II/Phase III trials, will help reduce the down time in the future in terms of eliminating some discussions with the FDA and the volume of institutional review board approvals," adds Lawton. 

The onus is on drug developers to reduce inefficiencies between phases. And the impact of doing so benefits not only program timelines and costs, but also—and perhaps more importantly—the quality of the product label. 

 MBA, is a Senior Research Fellow at the Tufts CSDD and Chairman of CISCRP, both in Boston, MA, email: 

Clinical Trial Insights

Today's sponsors are waking up to the fact that changes made between phases can positively impact R&D.

In Search of Efficiency Between Trial Phases

Slow subject recruitment and poor retention are perpetual problems for the pharmaceutical industry. According to industry estimates, delays caused by recruitment affect most studies and end up costing hundreds of thousands to millions of dollars. Biopharmaceutical companies concerned with achieving their Last Patient In (LPI) targets should focus on making their subject recruitment and retention strategies, planning, and execution far more effective through a combination of technology, data assets, and process changes. Through appropriate use of technology platforms to bring together disparate information from across the organization, biopharmaceutical companies can better predict and manage recruitment and retention through data-driven frameworks.   

Access to the right data allows trial sponsors to more accurately address three vital questions about subject recruitment:  

What are the likely enrollment rates for a particular clinical trial?

How will known development issues, such as staggered study startup and holiday periods, impact my LPI milestones?

Who are the best investigators to achieve the required recruiting objectives?

Information concerning the feasibility or difficulty of subject recruitment for specific types of subjects, indications, and sites directly impacts the accuracy of projected enrollment rates. By identifying appropriate data assets to support feasibility studies and site selection, sponsors can make the right decisions about trial staffing, budget, and timelines and positively impact subject recruitment. 

Feasibility should be driven by a triangulation process involving three major elements:  

previous recruitment results from similar trials (internally generated or via literature reviews)

A database of previous experiences that includes key information such as eligibility criteria, study synopses, and enrollment rates by country are critical to determining the relevance of a previous trial's results on the current trial. An analysis of the similarities between eligibility criteria, the drug, procedures, and standard of care can be used to modify the enrollment rate of the previous trial to approximate what can be expected in the new study. 

This internal data can be augmented with published literature, particularly in areas where there is little relevant experience within the company and/or in indications where a substantial number of similar trials have been published. Most published studies provide enough data to allow for an approximate enrollment rate to be developed, but they tend to play a secondary role due to the lack of detailed information around enrollment time frames at the site level or specific eligibility criteria that is needed to develop a more refined estimate. 

Data from previous trials can be used as part of a formal analysis process, conducted by internal and external experts. These experts should have a firm grasp of the standard of care in each relevant country (past, current, and medium-term future) and the clinical trials environment, and they should also have access to epidemiological data. Through the combination of these elements and the historical trial data, a reasonably tight range of most likely enrollment rates can be developed. 

Finally, this process should be compared to the results of a survey of potential investigators in each relevant country. This process is typically blinded and asks relevant questions about such topics as likely enrollment rates, IRB/EC issues, and other factors that may influence the conduct of the trial. This process plays a critical role in refining the analysis described earlier and identifying potential high enrollers. A reduction factor, however, must be applied to the enrollment results from the sites to account for the lack of complete data about the trial, lack of time for site staff to carefully think through the survey, and the level of irrational exuberance that's typically contained in the responses—a 50% reduction of the enrollment estimates is often appropriate. 

This entire process should be coordinated by a central group that is separate from the trial team. This allows for both process flow management efficiency and a level of dispassionate estimation that is critical to accurate planning. 

Accurate data is absolutely essential to planning and management, but it is only one part of the equation to improve subject recruitment performance. A sponsor must also have the appropriate data modeling and management tools in place to leverage the data. Inappropriate modeling tools will fail to account for enrollment variables that affect every trial. 

Sponsors should leverage widely available technology (e.g., Excel) to develop comprehensive analytic tools that allow for realistic predictions to be made and that also enable changes in the environment or the clinical plan to be quickly incorporated into decision making. Combined with accurate historical data, models can be created that recognize important recruiting variables, such as:  

Differences in enrollment rates among countries, sites, and investigators

Variations in time to first site live by country

Variations in time to 20%, 40%, 60%, 80%, and 100% of sites live by country

First "month" of enrollment that is not a full 30 days

Impact of seasonal variations, holidays, site fatigue, and database effects on recruiting rates.

As the case study in Figure 1 shows, use of a recruitment modeling tool can lead to a much more accurate estimate of enrollment. The assumptions in the Request for Proposal (RFP) included both a straight-line extrapolation of enrollment as well as an unrealistic recruitment rate. When these assumptions were retrospectively run through a recruitment modeling tool with a more realistic recruitment rate, it was determined that half of the six month gap between the desired LPI date and actual LPI date was due to the use of inaccurate recruitment modeling. The other half was due to the use of a less than realistic recruitment rate. Developing an accurate estimate required both improved modeling and a more robust estimate of recruitment rates.  

Figure 1. With the right modeling tools in place, sponsors can more accurately identify variances to recruitment goals. 

To improve subject recruitment performance, the industry must also rethink its use of investigator databases, which typically contain little more than contact information, previous trial participation, and areas of therapeutic specialty. Choosing the right sites is particularly critical given that analyses show 80% of subjects typically come from the top 20% to 30% of investigators across a range of therapeutic areas and countries. By using a more data driven approach to choosing investigators that includes previous enrollment performance (relative to peers), external data, and quality metrics, it is possible to identify high potential investigators that are much more likely to be top sites that will drive recruitment for the study. 

For instance, a recent analysis of 371 Phase III studies demonstrates the importance of picking the right sites. For an average size Phase III study (10 months of enrollment and 73 sites), replacing the seven bottom-performing investigators (10%) with investigators that match the performance of the top 10% reduces overall enrollment timelines by 25%—or 2.5 months. The impact that can be generated by a relatively modest change in sites is clearly substantial. 

For many sponsors, the data for this type of analysis can often reside in many different systems (e.g., Clinical Trial Management Systems, IVRS, and project manager spreadsheets). A cross functional team may be required to reach out to these various systems to develop a clean and accurate profile of investigator performance on previous studies. While the effort associated with these types of aggregations is substantial, it can generate enormous value in selecting high performers and reducing enrollment timelines. 

Bringing together these various planning and management tools allows sponsors to begin moving away from a reliance on rescue contingency plans that are implemented only after subject recruitment issues develop. By building proactive contingency plans with predefined triggers into core development programs, months of delay and costs can be saved by detecting signs of trouble well before they become major issues. 

For contingency planning to be maximally effective, it is critical to develop early warning analytics, ideally connected to the modeling tools described. These analyses should be driven not only by recruitment results but also by variances to planned study startup timelines, screening/enrollment rates, and average speed for sites to begin enrolling their first subjects. These factors can provide early evidence of delays long before they are typically spotted using only recruitment results. 

In addition to ongoing analysis of results, effective contingency planning requires implementing small but critical seeds at the outset of a study. These can include identifying/qualifying backup sites, developing explicit escalation plans for underperforming sites, and getting subject outreach materials approved by IRB/EC. By implementing these activities at the beginning of a study, time and money can be saved if enrollment results lag. 

The project manager or trial leader for the study—with input from medical and clinical staff—is often best placed to develop the overall subject recruitment plan and to identify the appropriate contingency triggers. The recruitment plan should incorporate both the current situation as well as multiple levels of contingency activities based on the potential need. Resources required, lead times, and expected impact should be part of this plan to allow for thoughtful and timely implementation of contingency activities. Finally, the recruitment plan should be viewed as a "living document" that changes frequently over the life of the study as the environment changes and as more data is available (see Figure 2).  

Figure 2. Contingency-based escalation is predicated upon incorporating preparatory activities into the core plan. 

A recent case study of a multiprotocol diabetes program illustrates the contingency management concepts described earlier. To maximize the chances of achieving LPI milestones, the initial steps of a range of recruitment support tactics were implemented, including IRB/EC approval of subject outreach materials, identifying back-up sites, developing/communicating site-level escalation plans for nonperformance, and building site support plans (such as provisioning rapid screening kits and subject travel stipends). These initial activities were inexpensive and were done in parallel with protocol development and study startup activities. 

Using the scenario planning capabilities of a recruitment modeling tool, it was determined that regulatory and other delays during the start-up period were generating unacceptable risk to the LPI milestones. Given the value to the sponsor of achieving these timelines, a decision was made to fully implement the contingency activities that had been previously put in place. Because of these early preparations, it was possible to launch backup sites, nonperformer escalation plans, and subject outreach in a fraction of the time it would have taken—leading to a rapid improvement to the recruitment situation. 

Overall, with the right data and tools, sponsors can more accurately predict, monitor, and manage subject recruitment, while avoiding expensive and risky trial delays. The result of investments in better data assets, recruitment modeling tools, and feasibility/management processes can be leveraged to reduce costs and bring new products to market faster—improvements that are invaluable in today's highly competitive pharmaceutical marketplace. 

, is vice president, patient recruitment, clinical research services, Parexel International, 200 West Street, Waltham, MA 02451, email: 

Effective contingency planning requires implementing small but critical seeds at the outset of a study.

Applied Clinical Trials-03-01-2008

Data Based Predictions

Research Disclosure Rules Raise Questions

Note to File (NTF) is Not an FDA Panacea

Making Reality of Pediatric Rhetoric

In Search of Efficiency Between Trial Phases

Improving Subject Recruitment