A new study by Premier Research shows that both American and European pharmaceutical companies are facing similar problems in regards to pediatric trial regulations. The number one concern for both? Patient recruitment.  

The study, which surveyed 55 companies, revealed that patient recruitment may be suffering because of the lack of children available who meet study guidelines. In fact, over 70% of US respondents indicated that finding enough patients for Pediatric Research Equity Act (PREA) studies is difficult. 

 asked Charli Sanders, MD, Premier Research Vice President, Regulatory Affairs and Pediatric Consulting, how a company can go about improving patient recruitment. 

"One thing that companies embarking on pediatric studies ought to do is to evaluate the customs, cultures, and healthcare access patterns of the pediatric populations they intend to enroll," Sanders said. "Alternatively, they should select a partner—such as a qualified CRO—which can do such an evaluation for them." 

Sanders also noted that companies should remember that matching patient profiles to the clinics and countries where the trials are conducted is essential to the success of a study. 

Another option for trials that have only a few available subjects or with a long enrollment period is "pooled population study." 

"The value of such studies is that they are able to rationalize scant data derived from seemingly unrelated sets of pediatric patients exposed to the same product. This methodology pools the data, which are analyzed together to construct a pediatric profile for a specific product," Sanders said. 

Although studies with larger subject numbers would be preferable, these computer-based results can also deliver informative data. 

In addition, the Premier Research survey showed that companies faced other challenges besides patient recruitment such as general confusion about PREA rules in the United States, as well as the Pediatric Regulations' Pediatric Investigation Plan (PIP) requirements in Europe. 

Seventeen percent of US respondents do not understand PREA, about 60% said they "somewhat understood" PREA, while an alarming 10% never even heard of PREA, which has been around since 2003. 

And results were little better across the pond. According to those surveyed from Europe, two in 10 said they do not understand PIP, only 55% said they "somewhat understand" PIP, and 6% claim they never heard of PIP. 

To counteract this problem, Sanders recommends that companies begin looking at PREA and PIP guidelines earlier rather than later. 

"Because many companies don't fully understand the process, delays occur," Sanders said. "Obstacles frequently have less to do with the regulations themselves than how companies are set up to handle the global demands that these pediatric regulations make, both financially and in terms of time management." 

For those who are still baffled by the pediatric guidelines, Premier Research has conducted a series of webinars about pediatric clinical research which are available on their website at 

. The company has also issued the first of two white papers regarding pediatric trials for further background. 

But just how important are these regulations to companies anyway? In the United States, 36% said complying with PREA is a moderately high priority, 12% relatively low priority, and 52% noted it as a high priority. Results were similar in Europe, where 26% placed pediatric regulations as a moderately high priority, 4% admitted it was a relatively low priority, and 54% said they made it a high priority. 

Other key takeaways to note from the survey are that about one-third of users did not realize they could revise their PREA obligation by working with FDA. 

"For that expressed reason, we recommend an initial consultation," Sanders said. "When appropriate, it also may be helpful to invest in pediatric pharmacometric work up front that could potentially eliminate the need for more expensive and elaborate clinical trials down the line." 

About half of respondents in the United States and Europe said that PREA and PIP guidelines have forced them to increase R&D budgets. And almost all surveyed in both the United States (92%) and Europe (90%) agreed that having an independent analysis of the company's' PREA or PIP obligation would save time and money. One major difference between Europe and the United States? Europeans (68%) believe securing PIP waivers or deferrals should be easier, compared to 39% of Americans surveyed. 

To see more results from the survey, go to 

Benefit from industry updates and case studies related to this article at CBI’s Workshop on Pediatric Investigation Plans, September 20-21, 2012, Boston, MA 

Articles

News

A new study by Premier Research shows that both American and European pharmaceutical companies are facing similar problems in regards to pediatric trial regulations.

Survey Reveals Patient Recruitment is the Biggest Challenge in Pediatric Trials

ACT Cover

Managing clinical trial agreements with hospitals and investigators can be quite a challenge, especially when dealing with a large multi-country study. Many different parties are involved in the process and you have to deal with a variety of laws and regulations, languages, cultures, social and historical backgrounds, and different local or even regional customs. 

Lack of knowledge and experience in the above-mentioned areas may result in a substantial delay in the contract management process and, as it appears, in the overall clinical trial process.  

In surveys conducted by CenterWatch, investigational sites indicated that contract negotiations were considered to be among the top delaying factors when performing a clinical trial, both in Europe and the United States.

  Interestingly enough, when asked in the CenterWatch survey about solutions to avoid delays, none of the participating sites mentions improvement of the contract management process, which could be perceived as a "necessary evil" rather than an opportunity for process improvement and eventually for an increase of quality and reduction of costs.  

Since there is not much data available on the general experience on and understanding of this topic from the clinical research industry (i.e., pharmaceutical companies, biotech companies, and contract research organizations), a survey was conducted by Salvius Legal and 

Although budget negotiations are related to the contract negotiations with the sites, and thus fall in the category of potential delaying factors in the clinical research process, the focus of the survey and this article shall remain limited to the actual contract negotiation of the legal terms.  

The survey was conducted by sending an e-mail to subscribers of 

inviting them to fill out the questionnaire online, which resulted in 534 completed questionnaires. The respondents consist of a well-balanced mix of representatives, mostly from the clinical departments of companies ranging from small to very large CROs, pharmaceutical, biotech, and other companies or organizations. 

 Half of the companies and organizations are located in a single country, the other half in more than one country; however, 65% of the respondents operate in multiple countries across the globe. The group of respondents consists overall of a very solid representation of parties in the industry dealing with clinical trial agreements at an international level. 

Given the current economic situation and cost developments in the industry, it seems only appropriate to start with a short reflection on the relationship between clinical trial agreements and costs. Clinical trial agreements potentially influence the costs of a sponsor of a clinical trial in several ways. First, a poorly drafted and/or negotiated agreement can create legal risk exposure, which in turn could result in unexpected financial liabilities. Second, inefficiencies in the negotiation process can result in unnecessary additional costs associated with extra man-hours. Third, and possibly most serious, troublesome contract negotiations may delay a clinical trial and, in effect, delay the marketing of the investigational drug, resulting in severe loss of profit for a sponsor.  

Clinical trial agreements are generally considered low-risk agreements, presumably because parties operate in a strongly regulated environment and the framework and requirements regarding the performance of the clinical trial are for a large part set in the protocol. In addition, parties have a scientific and ethical reputation to uphold, and therefore are not very likely to agree to terms that may jeopardize such reputation. 

However, site agreements in which reimbursement clauses were not properly drafted do exist. Consequently, hospitals were able to claim costs that are not a reasonable responsibility of the sponsor to reimburse. Additionally, and often even more damaging, poorly drafted agreements may result in inadequate confidentiality and intellectual property clauses. If, for instance, a hospital is under no obligation to ensure that its study staff comply with the confidentiality obligations in the agreement or transfer any rights to the study data and inventions potentially arising from the trial to the sponsor, a serious impact on the sponsor's competitive edge could result in a considerable loss of profit.  

The above should be put into perspective: If there is an opportunity in the agreement to "sabotage" a clinical study, it does not mean that this will actually happen. Investigators and hospitals are usually not focused on finding openings in the agreement to the disadvantage of the sponsor. Also, if there is a breach or problem, the parties will usually be more interested in settling in good faith, in order to avoid negative publicity or the risk that future collaboration will be severely jeopardized.  

Notwithstanding the above, 9% of the respondents of the survey indicated that their respective companies have been in a situation where damages were caused to their company or other parties involved in the clinical trial because the contents of the site agreement were not properly negotiated  and over 6% indicated that their company has been involved in a legal suit or action in which the contents of the clinical trial agreement was considered crucial for settling the suit or claim. Although it is clear that serious issues arising from poorly drafted site agreements are rather an exception than the rule, the results of the survey indicate that these exceptions should not be neglected. 

Inefficiencies in the site contracting process have an influence on the costs of a clinical trial as well. Insufficient training, poor communication skills, and unclear processes can all result in drawn out communications between the parties or a duplication of work. Too many hours spent on a task and unnecessary delays are the result. 

As mentioned, sites experience the contract negotiations as a top delaying factor. From the survey it appears that industry representatives also perceive it as the most important cause of delay in the clinical trial process (Figure  1). Most of the respondents indicated that contract negotiations usually take more than six weeks, but a large part also indicated longer than 12 weeks, and some even more than four months. Whether the contract negotiation period actually causes a delay will ultimately depend on how long other clinical trial start-up activities are taking, since contract negotiations usually run in parallel. However, it clearly is the perception and experience of the parties involved that this part of the clinical trial process takes longer than it should. 

So why doesn't this part of the clinical trial process get the attention it deserves? Maybe the required experience and skills—legal, operational, and organizational—are often underestimated. In order to ensure good quality, consistent, and quick site contract negotiations, it is important to put in place clear processes, good-quality documents, and well-trained and experienced staff with solid communication and organizational skills. Contract negotiations will always be a part of the process that most operational staff consider as inconvenient but necessary, and even the best contracts management team cannot prevent negotiations taking a certain amount of time. However, negotiation times can be reduced by following the right approach and acknowledging what is required to achieve this. 

When looking at costs associated with delays of a clinical trial, it becomes even more urgent to consider whether your company is taking sufficient action to avoid such delays. Everybody working in the industry is aware of the enormous costs of developing a new drug. Costs for delay of a clinical drug trial are estimated to be on average $1.3 million per day.

Being aware of this fact makes it easy to conclude that each day saved on contract negotiation time, may save a pharmaceutical or biotech company substantial amounts of money.  

Country- and industry-specific knowledge.

 Delays often occur because of a lack of knowledge on applicable local laws and regulations, as indicated by the respondents of the survey. There are situations where lawyers insisted on trying to negotiate certain clauses in the agreement that were an exact copy of what was stated in the law or that would be overruled by imperative local legislation. 

The different cultural backgrounds and local customs are also factors to be taken into consideration for the planning and approach of the negotiations: it is for instance helpful to know that in the months of July and August, it can be very difficult to progress negotiations in a majority of the countries of Southern Europe, because of the long vacation period. 

Besides the local specifics, a contract manager should also be fully aware of the actual clinical trial process and the differing risks involved with different types of trials. Such awareness is necessary so that a proper risk assessment can be made and a pragmatic approach applied. If a certain situation is very unlikely to occur in a clinical trial, and even if it occurs, presents minor disadvantages, it is not necessary to insist on language that deals with the situation. Also, a contract for an observational trial, for instance, has a different risk level compared to a contract for an early phase clinical trial.  

 The respondents of the survey indicated that site agreements are usually dealt with by internal staff of the concerning company: internal lawyers, internal contract managers, the clinical department, but also administrative staff (Figure 2). Legal staff usually deal with the review of actual legal terms. Contract management, administrative staff, and sometimes members of the clinical department review agreements to the extent such relate to administrative changes or are based on pre-agreed fallback provisions, and are responsible for tracking and organizing the agreements. The clinical team is usually serving as the direct liaison with the hospital and the investigator.  

It is clear that where site contracting is not managed properly it may result in unnecessary risks, inefficiencies, and delays. Therefore, it seems only logical to ensure that for this part of a clinical trial, sufficient, qualified staff, possessing the required skills and experience, are made available. This is apparently a challenge, since the respondents of the survey indicated it is not easy to find qualified staff (Figure 3). However, the workload in this area can fluctuate considerably, which makes it difficult to always have sufficient and trained staff available. 

It is in that sense interesting that only a few respondents of the survey use external resources for dealing with site agreements, since it could offer flexibility and the required expertise when needed. It could be the case that parties have the idea that contracting for such external expertise is too expensive (the average hourly rate paid for this service seems to be between $200-$300). Granted, if the external party delivers a poor service—rigid lawyers that do not have the industry experience and do not share the same sense of urgency that is usually associated with these agreements—it can add substantially to the costs without providing the required benefits. However, if the external party can truly contribute to the improvement of the timelines, efficiencies in the process, and quality of the contracts, it can save money for the company.  

Either way, qualified contract management resources are worth investing in, whether contracted or employed. The respondents of the survey seem to realize this; they opine that involvement of contract management specialists with a solution-oriented, pragmatic approach and with experience in the industry could improve the process.  

Clear processes, training, and communication. 

Well written contract templates, logical processes, and consistent, good quality contract reviews are important if a company wishes to reduce risk, inefficiencies, and delays; also if a company desires some control over the documents it signs and has an interest in maintaining the image of a professional and reputable organization. 

 Therefore, besides the availability of quality resources, it is important to ensure that clear processes are established and proper contract management tools are available. A tracking program, fallback provisions, a "previously approved language" list, and review guidelines that clearly define the responsibilities of the different parties will contribute to the above described objectives, as also indicated by the respondents of the survey. 

 Of course the processes and tools will only work if the parties involved are properly trained. The training should also include good communication guidelines and skills; the lack of proper communication is considered as a bottleneck in the contract management process by the respondents of the survey (33%) (Figure  4). 

In order to evaluate the processes and identify bottlenecks and stagnations in the process it is important to track the progress of the negotiation. There are many reasons why delays occur, and many of them can be avoided if the cause of the delay is known. Lack of clarity on who is responsible to move things forward at a certain stage, too high a workload of the parties responsible for the negotiation process, or a contract slipping through the net can all create delays, but if identified in time while tracking the progress and followed-up by the correct action, it will be possible to minimize the consequential delays. Keeping metrics of the turn-around times can also assist with setting the right expectations with the different parties involved, and help with realistic planning. 

Apparently, however, many companies do not have an official, solidly working tracking system or follow-up processes in place. The survey shows that most of the respondents are not using an official tracking system but are using simple methodology such as an Excel sheet. Not quite half of the respondents indicated that they keep metrics on turn-around times. There is obviously still room for improvement in this area (Figure 5). 

 A large treatment-naïve patient population, a well-organized health system, low costs, the availability of certain key opinion leaders, and other factors influence the decision to select a country to participate in a clinical trial. From the survey it appears that troublesome contract negotiations can also be made part of that list: 30% of the respondents indicate it can influence their decision not to select a country. 

It is important for the decision maker to know the actual reason for difficult negotiations in that country. It could be the case that the staff dealing with these agreements are simply not familiar enough with the local laws, regulations, and practices. Countries that are perceived as most "difficult" by the respondents of the survey are the United States, France, Spain, Italy, Russia, and Poland. The European countries listed are typically countries where one could save valuable time were familiar with the local requirements. In such cases, it is worthwhile to ensure proper training of contract management staff, so that the decision to select a country can be based on other factors that are more difficult to influence.  

Demanding country-specific procedures, laws, and regulations, or bureaucracy at the sites are harder to avoid. In such cases, it might be interesting for local organizations that promote clinical research in their country to use their influence in order to help adjust local laws and regulations, to stimulate more efficient local procedures, and to facilitate education and support of the relevant site staff and/or investigators.  

When selecting sites, a vast majority of the respondents (80%) state that previous bad experience with the contract negotiations at the site influences their decision to work with that site in the future. There can be reasons to select a site despite a poor reputation with respect to contract negotiation timelines, for instance the availability of a key opinion leader, but the results of the survey imply that timelines are eventually a major decisive factor (Figure 6). 

The results of the survey show that the general perception in the industry is that hospitals or investigators participating in a clinical trial often cause delays in the contract negotiation process due to rigid hospital lawyers and a lack of a sense of urgency at the site. The industry perceives turn-around times to be unnecessarily long.  

Bureaucracy and lack of understanding are difficult to avoid; however, there are still ways to influence the progress of the negotiations. Setting deadlines with the sites seems self-evident, but is often not done. Another way to speed up the process is to provide a solid explanation and background information on difficult topics to clinical sites. If necessary, instead of a member of the clinical team trying to negotiate with the site on the basis of comments of the lawyer or contract manager, the latter could get in touch with the site directly to solve any outstanding items.  

Training, education, and creating awareness both at the site and with the contract managers could in the long term contribute to a solution for this delaying factor. 

If at the beginning of a negotiation the topics that are usually difficult to negotiate are known, it provides the opportunity to anticipate and pre-empt such problems. Suggesting clear and fair language and providing additional explanation on difficult or sensitive topics can make a difference. According to the outcome of the survey, the most difficult topics to negotiate in site agreements are terms relating to budget and payment, intellectual property and inventions, indemnification and liability, publication, insurance, and applicable law and jurisdiction.  

Feature Article

There are opportunities to make the negotiation process more efficient and reduce timelines.

Clinical Trial Agreement Negotiations

Spring arrived early this year, and then went away just as quickly. But while the temperatures re-chilled in April, the trees had already begun to leaf. Along the edge of my property lies a stretch of woods, which has formed a definitive border for our yard and a convenient place to dump yard waste and wooded debris from past winters. Yet in that early spring, as we enjoyed a few weeks in the unseasonably warm sun, we noticed that jutting behind the ring of emerging, spindly buckthorn that dominated the woods were oaks and maples—trees that we'd barely noticed in past years.  

So it was time to clear the buckthorn. European Buckthorn (Rhamnus cathartica), is an invasive, woody plant that will dominate any northcentral landscape if left unchecked. A single plant can sometimes be trained to form an interesting specimen with careful pruning, but you can't train it to remain in solitude. One plant soon becomes a grove, which soon becomes the woods, which provide shielding from wind and sight but are suitable only as a screen to dump behind. And even that soon becomes a challenge, as the buckthorn will soon form a forest of thorns that even Prince Phillip's sword would find formidable to penetrate. 

So we engaged a local contractor to clear cut a substantial section of the woods. This exposed the trees, which were indeed mighty but a bit emaciated as it turned out —having also been cramped by the pushy buckthorn despite their greater girth. The clear-cutting was only a temporary solution. We could now reclaim more land for the moment, but hundreds of aspiring hidden roots and threatening shoots still remained, and, if left to their own device over another season or two, a new wall of buckthorn would appear all over again. You see, you can't just cut it off—you have to painstakingly dig out the roots, and then watch for and eradicate new shoots over and over again. 

We have to clear the buckthorn in our business lives as well. I recently changed jobs and, rather than just copy my old files from one PC to another, I decided to make it an opportunity to switch to a Mac and start all over. But this wasn't so easy, because buried in the many gigabytes of past documents and e-mails were things that I occasionally needed to refer to again. It wasn't as easy as simply digging out the roots—I had to keep a small side garden for these old files, just in case.  

Alas, there's a lot of buckthorn in our clinical data.  

We collect too much data, and we make too little use of what we collect. Each data item we collect places more burden on investigators, monitors, and data managers, since our quality standards require us to ensure that case report forms (CRF) data be accurate and complete. And cluttering up the essential data creates noise that obscures more effective data reuse downstream.  

As with buckthorn, the only way to avoid infestation is to keep the weeds out in the first place. In research, this can be accomplished in the protocol, which specifies the data to be collected at a high level. But when the high level data collection plan in the protocol is translated into CRFs and a data collection system, some of the weeds—the legacy of past, similar studies—manage to sneak their way back in. 

In fact, the problem begins even further upstream. In the clinical development plan, a decision is made to develop a drug as a treatment for a particular indication. But there is a body of knowledge already published about the indication and what data or biomarkers are deemed to be important or necessary to collect during clinical studies testing treatments for that indication. This knowledge history already has been accumulated from the prior work of researchers in the scientific and academic community, as well as those from the pharmaceutical and biotechnology industry. Typically, this information is expressed as common data elements or variables that are collected on CRFs. Some pharmaceutical companies or research institutions have tens of thousands of such elements, many of which are more or less equivalent to each other, though perhaps with slight variations in meaning, labels, format, or attributes. Past experience tends to result in an accumulation of clinical concepts, since it is usually easier to create a new concept rather than figure out which existing one to use that may not seem quite right for the purpose at hand. And this is assuming that it's easy enough to find the ones that are already defined and understand them sufficiently to recognize that equivalence. Meanwhile, these concepts get translated onto CRFs—even if they are not always necessary or directly pertinent to the protocol at hand. We need to be wary of the weeds. 

And often the same medical concepts get expressed differently to different audiences, which adds to the confusion. Some of these medical researchers speak in the languages of healthcare service delivery, encoded in systems such as SNOMED-CT and ICD-9, while industry researchers tend to think in terms of research dictionaries like MedDRA. So the same medical concept may be expressed in different vocabularies—which proliferates the clutter because you can't easily translate one to another because of the different structure of the coding systems.  

And science marches on, creating yet more variation even when describing the same essential things. This is the nature of the scientific method—we conduct experiments, learn from the experience, and then apply that learning to the next study by creating a new protocol with a different design and modified data points we want to examine. But when we look at medical observations that occur during the conduct of primary patient care delivery, are they really the same as protocol-specified measurements taken on a precise schedule according to a research protocol? They may be called the same thing in some cases (though often not), but the parameters, conditions, and constraints specified may vary with each new trial. Yet there's value in knowing when two observations are the same, or when they're similar except for certain attributes, or when they're entirely different. 

Identifying and understanding the essential core set of data elements that comprise research in a specific disease or therapeutic area is not an easy task. Clinical experts tend to have strong opinions of what's important, and imprecise language can be deceptive. The process of identifying this core set requires extensive interaction among a broad user community, and visual tools such as mind maps and domain analysis models to describe and express the concepts in a way that the broader scientific community can understand—and buy into. 

If we could get a better handle on the essential concepts we need for research in each therapeutic area, we might also begin to learn certain metrics such as which data elements are most often used for which types of studies on which kinds of drugs for the exploration of different medical conditions. Which ones are most typically used as primary or secondary endpoints? How often are they used? What types of information are needed for a complete safety profile for certain indications? Which are not particularly useful? In other words, which of those green shoots springing up from the soil are more likely to be cherished annuals and perennials, and which are the weeds we want to pull out? These are some of the things we'd want to expect from the learning healthcare system that the Institute of Medicine has been envisioning. 

Such a problem should be addressed on a global basis, through a shared knowledge base. All of our scientific research concepts and data elements should be stored in a comprehensive metadata repository where they can be accessed and applied on new studies by the entire global research community. Such a repository would identify essential, known clinical data elements; explain what they mean and how and where they are used; bind them to common value lists of controlled terminology; describe how they relate to various data standards and information models; express relationships on how elements fit together on a CRF, a data file or other packages for use in research; and identify equivalent and similar concepts used elsewhere in healthcare as well as research. The repository could even be used to facilitate data mapping to standard formats, even though that is not as desirable as defining the correct elements up front. 

Of course, it may be too utopian a vision to accomplish all that right now, but why shouldn't we know at least as much about the fundamental data elements and concepts essential to conduct high quality research as we do about, say, shopping for groceries? Shouldn't healthcare and research be at least as much of a learning system as the retail marketplace? 

We need to identify these core clinical data elements that are pertinent to each therapeutic area as well as the most important elements necessary to evaluate safety. We need to trace many of these back to the same concepts used between doctor and patient at the point of care. We need to understand how these all relate together—how they are discussed in the physician-patient meeting; encoded in healthcare systems for orders and billings; collected on CRFs; represented in databases; and analyzed for clinical study reports and later, aggregate analyses. And we need rich, comprehensive metadata that ensures we understand the nuances of these concepts and can trace that flow effectively from end to end. We need to concentrate on these specimens for our garden of knowledge—the ones that we really want to see. Maybe then we can finally start to understand the wonders that are presently obscured among all the buckthorn. 

is Chief Technology Officer for the Clinical Data Interchange Standards Consortium (CDISC). He resides near Chicago, IL, and can be reached at 

CTI Insights

We collect too much data, burdening investigators, monitors, and data managers.

Buckthorn Wars and the Essence of Clinical Data

If you missed International Clinical Trials Day this year, you are certainly not alone. It took place, apparently, on May 20, and is celebrated every year on or around that date, in commemoration of the day that James Lind started his trial comparing treatments for scurvy, back in 1747. 

With some small embarrassment, given that I have been writing about clinical trials for more than 15 years, I am obliged to admit that I had never heard of International Clinical Trials Day until this year. And I would probably still be ignorant of it were it not for a press release from the European Medicines Agency in London. 

The agency "supports International Clinical Trials Day," it announces. And it goes on to explain that the aim of the day is to "enhance communication and coordination of clinical trials between countries, resulting in better clinical research that is relevant to the needs of patients everywhere." That is certainly a noble goal. But I can think of an even better one—and one that the EMA may also share right now. 

In early May, the EMA suffered a new reverse in its fortunes, when the European Parliament voted against clearing the agency's accounts, because of concerns over its management. This decisive thumbs-down from the European Union's watchdog on spending was just the latest setback in an annus horribilis (an annus and a half, really) for the beleaguered agency.  

As reported in this column (and in many other channels), trouble started for the hitherto spotless institution when its former Executive Director, Thomas Lonngren, jumped ship to work for the drug industry at the beginning of last year.  

Management board complicity in the move generated additional anxieties over how secure the agency was against conflicts of interest. Only weeks after that imbroglio, the Mediator circus came to town, when suggestions were made that the agency had somehow been negligent in pushing for re-assessment of the antidiabetic from Servier.  

A delay of almost a year before filling the vacant post of executive director didn't help improve the agency's image in the outside world. And by the time the new boss started work late last year, the agency was facing another major challenge—threats by the European Parliament's health committee to refuse to accept the agency's accounts pending adequate assurances that management was fully in charge and doing its job, particularly over averting conflicts of interest among experts, staff, and management. 

Until recently, the agency had been hopeful of averting humiliation. It had supplied numerous details of new methods put in place to meet MEPs' concerns. But in the end, the health committee remained adamant that not enough evidence had been provided of a new broom making a clean sweep. And it persuaded a majority of the Parliament to refuse approval of the accounts.  

The new boss (no longer really new) is left casting about for ideas as to how to prove his agency is now whiter than white. 

In the meantime, the damage done to the agency's reputation is huge, and persists. From being a world-renowned paragon of virtue in international regulatory circles, it has fallen to the level of a suspect. Public perception too has been negatively affected by the repeated attention to its alleged deficiencies. So it is little surprise that the agency has seized on the opportunity of International Clinical Trials Day to offer a reminder of what its core purpose really is—and to point out how it is fulfilling those responsibilities. 

In what looks like a clear rebuttal of the Parliament's suggestions that the agency is no good because of some oversights in largely administrative matters, the press release states clearly that "the majority of the agency's scientific work is centred on the review, coordination, and supervision of clinical trials."			

It then sets out at some length to explain how it goes about discharging these tasks in easy-to-grasp layman's terms. It describes its scientific evaluation work as involving "the review of clinical trial data that are included in the application information from a pharmaceutical company when seeking marketing authorization." It underlines its role in providing scientific advice on the design of clinical trials conducted as part of medicine development, and decisions on clinical trial design in pediatric investigations. And it notes its provision of scientific guidance on the design and conduct of clinical trials in specific therapeutic areas. 

The agency also flags up its "central role" in ensuring application of good clinical practice at the European Union level, and its activities as host of the EU clinical trials register on behalf of EU Member States and as developer and coordinator of the EudraCT database used by national medicine regulatory authorities to enter clinical trial data from clinical trial sponsors. Its recent guidance on how clinical trials outside the European Union should be conducted also gets a mention. 

In other words, the agency is basically doing a good job, it would have us believe. It highlights the very concrete and positive benefits of its activities, implicitly relegating to a secondary level of importance the areas where it still stands accused of inadequacy. It is an understandable and indeed even a sensible way to proceed. While it is not for this column to presume to pass judgement on any of these weighty matters, it is plain to anyone with eyes to see that a certain disproportion risks creeping into discussions of the EMA—and, indeed, of other institutions, some of them closely linked to the European Union.  

Accusations  naturally attract attention—and not just in the media. The accusations against the EMA have attracted wide attention. They have also colored perception of the agency, because in nearly two decades of existence the agency has remained almost anonymous, unknown to the world outside medicines regulation. Its first public appearance is in the defendants' box, and the first public discussion of its activities has taken place against a febrile background of claims of gross misconduct.  

In consequence, the risk exists that the general perception of the agency is deeply negative—irrespective of the validity or relevance of the accusations it faces. 

That is bad news for the agency. But it is also bad news for the clinical trials community. Because if the agency's credibility suffers, so too does the credibility of everyone subject to its regulation. And no one in the world of medicines development needs any reminders of the perils of lost credibility—whether it be among patients, physicians, regulators, or investors. 

So it is a smart move by the agency to try to redress the balance by invoking the merits of clinical trials in general, and the merits of its own involvement in ensuring high standards in their conduct. 

And just for the record, this is a brief list of the changes that the agency has introduced over recent months in a bid to demonstrate that it is managing its affairs well. 

The agency has a policy on the handling of conflicts of interests for its scientific experts, including committee members, which was last updated and endorsed in March 2012. It says it takes a proactive approach to identifying potential conflicts of interest and searching for alternative experts where necessary, and to help achieve this, all experts must complete a declaration of interests form every year. 

The agency screens each expert's declaration of interests to decide whether or not to include him or her as a member of a committee, working party or other group. It assigns each expert a risk level based on whether the expert has any interests, and whether these are direct or indirect. To assure transparency, completed declarations of interests and risk levels for all experts are available in the European expert list on the agency's website. After assigning a risk level, it uses the information provided to determine if an expert's involvement should be restricted or excluded in specific activities, such as the evaluation of a particular medicine. It bases these decisions on the nature of the interests declared, the time since the interest occurred, and the type of activity that the expert will be undertaking. Experts can only be involved if they have signed a declaration of interests form and the agency has assessed those interests. All proposed members for its scientific committees have their declarations of interests screened before their formal nomination. 

In March 2012, the agency endorsed a breach-of-trust procedure setting out how it deals with incorrect or incomplete declarations of interests by experts and committee members. Similar rules have been introduced governing agency staff and members of the agency's management board. 

The coming weeks will determine how far and how fast the agency can clear its name fully, and how soon it—and the wider clinical trials community—can get on with some real work, free from suspicion. 

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

View from Brussels

European Parliament voted against clearing the agency's accounts because of management concerns.

European Medicines Agency Under Attack

Personalized Medicine for Now and the Future

The 2010 US Patient Protection and Affordable Care Act authorized the creation of the Patient-centered Outcomes Research Institute (PCORI) and requires that the PCORI Research Project Agenda "be designed as appropriate to take into account the potential for differences in the effectiveness of healthcare treatments, services, and items used with various subpopulations, such as racial and ethnic minorities, women, age, and groups of individuals with different comorbidities, genetic and molecular subtypes, and quality of life preferences, and include members of such populations as subjects in research as feasible and appropriate."

This requirement in the statute presents the potential to discover and disseminate crucial comparative effectiveness research (CER) findings that individual patients and their clinicians need for making informed healthcare decisions, especially when there can be known harmful consequences to some patients. Achieving this enormous goal will move our nation closer to knowing what works for whom, under what conditions, and realizing the promise of what's often been termed personalized medicine. Indeed, results from genetic and molecular subtype research have advanced the ability to recommend treatments with the greatest likelihood of success, given that we know a patient's genotype. This important and direct use of genomic data is the view that's normally associated with personal medicine. 

However, treatment decisions—and the tools for making many treatment decisions—also utilize non-genomic information on patient characteristics. That is, healthcare providers and systems know race, ethnicity, sex, age, comorbidity status, and other relevant health information for patients. Therefore, a more holistic definition of precision or personalized healthcare can now be considered, one that seeks the promise of knowing which interventions are most effective for which patients and under what conditions. Personalized or precision healthcare also incorporates the personal needs, preferences, healthcare access, and adherence attributes that each person brings to the healthcare encounter and decision-making process, in addition to genomic information, if available. Although PCORI is a US initiative, the need for increased precision in healthcare is important worldwide. 

Recently, Amy Abernethy, Felix Frueh, and Jens Grueger presented their viewpoints on the challenges both facing PCORI and for achieving the hope for personalized healthcare from the perspective of a medical oncologist, a pharmacy benefit management (PBM) research leader, and a pharmaceutical developer, respectively. Four relevant questions incorporating each of these professional's viewpoints were answered and discussed, thus ensuring that the order of response for each perspective continually changed. The questions are as follows:   

Will healthcare product development embrace the identification of subgroup effectiveness early and throughout the development process?

What roles do payers and manufacturers have in realizing the hope for personalized healthcare?

Are healthcare databases designed to address the challenges of achieving personalized healthcare?

How can PCORI research related to personalized healthcare be adopted into US policies?

 I'm a medical oncologist caring for melanoma patients. Undoubtedly, subgroup effectiveness is making its way into my clinic, and I see this on two main fronts. The first is in terms of the clinical trials where I try to match my patients by biomarker, by site of disease, or by line of therapy. These trials are increasingly more honed, and this means that I've got more patient characteristics to remember as I try to get the patient into the appropriate trial. Subgroup effectiveness doesn't feel new to me, but the number of things I need to remember about each patient for specific trials or interventions is increasing rapidly. 

Second, in the post-marketing setting, I'm seeing subgroup comparative effectiveness and subgroup effectiveness in terms of how I take care of my patients. For example, consider Vectibix®  (panitumumab), which was approved in September 2006 by the FDA for patients with epidermal growth factor receptor expressing colorectal cancer with disease progression on or following fluoropyrimidine, oxaliplatin, and irinotecan-containing chemotherapy regimens. To consider prescribing panitumumab, I obviously have to remember a number of things about my patient inherent in the product's approval. Moreover, the number of characteristics that oncologists try to coordinate in tailoring treatments to their patients increases every day. Given that drugs don't get to patients without going through us, information derived from specific subgroup analyses is directly impacting patient care by changing our therapeutic choices. 

 I'll make just a couple of observations about the question itself, which I found quite interesting. First, you ask about healthcare product development, and I think it's important that we don't equate that only with drugs. There are many healthcare products, and therefore many venues that can actually look at tailoring something new to individual patients and identify subgroups. Second, you mentioned effectiveness rather than efficacy. I think that's another critically important distinction. When you're developing a package to submit to the FDA for regulatory approval, you're demonstrating clinical utility, but not necessarily clinical effectiveness. Often, information on effectiveness comes much later, when we actually realize how a new medical product performs in a real-world setting. Third, the question focuses on the development process. If you look at the pipeline, I believe that about two-thirds or so of all drugs that are currently being developed, be that small molecules as well as biologics, have a biomarker associated with them in one form or another. So in that sense, I think that the advent of personalization, or the more precise delivery of care, is currently part of most ongoing development processes.  

The next step is the follow-through. Take Effient®  (prasugrel) for example, where a lot of subgroup work was been done pre-market, but the follow-on post-market effort hasn't really happened. Opportunities are being identified, but they're not being translated into clinical practice. I think that's an area where we're probably going to see much change over the next few years. What is important in all of this is that we look at medical product development as a continuum that doesn't stop at the point the product comes to the market. We need to identify subgroup effectiveness opportunities as early as possible, even if this sometimes will be in the post-market setting. 

 First, just as a reflection here, I work in the Primary Care Business Unit at Pfizer. In the 1990s and into the 2000s, Pfizer perfected the blockbuster model, yet it is the antipode of what we are speaking about here. Even a company that has worked this way in the past is realizing now that the future will be in better targeting our medicines to the patients with unmet needs. This is not just in highly specialized oncologic areas, either, where we have lots of examples of personalized medicine. I expect this is also coming into the primary care space because we have to face the fact that generics have become the standard of care for the diseases we are looking at. As part of the future of product development in this area, we need to identify the patients who are not effectively treated by the plethora of generic medicines. So my response here is "yes," and we have both risk factor data and genetic data in all of our clinical development programs. We are trying to understand the heterogeneity of treatment response to our medicines at an early stage. That way, we can include these subpopulations in the design of the Phase IIIb trials. 

Regarding subpopulations, we have to make choices. It is important to understand the subgroups or strata where there is a response difference. I can confirm Felix's point there. I'm not sure whether two-thirds of the Pfizer portfolio of drugs in development are personalized medicines, but two of our late-stage products have significant genetic subgroup differences. First, critzotinib is an oral anaplastic lymphoma kinase (ALK) inhibitor approved by the US Food and Drug Administration (FDA) for the treatment of patients with locally advanced or metastatic non-small cell lung cancer that is ALK-positive. Second, we have an Alzheimer's disease drug where we know from the Phase II data that the safety profile is influenced by the genetic status of patients; for ApoE4-positive carriers, the safety profile is different from the ApoE4-negative patients. I think the personalized medicine hasn't come as fast as people have thought it would 10 years ago, but I think we're at the point where quite a substantial number of products are coming to market with this personalized information. 

 Before payers pay a bill, they want to know what they're paying the bill for. I think the role of the payer in this context could be as a very rigorous evaluator of how the treatment, intervention, and therapy impacts outcomes. I think that the outcomes-based focus will significantly increase once we have more choices, and can make those choices based on an individual basis. Therefore, I think the role of payers over the next few years will be to discriminate between what works and what doesn't work, and to put incentives in place to make sure that this is being followed, but with a broader view in the payer community. In particular from the PBM perspective, the logistics and infrastructure that we have access to are very interesting. There really is no other place with a hub or central place to access physicians, patients, laboratories, and payers. If we're talking about personalized medicine, all of these groups need to converge in one place to mediate the interaction between all of these stakeholders and provide encouragement for the use of these novel products. For example, we can inform patients and physicians about the availability of new genetic tests and make them accessible. Hence, we have the logistics, infrastructure, and operational backbone that creates a very interesting place to enable precision healthcare and personalized medicine. 

It is important to note that this also requires education and decision support. I remember when I was working at the FDA, we developed two online courses for physicians for personalized medicine—one in collaboration with the American Medical Association, and the other one with the American College of Clinical Pharmacology. Despite offering continuing medical education credits, they just flopped because there was no motivational rationale for the physicians to go online and take these courses. What has been missing is the introduction of a teachable moment. When you think about the PBM infrastructure that I was just mentioning, we are creating this teachable moment at the time when somebody comes to the pharmacy to fill a prescription for a drug where a personalized medicine tool, like a genetic test, is available to understand: the best dose, whether the drug is going to work, and/or the patient's risk for an adverse event. Therefore, we can take that opportunity at the pharmacy to inform the physician and the patient about the availability of such a test, and that's the teachable moment that otherwise doesn't exist. Moreover, we can do that on a very large scale. And since payers are responsible for paying the bills and ensuring that medication is used appropriately, you create that incentive at the needed point in time. I think it is this educational and decision support that's what is clicking with physicians. 

The last point I want to make is about metrics, because payers, patients, and physicians are interested in long-term beneficial outcomes, as well as monitoring these outcomes. Therefore, I think it's critical that we're not just looking at making a decision at a particular time point and ignoring what happens afterwards, but instead following patients over time and evaluating them at appropriate intervals to see whether or not a particular intervention makes a difference. With this follow up, we can then adjust and optimize the delivery of care. 

 I interpreted the question in a slightly different way than Felix. I've placed my emphasis on the "and" that is between "payers" and "manufacturers." I think we have to collaborate in this area because personalized healthcare treatment strategies will be complicated. In order to be implemented, we need the data that includes the evidence that we have created in the development program, together with incentives and processes that will then be helping us first to implement these strategies in the real world, and then to validate those strategies. This is when we will know the difference between efficacy and effectiveness to determine if these treatments work, and whether the genetic information can determine at all times whether something works or not. In many cases, the problem will be that we don't have 100% sensitivity and specificity for these strategies. We will need to collaborate together in those gray zones where there is some benefit for some patients, but it's not the extreme benefit that we are hoping for from a personalized strategy. 

Personalized or precision treatments based on heterogeneity of treatment effect will also show us that the value of what we as an innovator deliver to the marketplace varies across different patient groups. Therefore, it will show how we should deal with a situation where the value may be very high in some patients and lower in other patients. The treatment may still be a good value, and better than what existing treatment strategies offer. This reminds me of the discussions that we have outside of the United States related to value-based pricing, and wondering if we need to solve the problem here in the United States. That is, do we need to say that depending on how the products are going to be used, the reimbursement from payers to the manufacturer varies depending on whether it is a real breakthrough situation? Should there be a smaller premium if it's just a small improvement on an existing therapy? These are complex situations, but I think it is critical that we can solve this in order to then provide the right incentives for implementing and further developing these strategies. 

I agree with Felix and Jens that the generation of effectiveness information in the outcome setting is critical to going forward, and that we must try to continuously understand how to hone therapies to determine what works for whom and when. It is also crucial to transfer that information to clinical practice in a way that supports clinical decision-making at the time of the teachable moment. The days of continuing medical education, where I would sit in a room and listen to a lecture, and then two years later I'm supposed to somehow remember what I learned and integrate it to this particular patient on this particular day with this particular targeted agent, are pretty much gone. Therefore, my recommendations are for payers and manufacturers together. So I really focus on generating more of the information in partnership with the clinical community—and with government—about how to understand what works in the outcome setting. We need more pragmatic CER that continuously and progressively defines what works. Specifically, I always think about treatment sequencing when I decide which drug to recommend from my toolbox for this particular patient, especially when we have multiple drugs that target multiple pathways or the same pathway. Demonstration projects supported by payers and manufacturers are needed that help us understand: what it looks like to have personalized medicine in action; where it's not just the genetic test but also patient values; how to communicate these choices effectively; and what are all the core components of healthcare necessary to turn personalized medicine into something that can be done in the clinic. 

We also need reimbursement mechanisms, especially to support participation in clinical trials, efforts to facilitate evidence development, and ways to best implement lessons learned in the clinic. As Felix said, it's not just about drugs but targeted strategies in order to achieve personalized medicine; "strategies" requires the testing of how all of healthcare and the process of personalization works in concert, not just one particular drug for one particular target. 

On the manufacturer's side, we need to support mechanisms that help clinicians sort through a myriad of signals to be able to match treatments to patients; I think manufacturers need to understand all of the signals that are coming in. We need to support patient values and adherence. We need to conduct continuous post-marketing research. And we need to be ready to constantly update knowledge. Everything in my practice changes around June 5 each year, when the American Society of Clinical Oncology (ASCO) Annual Meeting happens. As soon as ASCO hits, my practice changes, and then it continuously evolves from that point over the course of the year. 

For you, at what point does your company engage with payers in product development and look for input to perhaps design a later-stage clinical trial to generate information that is also relevant for the reimbursement part?

 (Frueh's follow-up question to Grueger)  

First, even before the products come into Phase I, we develop guidance documents internally to focus the research in areas that would be considered of value from a regulator, payer, and patient perspective, because that's what our researchers are looking for these days. They know that just having some new mode of action is not sufficient. Most important, of course, is when the first proof-of-concept data are available in Phase IIa. I think many companies are now asking for scientific advice from payers at that point in the very same way that we ask for that advice from the regulators; that includes the national payers outside of the United States and the private payers within the United States. It's an interesting experience because this requires new skills, like those at the Medco Research Institute. Both the innovator and the payer will have to predict what information will be relevant in five years' time that will drive reimbursement strategies for personalized medicine. 

 No. We have a choice between breadth and depth. Medco can offer data for more than 50 million lives covered in their databases, in some way or the other. Within those databases, there will be some pockets where we have very deep data, such as lab data from genetic labs or from other investigations. I think Felix in his introduction already said the art is to combine these databases, and I think that's where a lot of investment is currently going from healthcare reform. There was even more money invested into health information technology than there was in CER, so hopefully some of that money is really going in the direction to create databases that allow us to collect the information to drive personal healthcare. 

 Databases are critical, and this is a pretty big issue near and dear to my heart. However, we need more than the ability to look into databases and mine them; we need to be able to use the databases for achieving personalized medicine and personalized healthcare. So my answer is no, because our databases don't talk to each other very well. We lack the standards, the governance, the trust, and essentially the mechanisms to have free and liquid data flow across databases, both to facilitate stratified analyses and understand different interventions for specific patient populations. Moreover, when caring for the individual sitting in front of me, how do I take specific characteristics about this person and have that information be automatically matched into multivariable, prognostic, predictive, and other kinds of models that likely sit outside of my electronic health record and flow back to me, coupled with clinical decision support and other mechanisms? This is going to require a process of free-flowing liquid data that then also coordinates into our data systems and allows for continuous CER. We see this happening in some pockets and in some discreet systems where we understand what the walls of those systems look like, and how information can flow and work together. But thinking about it in a much larger framework has been difficult to date. 

 I have a slightly different opinion. I think current databases can be used for personalized healthcare in certain circumstances. They're certainly not designed for this particular use, but the data that's contained might in fact be very useful to at least create hypotheses that you can then take forward and either confirm or disprove. For example, when the reports came out that Plavix®  (clopidogrel) was being metabolized predominately through an enzyme called cytochrome P450 2C19, we didn't really have a lot of genetic information to figure out whether or not the presence of this enzyme translates into different patient outcomes. What we did have, however, was drug-drug interaction information, where we could look at drugs that interact with this pathway and mimic the genetics that we're interested in. So by pheno-copying genetics and looking into longitudinal pharmacy databases—and then outcomes databases to see whether or not patients who were on both drugs have worse outcomes than patients who are only on Plavix—we actually had a proxy for the impact genetics could have. If we consider that interaction as a hypothesis that we could then take forward and prove valid or not valid in clinical practice, I think it's that alternative use that we have to respect when looking at the current databases. That doesn't mean that we have the perfect system. I completely agree that there are new types of databases, more complex databases, and databases in particular that address molecular features of individual patients that we need to look at, but they're being created as we're moving along. I don't think that you're going to go out there and just design one database that becomes your personalized healthcare database for an individual patient. There are going to be various different iterations.  

What I'm advocating for is that we look at what we have, to see whether or not there is a possibility to combine some of these datasets and explore opportunities where large genetic data pools exist to see whether or not we can combine them with pharmacy records, for example, and look for correlations so that we don't have to reinvent the wheel. The data is already there, and I don't think we have put a lot of thought into making smarter use of the data we already have. 

 I view PCORI research findings as an opportunity to look at novel mechanisms and tools that we can deploy in evaluating whether something is valuable, and then take that information forward into clinical practice knowing whether something makes a difference. This has implications for the larger use of coverage with evidence development. I think what the Centers for Medicare and Medicaid Services have started in certain cases is something that I could see being taken up in the private payer environment as well. It's a good system to get your feet wet and evaluate whether something actually has the potential to work. 

I personally have a problem with PCORI leaving economics completely out of the equation if we're talking about comparative effectiveness. You can't just look at one bucket versus the other bucket, and not look at whether or not it's economically feasible to use any one of these buckets in the real world. I think there needs to be a reality check that is based on the economic environment we're working in. And I just find it peculiar that, while we're talking about healthcare reform focused predominately on cost, we're creating a PCORI that leaves the cost part completely out of the equation. 

I see the explosion of information and the huge, on-the-ground difficulty of cognitive overload being one of the biggest challenges for personalized medicine at the front line of clinical medicine. In order for PCORI research related to personalized healthcare to be adopted into US policies, PCORI needs to handshake with other parts of the government that are responsible for creating the kind of information systems, informatics standards, governance, etc., to ultimately facilitate the information that's going to support personalized medicine and the information flow. In particular, the Office of the National Coordinator for Health Information Technology, the Agency for Healthcare Research and Quality, and the National Institutes of Health need to be informed by PCORI and vice versa, with frequent conversations around common data elements and CER. I think that the inclusion of industry, as well as payers, is critical to not only this conversation but also the one around the information that's coming out of PCORI. 

Second, I think PCORI needs to ensure that the conversation around personalized medicine does not get limited to genetics and genomics, but really continues to be personalized healthcare. That way, it is about all the contexts of patient care, including this person's values, how they're experiencing healthcare, and their own social situations. The message from PCORI should also continue to include important outcomes measures, like patient-reported outcomes. 

Third, I think PCORI should work together with payers to develop better processes for coverage with evidence development, pragmatic clinical trials, and other evidence development schema. This is going to be how we learn the best methods to make this happen from an evidence standpoint. And finally, PCORI needs to work within the context of demonstration projects to understand what personalized medicine means within the microcosms of healthcare. It's not just BRAF to BRAF-positive melanoma; it's really BRAF inhibitors in the context of melanoma that's got an appropriate BRAF mutation for a particular person where we've got the right line of therapy, where we understand other issues around this person's tumor, and we understand issues in terms of toxicity over time, as well as how far they live from a place that can give them that particular drug, etc. There are a lot of things we have to do in order to figure out how to take care of this particular person within this particular context, and that requires demonstration projects. 

 Personalized healthcare is central to PCORI; it is patient-centered. I think that's another word in that direction. The starting point is to strive for appropriate databases, and for appropriate standards for these kinds of analyses and research. The next step is that PCORI is funding and stimulating research in these areas, with valid research on the basis of better data than we are currently generating. I think these are the core missions; I wouldn't overload it. If PCORI achieves these two or three things, they will be extremely successful. 

 This discussion took place on May 24, 2011, at the International Society for Pharmacoeconomics and Outcomes Research Annual Meeting in Baltimore, MN. Kathleen Wyrwich, PhD, moderated the discussion. 

PhD, is Senior Research Leader at United BioSource Corporation, 7101 Wisconsin Avenue, Suite 600 Bethesda, MD, e-mail: 

PhD, is President of Medco Research Institute.

MD, is Associate Professor of Medicine at Duke University School of Medicine. 

PhD, is Vice President and Head of Global Health Economics & Pricing, F. Hoffmann-LaRoche AG.

1. Subtitle D—Patient-Centered Outcomes Research, Public Law, 

www.pcori.org/images/PCORI_EstablishingLeg.pdf

*To whom all correspondence should be addressed. 

What works when and for whom in the era of comparative effectiveness research.

Personalized Healthcare

The implementation of an effective pharmacovigilance function is high on the list of priorities for pharmaceutical companies due to the major emphasis that is placed on ensuring drug safety. This emphasis comes as a result of the stringent legislation enforced by regulatory bodies that demands greater transparency during the pre-marketing and post-marketing of all new pharmaceuticals to protect patient safety. As a result, it is vital that manufacturers effectively document and manage data on each and every aspect of their development and marketing processes.  

The advantages of an efficient pharmacovigilance system can often mean the difference between a drug that is withdrawn due to safety concerns and one that is successfully delivered to market. A comprehensive drug safety methodology will help to ensure the latter and by investing in an efficient system that will guarantee the effective processing of clinical trial safety data, pharmaceutical companies will benefit greatly in the long-term. 

Traditional thinking suggests it is essential that pharmaceutical and biotechnology companies exercise complete control over their pharmacovigilance activities to make certain that any safety signals are detected effectively, that regulatory requirements are complied with and most importantly to ensure a target drug's successful progression to the final stages of development. Doing this effectively can present a number of challenges, including the expansion of drug safety departments and the associated costs. However, successful experiences of outsourcing other clinical activities are making outsourcing of safety services to specialised service providers a more attractive solution for pharmaceutical companies. 

An effective pharmacovigilance function necessitates the efficient management of clinical trial serious adverse events from case assessment through to expedited reporting of suspected unexpected serious adverse reactions (SUSARs) to the regulatory authorities. It also requires development safety update reports to be compiled and submitted to regulatory authorities and ethics committees throughout the duration of the clinical trial program. Companies must also exercise the efficient management of information obtained from numerous sources including literature reviews, ongoing studies, knowledge of pharmacology and other drugs in class, preclinical data, patient population, co-morbidity profile and the disease process (pathophysiology).  

Pharmaceutical companies must also meet regulatory protocols and global standards. Due to varying regulations across the globe, being compliant on a worldwide scale has become increasingly difficult and efficiently adapting processes to meet the numerous guidelines and regulations of each country is something that many organizations are struggling with. Current guidance is based upon the International Conference on Harmonization and the Council for International Organizations of Medical Sciences guidelines; in addition to the confidentiality agreement from November 2003 between the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA), which covers the sharing of drug safety data. The proposed FDA guidance for a risk evaluation and mitigation strategies (REMS) program provides a new blueprint for how safety strategies should be developed, while the FDA final rule on investigational new drugs safety reporting and associated draft guidance contributes significant changes in safety reporting practices. Together with the EMA's Committee for Medicinal Products for Human Use, Guideline on Risk Management Systems for Medicinal Products for human use, these guidelines form the basis of pharmacovigilance regulations in most parts of the world.

In all pharmaceutical companies there is a need for an appropriate approach to pharmacovigilance that is risk-based; proportionate; and feasible within resources, but which meets quality standards and protects patients. Standard operating procedures (SOPs) that meet regulatory obligations must be put into place to guarantee quality measures for recording, reporting, and managing adverse events (AEs). Systems must also be implemented for receiving both spontaneous reports and clinical trial reports from investigators and forwarding these, within the necessary timeframes, to the appropriate bodies and individuals.  

Sponsors must provide the means to follow-up on safety issues, maintain records, and handle overall safety systems. Processes should be implemented to check that arrangements for projects have been established and documented correctly, and that procedures are being rigorously adhered to. It is also essential that a quantitative methodology is not used in isolation: it should be combined with expert judgment to create the safety profile of a drug.

Until recently many pharmaceutical companies have been reluctant to outsource their drug safety activities. This was primarily due to fears among manufacturers about losing control of processes and proprietary knowledge and the legal ramifications if the outsourcing partner "got it wrong." Today's marketplace offers a broad choice of both service providers and scope of pharmacovigilance services and in the face of rising profit pressures, many companies are increasingly turning to outsourcing processes as a way to gain access to innovative new ideas, maximize the use of existing resources, and reduce expenses.  

Outsourcing pharmacovigilance provides access to specialists that have the skills, technology, processes, and scale to perform tasks as well as or better than a pharmaceutical company itself. Manufacturers can benefit from specific support not available in house as and when they need it, enabling companies to save on recurring personnel and infrastructure costs while also offering the flexibility to cover times of high work throughput. 

The functions that can be outsourced during the development phase of a new compound include the review of safety results from preclinical and clinical studies, expedited reporting to regulatory authorities, preparation of DSUR reports, literature screening for safety issues and case reports, surveillance of emerging data, and the evaluation of benefit and risk for a product. The preparation of development risk management plans, preparation of SOPs and other controlled quality documents, system evaluation, database evaluation, database validation, and labeling evaluation are services that can also be outsourced.  

Evaluation of individual serious cases and AEs of special interest leads to the need to address important safety issues that are identified. In turn, the periodic cumulative assessment of all available clinical data (including laboratory and physical data) must be performed; this aggregate review depends on competent reviewers and auditable documentation. A specialist provider will have the capabilities to provide ongoing expert physician review to ensure the highest levels of safety are met. Such companies will be able to deliver DSUR reports that demonstrate whether or not any issues arose during a study that could have an impact on the known safety profile of a drug and can ensure that the data obtained are still consistent with the recognized profile.  

Outsourcing pharmacovigilance can offer a myriad of benefits to the pharmaceutical company. They are provided with increased speed and flexibility that provides access to a virtual team that works as and when projects demand and allows particular individuals to be brought in when specific expertise is required. In addition, the input of an outside organization can bring in strategic direction and often enables operations to get up and running more quickly. Highly specialized and expensive skills are required to carry out drug safety effectively. Outsourcing to the right company provides access to experienced pharmacovigilance physicians who not only have a critical scientific eye and the ability to conform to rigorous processes, but will also have a broad view of the industry.  

A further potential benefit of outsourcing safety evaluations during clinical development is that unblinding can be handled by the provider rather than the sponsor. This allows more controls and limits on who is informed of treatment assignments for reported SUSARs. 

An improvement in processes is also a significant advantage of outsourcing. Service providers can offer a short cut to radical improvements in efficiency, cost, and speed by rethinking a company's ingrained habits and processes. By doing so, outsourcers can implement new and better methods as a matter of course. Through outsourcing, a company can also rely on another firm's infrastructure rather than providing the capital itself and can take advantage of the ability to avoid huge fixed costs. In addition, outsourcing non-core and transactional tasks can enable a company to focus on its core competencies. 

Challenges: ensuring effective outsourcing

Outsourcing to the right provider can contribute many advantages to a pharmaceutical company, however, manufacturers must remember that doing so will call for monitoring of progress; performing inspections for quality data assurance; evaluating problems; and proposing corrections, as well as preparing plans for terminating the outsourced services. Similar to outsourcing any other service, it is vital that companies evaluate all the issues that may occur as a result of contracting these services to outside organizations before choosing to work with a provider.  

Though the many benefits make outsourcing a worthwhile activity, it should be approached cautiously to overcome risks and maximize success. There are a number of practices that will help manufacturers to make good outsourcing decisions and choose their partner wisely.  

Pharmaceutical companies will need to give considerable thought to how best to manage the relationship between themselves, the contract research organization and the pharmacovigilance service provider. To achieve success it is essential that collaborative processes are established that will not threaten the future of a drug. A sponsor action plan should be clearly designed at the beginning of any development program setting out predetermined objectives and measures to evaluate the outsourcing solutions. The legal, training, and confidentiality requirements that will guide the relationship must also be developed at this point. 

Some cases may involve the outsourcing process being divided between multiple providers meaning that the safety provider is often not in direct contact with the primary sponsor. In this instance it is important to ensure that the conduct of safety management in a clinical trial is a collaborative process requiring cooperation in evolving and implementing activities. In order to guarantee the success of the clinical program, training is of paramount importance to ensure any issues can be met with immediate action. 

The continuous exchange of information between the provider and the sponsor is another key element to success. However, sponsors must be certain that this is transferred safely and that confidentiality agreements are not compromised. It is therefore vital for sponsors to thoroughly check the competency of the provider they choose to work with. A good starting point is to undertake an SOP audit alongside checking the provider's team competencies and experience.  

Further to the collection, analysis, and timely reporting of safety data, an important point is the accountability for the detection of safety signals and the guarantee that signal identification is not lost due to segmentation of the analysis between providers and the company. In addition, responsibility for safety review meetings, data analyses, searches, compilation of documentation, and the ongoing creation of risk management plans needs to be defined prior to outsourcing in order to avoid misunderstandings. If it is decided that responsibility will lie with the sponsor, it is imperative that the provider is kept in the loop so all parties are aware of any new information or issues and can perform their work in line with the updated safety profile of the drug. 

Working with a specialized provider that is able to contribute expert advice and medical liaison will enable these challenges to be routinely addressed. As a result, pharmaceutical companies can rest assured that the clinical experience gained in clinical trials will contribute to building the safety profile of a drug rather than being the reason for bringing its development to a halt.    

Pharmaceutical companies are in a unique position to adopt the outsourcing model as a means to manage their processes more effectively and contend with pressure on profitability and a rising demand for efficiency. With a broadening array of both providers and service offerings, pharmaceutical and biotechnology organizations must remain in command, orchestrating the activities of different providers and ensuring that information is openly and continuously exchanged between all parties.  

The advantages of outsourcing are clear: cost savings, access to expertise, process improvements, the avoidance of fixed costs and big capital outlays, and the ability for a company to focus on their strengths. By utilizing the services and expertise of specialist providers, companies are offered a pragmatic solution, reviewing clinical trial data from a thorough safety point of view while also having a distinct understanding of the company's objectives and the use of a drug in clinical practice. As pharmacovigilance is a pivotal process to ensure that a company's product remains on the market, investing in an efficient system will benefit the drug manufacturer greatly by defining and validating a drug's safety profile and accelerating the delivery of new therapies to the marketplace.  

, MD, MFPM, is CEO, Prism Ideas, Regent House, Princes Court Beam Heath Way, Nantwich, Cheshire, UK, e-mail: 

1. Council for International Organizations of Medical Sciences,  Updates,  

An efficient system can be the difference between a drug being withdrawn or delivered to market.

Pharmacovigilance Outsourcing: A Guide

TTC estimates that nearly $1.5 billion of US clinical grant spending should be covered as part of standard of care treatment (SOC) by third parties for their patients' participation in clinical trials.  

SOC payment in oncology trials has been a common industry practice for a number of years. Sponsor pharmaceutical companies realize that the practice can be extended to other therapeutic areas as well. Additionally, large number of states specifically require that SOC procedures in clinical trials be covered by third party payers. 

Clinical sites are accustomed to billing insurance claims for their patients in general. A survey of 512 investigator sites in the United States on their current third party payers billing practices found that two thirds of sites regularly bill third party payers for their patients participating in clinical trials. When broken out by therapeutic area, billing is regularly done for oncology trials (84% of sites), dropping to 30% of sites participating in digestive system trials. 

The most mentioned reason by sites for not billing third party payers is simply that the sponsor did not ask them to. 

—TTC (for more information, please contact

Standard of Care Billing More Widespread

What Do More Complex eCRFs Mean for Clinical Research?

This month's blog focuses on the eCRF design complexity metric, which is a score that reflects the relative estimated work effort associated with implementing a clinical study eCRF—including eCRF build, testing, and deployment—using Medidata Rave®.  

The formula used to compute eCRF design complexity takes into account the study's total number of unique eCRFs, derivations, simple edit checks, and complex edit checks. The score for a given study is a weighted sum of these four eCRF components, where the weight applied to each component represents relative work effort, consistent with Rave study build resource tracking metrics. As a result, the eCRF design complexity score for a given study should not be taken as an estimate of work effort in actual units (e.g., hours, days, etc.) but as an indicator of relative work effort. 

Interestingly, as seen in this month's graph, Phase III data from the Medidata Insights metrics warehouse is in agreement with previous information publicized in other industry sources stating that clinical studies have been steadily growing in complexity over the past decade. Furthermore, it readily follows that more complex protocols (i.e., those having more procedures and assessments per subject) lead to more complex eCRFs.  

In a recent Data Analysis blog we revealed that a significant increase in eCRF reuse over the past several years has been accompanied by only modest reductions in eCRF build cycle times. Given the corresponding increase in eCRF design complexity over this time period, these modest gains are more understandable. It is very likely that cycle time (and resource) efficiency gains realized by study teams through reuse are being largely offset by the increasing volume of eCRFs and corresponding edit checks that must be configured for each new study. Organizations may be able to address this issue through focused "data reduction" efforts. First, a more structured approach to protocol design should be considered in which non-essential procedures and assessments can be identified and removed before a protocol is finalized. Second, eCRF standards should be developed that focus on removal of superfluous or non-essential data collection. It is estimated that 15% to 30% percent of data collected during the average clinical trial is never used in a new drug application ("Assessing the Downstream Impact of Protocol Design Complexity," 

Applied Clinical Trials-06-01-2012

Survey Reveals Patient Recruitment is the Biggest Challenge in Pediatric Trials

ACT Cover

Clinical Trial Agreement Negotiations

Buckthorn Wars and the Essence of Clinical Data

European Medicines Agency Under Attack

Personalized Healthcare

Pharmacovigilance Outsourcing: A Guide

Standard of Care Billing More Widespread

What Do More Complex eCRFs Mean for Clinical Research

Phones Still a Vital Part of Clinical Research

Business and News Update June 2012

Europe Turns Spotlight on Geriatric Trials

Trial Modernization Key to Innovation

Clinical Trial Community Portals

Applied Clinical Trials Digital Edition - June 2012