Richard Gliklich, MD

With more than 25 million people affected in the United States—and 50 million worldwide—rare disease research and treatment is an important medical necessity. Yet, little research has been done on many rare diseases, leaving both physicians and patients with a lack of treatment options, and, in some cases, with only a basic understanding of the disease itself. New studies focusing on rare diseases often face challenges related to small patient populations, the lifelong nature of the diseases, and variations among disease sub types. Increasingly, researchers are turning to patient registries to fill some knowledge gaps, as registries offer an opportunity to learn much about the way patients are diagnosed and treated and about how they respond to various management approaches. Patient registries have considerable potential to help improve understanding of rare diseases and provide the knowledge base necessary to support development of effective treatments. >

The US Food and Drug Administration (FDA) and the National Institutes of Health (NIH) define a rare or "orphan" disease as any disease that afflicts fewer than 200,000 people in the United States.

  Over 6,800 rare diseases, affecting 25 million Americans, have been identified to date. Rare diseases can cause a wide range of symptoms and may be chronic, progressive, disabling, and life-threatening. About 75 percent of these diseases affect children, and about 80 percent are related to genetic defects.

  Some of the more well-known rare diseases include sickle cell anemia, hemophilia, Tourette syndrome, and Tay-Sachs disease. Less well-known examples include Wilson's disease, Turner Syndrome, and Gaucher disease.   

In general, little is known about most rare diseases. The small number of patients with a rare disease often results in limited clinical experience within individual treatment centers. The clinical description of the disease may be incomplete or skewed, and the medical literature often consists of individual case reports or small case series, limiting understanding of the natural history of the disease. Both the lack of available treatments and the poor understanding of many rare diseases can be linked to the unique challenges that rare disease research poses. The challenges occur across the life cycle of a research study, affecting the study design, ethical considerations, and subject recruitment and retention.  

When designing a rare disease study, it may be impossible to find fundamental information on the disease on which to base the study protocol. For example, data on the disease prevalence and incidence may be unavailable, making it difficult to determine an appropriate study size. Diagnosis may be complex, particularly in cases where there is no definitive test. The development of the study data set may be hindered by a lack of information on the full range of disease symptoms or treatment practices. Selecting appropriate study durations may be difficult, particularly for diseases where new treatments are extending life spans.  

Ethical concerns may also arise in rare disease research. The majority of rare diseases affect children, who are considered a vulnerable population. Designing and conducting studies that enroll children may be more complex than designing studies for adults. For example, the International Conference on Harmonization (ICH) has released detailed operational guidelines for clinical trials in pediatric populations; these guidelines recommend, for example, that studies be performed in institutions with a pediatric infrastructure and appropriate personnel. Parents may be reluctant to consent to research, and there is ongoing debate about what age assent from the child, in addition to parental consent, is necessary for participation.

  Rare disease research may also focus on other vulnerable populations, such as cognitively impaired persons or pregnant women. Rare disease studies need to be sensitive to the needs of these populations. 

Once a study has begun, it may face patient recruitment challenges. By definition, rare diseases have limited patient populations. Patient recruitment can become even more complicated if there are multiple, simultaneous studies of a rare disease, as enrollment in one trial may make a patient ineligible for another trial. Patients with the disease are likely to be widely scattered across the United States or globally. Recruitment may involve a large number of physician offices or specialty centers, and studies may need to include patients from several countries to obtain a sufficient study population. Lastly, retention of patients for the duration of the study is often extremely important, given the small study sizes. Studies generally need to devote significant effort to following up with patients who move or seek care at other locations to keep these patients enrolled in the study. 

Efforts to encourage rare disease research

Economic factors create an additional hurdle to rare disease research, particularly research aimed at developing new treatments for these diseases. For most rare diseases, the costs of developing, researching, and producing effective treatments exceed the expected revenues. This economic reality led to enactment of the Orphan Drug Act in January of 1983. The act established tax and market incentives for developing treatments, also called orphan drugs, for rare diseases. The incentives have been largely successful. Since 1983, the FDA has approved over 350 orphan drugs.

  In contrast, the decade prior to 1983 saw fewer than 10 such products come to market.  

In addition to financial incentives, the FDA encourages rare disease research through the educational activities of the Office of Orphan Products Development (OOPD). The OOPD promotes collaboration among pharmaceutical companies, professional organizations, patient organizations, and academic centers. The office hosts training sessions on developing clinical trials for small sample sizes and provides assistance for product developers in gaining the orphan drug designation. These programs are intended to facilitate rare disease research and orphan drug development. However, it should be noted that orphan drugs are subject to the same regulatory requirements for obtaining approval as other products. Adequate, well-controlled studies must be used to establish safety and efficacy for these products prior to approval.

The US government also encourages rare disease research through the Office of Rare Disease Research (ORDR) at the NIH. The ORDR was established in 1993, but gained significant new funding and authority in 2002 with the passage of the Rare Diseases Act and the Rare Diseases Orphan Product Development Act. The ORDR coordinates research, sponsors educational programs for investigators, recommends national research priorities, and funds new studies of these diseases. The office also sponsors the Rare Diseases Clinical Research Network. Recently, the NIH launched a new effort specifically aimed at producing new treatments for rare diseases. The Therapeutics for Rare and Neglected Diseases program (TRND) is a collaborative effort involving the ORDR, the NIH Chemical Genomics Center, and the National Human Genome Research Institute. The program will create a drug development pipeline within NIH to stimulate research in rare disease treatments. The goal of the program, which will focus on pre-clinical drug development, will be to support drug research until a drug meets the FDA requirements for an Investigational New Drug (IND) application, at which time the drug will be transferred to an outside organization for further development.

Despite these efforts to encourage research into rare diseases, significant knowledge gaps still remain, and randomized controlled trials—the gold standard in clinical research—may be extremely difficult to conduct in rare disease populations due to sample size and length of follow-up limitations. Innovative research methods are needed to overcome the barriers of rare disease research. 

Patient registries are emerging as new tools with considerable potential for rare disease research. A patient registry can be defined as "an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes."

In recent years, patient registries have played an increasingly important role in medical research as stakeholders have emphasized the need for real-world data on patient outcomes and effectiveness from a broad range of patients. In 2007, the Agency for Healthcare Research and Quality (AHRQ) published the landmark handbook, "Registries for Evaluating Patient Outcomes," with a second edition released in September 2010. Reports published in the same year from the Institute of Medicine and the Congressional Budget Office both emphasized the importance of patient registries in developing comparative effectiveness evidence. In the past year, the NIH and AHRQ have issued several new funding opportunities under the American Recovery and Reinvestment Act (ARRA) that specifically focus on registries. The FDA already uses registries in assessing the safety and effectiveness of approved drugs and devices. Since 2005, the FDA Center for Devices and Radiological Health (CDRH) has called for some 120 post-approval studies, many of which use new or existing registries to study the real-world effectiveness of specific devices in community practice.

Patient registries have received particular attention in recent years among rare disease stakeholders, including patient advocacy groups, professional associations, and government agencies. These stakeholders look to patient registries as an efficient, powerful tool for observing the course of a disease, understanding variations in symptoms, treatment, and outcomes, and assessing the effectiveness of existing treatments. Through organized and coordinated clinical investigation systems like patient registries, researchers can accumulate a sufficient number of patients with rare diseases to provide the statistical power needed to study the clinical history of treated and untreated forms of the disease. Registries can also provide basic information, such as data on incidence and treatment patterns, needed for clinical trials of new tests and treatments.

  Two types of registries that are particularly relevant for rare disease research are disease registries and product registries. Disease registries enroll and study patients who are diagnosed with a specific disease. In rare disease research, these registries are often used to gather information on the natural history of the disease or to understand current treatment patterns. Product registries enroll patients who use a particular product. These registries may be used to study the long-term outcomes of patients using a new therapy for a rare disease.  

As previously discussed, rare disease research poses a number of challenges. Patient registries offer several unique features that make them particularly well suited to overcoming these challenges. In terms of study design, the protocol for a patient registry can be more flexible than for a traditional clinical trial. For example, in a disease area where the prevalence and incidence are unknown, a target sample size may be set at the study outset and adjusted during the course of the study, depending on the initial findings. In areas where diagnosis is difficult or not definitive, a registry may be designed to include patients classified as confirmed or probable cases. The registry data may then be used to help identify the most effective means of diagnosis.  

Registry data sets may also be modified over time, as new treatments or procedures become available. This can be particularly important in a registry designed to follow a patient for long periods, such as decades, or even for the remainder of the patient's life. In these registries, it is possible that new treatments will emerge during a patient's lifetime, making it possible to observe both the untreated and treated courses of the disease. In addition, because registry study designs are purely observational, it may be easier, in some cases, to obtain approval to study vulnerable populations, such as children or cognitively disabled people.  

Patient recruitment can still be difficult with a patient registry. However, registries generally have much broader inclusion criteria than trials. A trial may exclude patients using alternative therapies, or patients already enrolled in another trial. These limitations can severely limit the number of eligible patients in an already small population. Rare disease registries, particularly those attempting to understand the course of the disease and treatment patterns, may choose to enroll patients who are already in another trial, or patients pursuing alternative treatments.

While patient registries offer many advantages for rare disease research, there are several limitations to their use. First, patient registries cannot replace the controlled trials used to establish efficacy for new products and to obtain regulatory approval. Second, patient registries, like all observational studies, must address the potential effects of confounding. Study design considerations can help to reduce confounding, while statistical techniques can attempt to account for its effect on the study results. A second complication to the use of patient registries is the significant variation across observational studies in terms of their research methods and data quality. Many methodological improvements have been made in recent years, and good practice principles exist. For example, the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement provides guidelines for reporting the results of observational studies that have been widely adopted by biomedical journals.

  The AHRQ handbook mentioned earlier describes good practices for patient registry design, operation, and evaluation.

In addition to methodological issues, patient registries, particularly those that collect data over long periods, face issues with patient retention. Over a decades-long study, patients may move, or patients or their providers may simply stop participating in the registry. Registries must find ways to sustain patient and provider interest over the life of the registry. Other issues that may face patient registries include managing change as new treatments or procedures become available and ensuring data quality and consistency.  

In addition to the general advantages of advancing rare disease research, patient registries offer specific benefits to manufacturers developing treatments for rare diseases, providers treating patients with these conditions, and the patients themselves. For a drug or device manufacturer developing a product for a rare disease, a registry can be useful in both the pre- and post-approval phases. In the pre-approval phase, a disease registry may be used to advance the understanding of the disease; for example, the registry could provide new insights into the course of the disease or disease sub types, or provide more information on the burden of the disease and its effect on patient quality of life. This information may be important to designing and operating successful clinical trials to test a potential treatment. From a marketing standpoint, a disease registry can help to identify treating physicians and centers with large numbers of patients and to establish distribution channels prior to the launch of a new product.  

In the post-approval phase, a product registry might demonstrate the performance of a product in the real world, provide information on product use patterns, or meet a post-marketing study commitment. The FDA has noted that "through the creation of registries, a sponsor can evaluate safety signals identified from spontaneous case reports, literature reports, or other sources, and evaluate the factors that affect the risk of adverse outcomes such as dose, timing of exposure, or patient characteristics."

  Disease registries may also be useful in the post-approval phase, helping manufacturers better understand and separate the effects of the new treatment from the symptoms of the disease. A manufacturer with an existing disease registry may also consider adapting the registry into a product registry after the launch of a new treatment. This process could involve limiting enrollment of new patients to those using the approved treatment. Alternately, the registry could continue to enroll all patients with the disease, but collect additional data on patients using the new treatment.  

For providers, patient registries offer a tool for learning more about the progression and treatment of a rare disease. Both disease and product registries can help treating physicians connect with a community of their peers, where they can compare their patients' progress and trends to others and to the aggregate. These registries can help foster the formation of an international community of expert physicians who can collaboratively develop recommendations on the clinical management of patients. Evidence has shown that collective clinical experience can lead to the development of recommendations for evaluation and monitoring of patients with rare diseases. The analysis of registry data on treatment outcomes can facilitate the establishment of therapeutic goals for patients with rare diseases.

  This builds a foundation for a consensus and the foundation for a consensus- and evidence-based disease management approach. For example, the use of a patient registry contributed to developing treatment practices that have more than doubled the life span of an estimated 30,000 cystic fibrosis patients.

Patients with a rare disease may also benefit from participating in a patient registry. Registries can provide patients with valuable sources of information on their disease. For example, the registry may develop and distribute educational materials to patients. The registry may also use information collected at each visit to develop custom reports for patients; these reports could track the patient's progress over time on key indicators. Some patients may find satisfaction in participating in a project that will improve the understanding of their disease.   

Many patient registries for rare diseases are already in use. One of the most long-standing is the Cystic Fibrosis Patient Registry. This registry, managed by the Cystic Fibrosis Foundation, has collected information on cystic fibrosis patients in the United States for more than 40 years. The registry includes over 25,000 patients and has contributed significantly to improved care and longer life spans for cystic fibrosis patients.

 Another example is the Gaucher Registry, which was established by Genzyme in 1991. The goals of the registry are to improve the understanding of Gaucher disease, provide treating physicians with recommendations to optimize patient care, and to evaluate the long-term effectiveness of enzyme replacement therapy. The registry includes data on more than 4,500 patients, collected from participating providers in 56 countries. Several publications have resulted from the registry data.

  Registries also exist for many other conditions, including Fabry disease, Pompe disease, and congenital cytomegalovirus. No complete list of orphan disease registries exists today, except to the extent they are listed in 

. This may change, though, as interest in rare disease registries is growing. 

The current interest in rare disease patient registries will likely lead to the development of many more such registries. However, the development of each individual registry requires significant effort and resources. For some diseases, well-organized private foundations or manufacturers with an interest in product development or monitoring are capable of developing effective registries. To date, private foundations and manufacturers have generally developed registries independently, and, currently, there are no widely used models for collaboration or data sharing. However, private foundations are moving toward developing clearer rules for engagement with manufacturers. 

For many other diseases, there are few resources to support an independent registry. Some efforts are underway to develop linked networks of registries for rare diseases. For example, the NIH has put forth the idea of creating a federation of Internet-based registries for rare diseases. The goal of this effort is to reduce the costs of developing and running a registry. The idea was part of the discussion at a January 2010 conference on patient registries and rare diseases sponsored by the NIH's Office of Rare Diseases Research.

Another major issue for rare disease registries in the near future will likely be the collection and storage of biosamples. Much research is focused on the genetic origin of rare diseases, and researchers are increasingly interested in obtaining and storing biosamples from patients for future analysis. Storage of biosamples raises new legal, ethical, and logistical issues, particularly for global registries. These challenges will need to be addressed to support ongoing genetic research. 

Patient registries offer many advantages for rare disease research, due largely to their flexible design and ability to follow a broad group of patients for long periods. Given these advantages and the positive results of rare disease registries to date, it is likely that more rare disease registries will be developed in the near future. These registries may play an important role in improving understanding of rare diseases, developing guidelines for disease treatment and management, and providing information to support the development of new treatments. 

 MPH, Senior Research Associate at Outcome Science Inc, 201 Broadway, Cambridge, MA.

* To whom all correspondence should be addressed. 

 National Institutes of Health, Office of Rare Disease Research, "Rare Diseases and Related Terms," 

http://rarediseases.info.nih.gov/RareDiseaseList.aspx?PageID=1

 National Institutes of Health, National Human Genome Research Institute, "Rare Diseases Day 2010," 

 Denis Gill and Ronald Kurz, "Practical and Ethical Issues in Clinical Trials," 

Articles

Researchers are turning to patient registries to fill rare-disease knowledge gaps.

Patient Registries and Rare Diseases

As health care stakeholders, from regulators to providers to payers, demand more evidence on the safety and effectiveness of drugs and medical devices in real-world use, they are also increasingly asking life science companies to develop patient registries to fulfill this need. 

(PHOTOGRAPHY: MARTIN POOLE, GETTY IMAGES ILLUSTRATION: PAUL A. BELCI) 

Since registries are similar in many ways to clinical trials, on first review a CRO partner—strong in trials—would seemingly also be strong in patient registries. However, it is in fact the subtle (and not so subtle) differences that make this a potentially risky assumption for a purchaser. 

For a number of reasons, an organization's need for designing and operating high-quality registries at a reasonable cost is best met by partnering with service providers that are experienced in this rapidly evolving research space. 

Registries are a valuable pre- and postapproval tool. In general, registries provide complementary data to that obtained from trials and are an increasingly important tool in safety surveillance. 

In addition to safety evaluation, they are particularly useful for generalizing the findings of clinical trials to populations not studied in those trials and for evaluating the impact of physician decision making and actions on patient care. 

Registries are also being utilized for observational comparative effectiveness studies because they can provide useful information at a lower cost than alternative methods. 

These efforts require specialized knowledge in design and evaluation. More importantly, whether for review by a regulator evaluating a risk evaluation and mitigation strategy (REMS) or by a journal editor considering a registry manuscript for publication, registries are now judged on quality. 

Registries for Evaluating Patient Outcomes: A User's Guide

 by the Agency for Healthcare Research and Quality, the ability to review a registry on its quality has become common.  

Many CROs have extensive experience with Phase I–III and sometimes Phase IV trials, but have not managed a proportionate number of registries, cohort studies or quasi-experimental designs. In choosing your partner, consider:  

Does the CRO have specific standard operating procedures (SOPs) and personnel focused on registries or are they borrowed from clinical trials?

Have you reviewed the training and experience of the team that will be working on your registry?

While some functions are similar between clinical trials and registries, there are two key areas that are not: scientific skills (including protocol development, advisory panel guidance, biostatistics, and publications) and operations (including project and site management). Look for specialists in these critical areas—CRO personnel that focus entirely on registries and similar real-world studies and do not cross between study types. 

A patient registry is "an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition or exposure, and that serves a predetermined scientific, clinical or policy purpose."

While clinical trials focus on efficacy—the extent to which medical interventions achieve health improvements under ideal circumstances—registries provide strong evidence for the extent to which medical interventions achieve health improvements in real practice settings. 

A single standard does not exist for the conduct of observational research, but there are a series of publications and consensus efforts that can serve as guides to registry design and evaluation. These include AHRQ and their 2007 handbook mentioned earlier, the GRADE Working Group,

  These resources serve as useful guides in shifting from a trial focus to an observational strategy. 

An effective CRO partner will field a scientific team that will guide your organization through key stages of the registry, including developing a good protocol and case report forms; making an advisory board effective; and, generating high-level publications for top tier journals. 

A quality registry begins with a good protocol. If a protocol is hard to understand or provides irrelevant background information, it can confuse or alienate physicians. As a consequence, it can compromise the study's ability to recruit sites and enroll eligible patients. A registry protocol that is forced into a clinical trial template can cause incorrect, and often unnecessary, safety reporting. 

A scientific partner must have the ability to write a clear, simple protocol that will provide guidance on the different safety requirements that exist for a registry—not a clinical trial—and then facilitate the regulatory team in determining the appropriate procedures for the study. 

In addition to protocol complexity, there are several other telltale signs of an inexperienced CRO working on a registry. Identifying the right data to collect requires an understanding of the analytical needs in the future; data sets can be broader and are generally focused differently than for a clinical trial. A CRO must understand what the minimum data set should be and how much data is too much. 

Beyond the protocol, the scientific partner must also be able to educate registry advisors on the purpose and power of a registry; that education is typically ongoing throughout the registry. If the advisory board and CRO are inexperienced with registries and do not fully understand the benefits of the design, the reasons it was chosen over a trial, and what the pitfalls are along the way, all too often the project will drift to the more comfortable clinical trials paradigm—sometimes with disastrous consequences. 

A third common problem with an inexperienced scientific team is that the benefits of the registry in terms of output are not realized. While certainly the lack of appropriately sophisticated analytic support for observational data will limit success, even more commonly, inexperienced CROs and advisors set expectations too low for registry outputs. 

Good registry data and quality manuscripts from them are in high demand from top tier journals. Lower tier journals should not be the expectation for manuscripts produced from a high-quality study. If the CRO isn't suggesting top scientific journals for your registry, that could be a red flag. 

Sponsors should review the publication lists of potential partners and ensure that the CRO has successfully published results from patient registries in high-quality journals. 

The project management and site communication teams must also understand the unique considerations of observational research and be able to explain these to the enrolling physicians and other data contributors. The issues they encounter are frequently different than in a clinical trial. 

For example, site managers may need to explain to a site why a registry does not pay for health care services. The CRO registry team must have the ability to build strong relationships with sites typically with lower payment levels than in a trial. The CRO must have methods to engage the practices or they will lose motivation and enrollment will lag. 

A good understanding of technology and physician practice workflow is important in implementation, as busy practices commonly ask for workflow recommendations that are not commonly seen in clinical trials—which rarely take place in small, private practices. Appropriate technology, particularly technologies that provide workflow tools and can integrate with billing systems or electronic health records, can also be vitally important to successful implementation. 

Quality assurance is a key area where registry operations and ultimately registry data will be judged. Registry experts have advocated for a risk-based approach to identifying the most likely causes for error and diligently creating processes and procedures to both avoid likely errors and to evaluate and report the types of errors that occur. 

Because the types of bias that enter observational research are different than in a randomized trial, the quality assurance procedures also may need to be different. Simply borrowing QA processes from clinical trials can both dramatically increase costs and, at the same time, fail to provide the assurance of quality that is being sought. 

This is a common and often very costly error of CROs inexperienced in high-quality registries. 

With increasing global requirements for sponsors, leveraging a registry across multiple countries is both efficient and often necessary. Experience in conducting registries in the countries targeted for the registry is often critical. 

Ethical regulations, in particular, vary internationally for observational research, and they are not the same as those that govern clinical trials. For example, each of the 27 member states in the EU defines its own legislation pertaining to when ethical review is needed. Not all of these are clearly defined, and some countries allow local regions to outline their own specific requirements. Some countries, such as Germany, have additional regulatory requirements for observational research that one might not expect if accustomed to managing U.S. studies. 

If a CRO partner does not fully understand the requirements of the regions in which an observational study is being conducted, it will, at best, result in spending unnecessary time and funds on regulatory approvals. Even worse, lack of global knowledge could lead to a violation of international ethics regulations. 

A robust understanding and background in observational research, beyond clinical trials, is essential for a successful registry. Key components of the niche expertise in patient registries that should be sought in a CRO partner include:  

Site management and technology capabilities

Global regulatory experience in observational studies.

Registries are large investments with tremendous opportunities to generate return on those investments. Selecting the right partner is more often than not the primary determinant in the ultimate success of the registry. Choose wisely. 

is research coordinator of Outcome, 201 Broadway, Cambridge, MA 02139, email: 

Similarities exist, but successful design requires that CROs understand the differences.

Clinical Trials vs Registries

Recent safety issues associated with several blockbuster drugs, such as the Cox-2 inhibitors and antidepressants, have raised tremendous public and governmental concern regarding the safety of drugs and devices on the market. This publicity is naturally creating a more cautious and reactionary environment around the approval of new drugs by the Food and Drug Administration (FDA). This reaction, unfortunately, comes at the very time when it had been hoped that the approval process would be more streamlined and that promising, innovative therapies would be approved more quickly.  

 Photography: Comstock  Illustration: Paul A. Belci			

While the problem of slower approval cycles seems likely to worsen rather than improve, a solution is already at hand. New technologies and methodologies being applied in Phase IV safety studies and registries create an opportunity to change the paradigm to a proactive and systematic postapproval approach to detecting, estimating, and controlling risk as early as possible after approval. This approach is necessary because it is often not reasonable or possible to have all relevant safety information available prior to approval.  

A proactive approach to postapproval risk management and safety monitoring has two important components. First, the public should be educated on the limitations of pre-approval testing and the current postmarketing surveillance process of FDA's MedWatch, as well as programs from other initiatives and independent groups. Second, pharmaceutical companies should create and advocate safety registries as well as targeted safety studies and controlled distribution systems for situations where risk is not fully known at the time of approval (e.g., for potential blockbusters) or where risk is known but primarily confined to populations that can be readily identified.  

By proactively addressing safety issues through programs that improve on the industry's ability to monitor, detect, and act on adverse events in a broad patient population, pharmaceutical companies can make a stronger case for more rapid approvals and allay concerns for future blockbusters. 

 Figure 1. Safety registry with controlled distribution program.			

Two related limitations of pre-approval trials, which are difficult to overcome prior to approval, demonstrate why the anticipated reaction of slowing the approval process may be counterproductive.  			

First, pre-approval studies can only include a tiny fraction of the aggregate number of patients who will eventually be exposed to a drug or device. Second, pre-approval studies are often not fully representative of the population who will eventually receive the product for both scientific and ethical reasons. Taken together, these two limitations virtually guarantee that there will be subpopulations of patients in whom safety has not actually been assessed in the pre-approval phase.  

With blockbuster drugs and devices, millions of patients are treated with the product and it becomes more likely than not that some patients, whose genetic constitution or co-morbid health status places them at greater risk than those included in the pivotal trials, will be "exposed." It is a matter of numbers.  

While the relative risk in these population subsets may be very low, events will still occur. The general public needs to be educated that it is not possible to predict all potential safety issues prior to approval. Therefore, in order to enable promising therapies to be approved with reasonable amounts of pre-approval data, a new emphasis is required on effective, early detection systems. 

Currently, postapproval safety signal detection is primarily managed through voluntary, spontaneous reporting methodologies such as the the FDA's MedWatch program. This program is under intense scrutiny for failing to detect the recent high-profile safety cases. MedWatch, programs managed by its sister agencies like the European Medicines Agency (EMEA), and other United States agencies such as the Centers for Disease Control and the Consumer Products Safety Commission

 can be effective in identifying unusual adverse events. However, they are less likely to be effective in picking up a safety signal when the signal itself is a common event like heart attack or stroke. This is because the MedWatch system does not have a true "denominator." 

In other words, in order to calculate an incidence rate for events, one needs both the true number of events from a given population (numerator = number of patients with event) and the size of the population at risk (denominator = number of patients with event plus number of exposed without event). These calculations assume that the population at risk is being fully reported on (if an event occurs, it will be reported). With spontaneous reporting, the denominator cannot be known (or even estimated) with certainty since not all events that occur are detected or reported. The March 2005 FDA guidance documents on pharmacovigilance have clarified but not changed this spontaneous reporting paradigm.

In contrast, Phase IV safety registries and studies have a greater likelihood of selecting subjects representative of those who actually receive the drug or device, and in greater numbers than can typically be recruited in an earlier phase trial. They also provide a clear denominator. As a result, they generate a more statistically representative sample for monitoring for the adverse effects likely to be seen in the general population. 

When an adverse safety event is known, specific Phase IV studies can be developed to look for an increased event rate in larger and more diverse populations in a hypothesis-driven way. Specifically, studies are developed to address the safety question in a representative population of patients enrolled from real-world clinical sites. These studies are undertaken in a rigorous fashion with data safety monitoring boards and clear stopping rules. They are launched at or sometimes prior to the time of approval (collecting background safety data prior to the approval) and extend until appropriate sample sizes in several subpopulations are achieved. 			

When not all adverse events are known, as is the case with all drugs destined for blockbuster status, a safety registry is currently the best means for early detection of unanticipated adverse events. In a well-designed safety registry, a representative subset of patients receiving the drug or device are enrolled, and followed prospectively. Serious adverse events are universally collected and reviewed based on meeting specified definitional criteria, not specific anticipated event types.  

Effective early detection should require that the data be collected in a central database that is available in real-time for evaluation by a designated data safety monitoring board. Otherwise, there is a risk of delay in detection that would undermine the intent of the program. In certain systems, this capability is augmented by utilizing real-time algorithms to assess data for each patient for the possibility of an adverse event that may not have been recognized by the practitioner. If one is found, it alerts the sponsor and data safety monitoring board to the possibility. No system can be flawless, but attempting to detect elevated risk systematically rather than in an ad-hoc fashion is certainly a more effective way to monitor safety. 

Unlike the FDA's system, which relies only on spontaneous reporting, a safety registry increases safety signal detection and processing as a data safety monitoring board reviews results on both a scheduled and ad-hoc basis (if increased signal is detected). When data is collected and processed in real-time through Web-based or voice-based systems, the opportunity to detect an increased safety signal and to act upon it rapidly is enhanced. Such programs can serve to alleviate practical and potentially political concerns of regulatory agencies for early detection of potentially unsuspected adverse events. Physicians agree that if pre-approval studies cannot predict the safety risk, then early detection of increased safety signals in combination with a predetermined action is the next best thing.

 A well-designed, real-time, safety registry is currently the best means to accomplish that. 

Some drugs with known adverse events can still have significant (and safe) effectiveness in certain populations. In these cases, a safety registry can be expanded to include a controlled distribution arm. Such programs systematically limit distribution of drugs at the pharmacy level to patients who meet specified demographic and lab test criteria. Using an information technology system, including Web and interactive voice response, these programs function in real-time to provide authorization or denial at the point of prescription or distribution. Examples of such programs include those for thalidomide, clozapine, and others. 			

These programs are generally mandated by the FDA rather than proactively suggested by pharmaceutical companies. However, that need not be the case if a new drug has a safety profile that would suggest this as an initial course of action. The pharmaceutical company can in fact suggest such a program as part of a risk management action plan. While not ideal from a utilization perspective, a contingent approval is better than none at all.  

Therefore, for certain drugs with an overall concerning risk profile, but a subpopulation in whom the drug is both effective and safe, a proactive risk management program using a safety registry with a controlled distribution component should be considered. If the drug or device demonstrates real-world safety after a defined period of time, that contingency can expire and the drug could be made generally available. 

Will a "safety registry" scare off prescribers?

 Some sponsors have concerns about the implications that the proactive use of a safety registry might have on the general view of the safety of a product after launch. In reality, the recent withdrawals of several products have raised general concern among providers about the safety of new products and the limitations of the pre-approval process. They are welcoming all efforts to improve signal detection. 			

With an understanding of the inherent potential risks of all drugs and training to constantly evaluate new data regarding prescribed therapies, the physician community will have more confidence in a process that includes systematic postapproval evaluation, rather than blind trust that every possible safety issue was detected in preclinical studies.

 In fact, the first major sponsor to announce safety registries on all approved blockbuster products might take the position of the "safety" company, a position highly valued in other industries, but not yet claimed by a major pharmaceutical company. 

Furthermore, Phase IV studies and registries offer additional benefits to sponsors. First, they provide useful safety and scientific data to prescribers through publications and, in some cases, directly through the Internet. Second, they provide an abundance of real-world clinical data on disease outcomes, product usage, product value, and market dynamics. Properly managed, data from these studies can generate a plethora of publications which may in fact speed the time to peak sales. 

 The hesitancy in routinely developing product or disease registries at the launch of every major product potentially comes from the concern of what to do if something is found. Sponsors and regulatory agencies are aligned on this point. If an unsuspected adverse event is detected as early as possible after product launch, the sponsor can not only mitigate some litigation risk but may potentially identify and contain the subsets of patients who are at risk from receiving the product and avoid a full product withdrawal. 			

With increasing genetic markers and predictive modeling statistical capabilities, it will be more and more possible to isolate populations at risk. With controlled distribution systems for pharmaceuticals, such as the risk management programs in place for drugs like clozapine, registries can be extended to control delivery of the medication only to patients who are approved to safely receive the drug. Modern information systems allow this at a relatively low cost at the point of care (see sidebar). 

Potential barriers to implementing a new approach

Transforming postmarketing surveillance to a systematic "monitor, detect, and act" approach is not without significant challenges. Clear definitional criteria for adverse event recognition need to be applied to help real-world clinicians in safety registries identify truly unexpected adverse events. Further, in some disease states, the background rates of certain adverse events (e.g., sudden death in epilepsy) are not well known. Comparator cohorts of patients without drug exposure would need to be constructed in parallel, thereby increasing expense. 							

Other data collection issues also need to be considered scientifically and practically. For example, universal registry enrollment of all patients on a newly approved drug would not only be expensive, but less likely to yield accurate detection data than a carefully constructed representative sample of clinicians and patients who agree to track more detailed adverse event information. Costs are another issue. While current electronic data capture techniques make it possible to collect structured data cost-efficiently, participating clinicians would likely require payment or other incentives to take on the data collection burden.  

There are of course ethical and privacy issues with real-world data collection, but these are not different than those being effectively addressed in existing safety registries, and the same principles should apply. Finally, with the global nature of many drug launches, the most practical strategy for integrating the surveillance programs across multiple markets and countries is an area for further discussion. 

By educating the public on the limitations of current safety detection, and proactively implementing systematic detection and control through postapproval Phase IV safety registries and controlled distribution programs where applicable, pharmaceutical companies can go a long way toward allaying government and public concerns of the inadequacies of our current postapproval safety net. Using currently available technology, companies can proactively recommend safety registries as part of risk management programs and potentially shorten the time to product approval. These programs also allay the concerns of prescribers, which ultimately shortens the time to product adoption. Proactive and strategic use of safety registries and controlled distribution programs may be the best means to keep the approval process on track in a time of increasing caution.  				

MD, is founder and president of Outcome, 201 Broadway, Cambridge, MA 02139 (

), and an associate professor at Harvard Medical School.

www.cdc.gov/mmwr/preview/mmwrhtml/mm5415a2.htm

2. Guidance for Industry Good Pharmacovigilance Practices and Pharmacoepidemiologic Assessment, http://

www.fda.gov/cder/guidance/6359OCC.htm#_Toc48124202

3. R. Harbaugh, Professor and Chair of the Department of Neurological Surgery, Pennsylvania State University.  

4. K. LaBresh, a cardiologist and vice president at the Massachusetts quality improvement organization, MassPRO. 

Registries could strengthen the postapproval safety net-critical in the current cautious environment.

Keeping Approvals on Track

Each year, many promising therapeutic agents intended to address some of our most serious unmet medical needs fail in clinical development due to the lack of efficacy or unacceptable toxicity. Inevitably, many of these agents offer significant clinical benefit for some patients. However, they often fail to demonstrate sufficient safety and efficacy across a larger patient population to the degree needed to surmount the high clinical and economic thresholds often established by pharmaceutical companies, regulatory agencies, and the marketplace.  

 Figure 1. Evolutionary Drug Developmentâ¢, a proprietary iterative process to         identify optimal rules.			

There is a growing body of evidence and increasing acceptance that many of these promising compounds can be made commercially and economically viable. By identifying patient subpopulations that are most likely to benefit from and/or least likely to adversely react to these therapeutic agents, researchers could "personalize medicine." This targeted approach holds the promise of more rapidly and safely bringing both old and new medicines to those patients most in need.  

Among the medicines that have become successfully commercialized consequent to identifying a responsive patient subpopulation is trastuzamab (Herceptin), an anticancer monoclonal antibody that targets the HER-2 growth factor receptor on breast cancer cells. It is approved as a single agent for second-line treatment and in combination with paclitaxel for first-line treatment of patients with metastatic breast cancer whose tumors specifically overexpress the HER-2 protein.

 Had this responsive subpopulation not been prospectively identified during the clinical development of trastuzamab, the drug would likely not have been approved in breast cancer, consequently depriving many women of a treatment that has proven to have prolonged many of their lives. 

On the other side of the equation are drugs that are efficacious in many patients but are not tolerated by some. Thalidomide (Thalomid) is the classic example of a medicine that has been commercially resurrected subsequent to its complete withdrawal from the world market (in 1961) for unacceptable toxicities. Initially promoted as a sedative and treatment of such conditions as asthma, hypertension, and migraine, it soon came into disfavor consequent to an associated epidemic of severe and often fatal perinatal malformations, most frequently phocomelia. Capitalizing on its diverse beneficial effects as an immune modulator and the successful identification of those patients for which it is contraindicated for safety reasons, thalidomide is now successfully overcoming its stigma as an unacceptably toxic compound and is showing promising activity in a wide variety of solid malignant tumors, multiple myeloma, graft-versus-host disease, and Crohn's disease.

Clozapine is another example of a medicine that has found a therapeutic niche despite being associated with significant toxicity, in this case life-threatening agranulocytosis. Clozapine was approved in 1989 for second-line symptomatic management of schizophrenia and is now being investigated for use in Parkinson's disease, Huntington's chorea, and depression.

The key to the successes of thalidomide and clozapine has been the ability to prevent their distribution to patients identified to be most at risk for their toxic side effects, namely pregnant women and those with severe granulocytopenia, respectively. In both cases, mandatory controlled distribution programs are in effect, helping to ensure the safe and effective prescribing, dispensing, and use of these two medicines.

There are three key challenges to introducing a personalized medicine approach to clinical practice: identifying the optimal patient subpopulation for receipt of a specific therapeutic agent, based on potential benefit-versus-risk; developing rapid, economical, accurate, and clinically practical methods for determining whether or not a specific individual belongs to such a patient subpopulation; and ensuring distribution of the agent to those for whom the agent will be potentially most effective and nontoxic.  

Although all disciplines of medicine could potentially benefit from the personalized medicine approach, this paper will concentrate on the challenges being faced in clinical oncology—a field that is fostering and benefiting from many emerging technologies and in which molecularly targeted therapies are showing great promise.  

Identifying the optimal cancer patient subpopulation

What can be done to ensure that there is a high likelihood that the patients entered in a clinical trial will respond to and tolerate a particular anticancer agent? Traditionally, this has been addressed by incorporating fairly standard patient inclusion and exclusion entry criteria in Phase II and III clinical trial designs. To some extent, this narrows the patient population down to including those that have at least some chance of responding while excluding those that are likely not to tolerate the treatment. Although this routinely generates an enrolled study population that would be commercially attractive if enough patients responded, the response rate is usually not high enough to convince most drug developers and regulatory agencies that marketing it for that indication is warranted.  			

This is a major cause for the high rate of perceived "drug failures" in oncology drug development and a source of much frustration for both investigators, patients, and the general public. A new clinical trial design paradigm that could potentially transform a drug failure into a drug success would be one that continues to narrow the target population to those patients most likely to benefit from such treatment while also continuing to tolerate it. 

Many novel molecularly targeted therapies are being developed in oncology. Although it is assumed requisite for anti-tumor activity that a compound's cellular molecular target be present on or in the patient's tumor, the degree to which this target needs to be expressed remains unclear. Although overexpression of HER-2 is required for trastuzamab to be clinically beneficial in metastatic breast cancer, the same appears not to be the case for those agents targeting the epidermal growth factor receptor (EGFR), such as gefitinib (Iressa) and erlotinib (Tarceva). For gefitinib in advanced non-small cell lung cancer (NSCLC), the presence of genomic mutations in the EGFR appears to correlate with gefitinib-induced tumor regression.

 However, in a large Phase III placebo-controlled registrational trial of gefitinib, such biological responses were relatively uncommon and did not translate into an overall statistically significant survival benefit for the advanced NSCLC patient population studied.

 In contrast, erlotinib has been shown to produce a significant prolongation of survival in advanced NSCLC.

In similar NSCLC patient populations, why did erlotinib demonstrate prolonged survival while gefitinib did not? The answer is likely hidden within the complexity and heterogeneity of tumor cells and the diverse biologies, demographics, and medical histories of cancer patients—all interacting to determine an individual's ultimate response to a particular anticancer agent.  

To answer such a question for oncology compounds in general, we are testing the hypothesis that by integrating the vast array of existent baseline patient and tumor information that is usually readily retrievable from concluded Phase II and/or Phase III studies of that agent, one can identify particularly sensitive, insensitive, tolerant, and/or intolerant patient subpopulations. Examples of such baseline patient and tumor data currently available include: patient demographics, medical history, response to prior cancer therapy, as well as tumor type, stage, and histology. Baseline tumor and patient genomic and protein biomarker data will become increasingly available in the near future and hold promise to significantly enhance the accuracy of such subpopulation assessments. 

To proceed with such investigations, the key question of what are the most clinically meaningful outcomes for the oncology compound under study first needs to be answered. Phase II trial designs may range from single-arm, uncontrolled studies that depend on comparison of results with historical controls to multi-arm, controlled studies that have a standard-of-care arm for comparison, as with Phase III studies. Depending on the intent of the trial, the stage and natural history of the cancer, and the mechanism of action of the study drug, clinically meaningful efficacy endpoints might include survival (e.g., one-year, overall, etc.), time-to-disease progression, the incidence of stable disease (as defined in the protocol), quality-of-life, and/or changes in cancer-related biomarkers, e.g., serum PSA in prostate cancer.  

The goal is to generate "outcome predictors" (a.k.a. "screening classifiers"), that can be statistically validated in subsequent proof-of-concept Phase II clinical studies. If shown to have adequate positive and negative predictive values, these new "rules" for patient selection can then be incorporated into larger targeted Phase III proof-of-efficacy trials. Because trials designed to incorporate such outcome predictors will require fewer randomized patients than untargeted designs, such an approach could potentially conserve significant amounts of drug development resources.

A major challenge to generating useful outcome predictors in this fashion, both now and in the future, is how to efficiently condense and analyze the ever increasing amount of baseline data obtained from a relatively small number of patients. Such information is derived from diverse technologies like quantitative immunohistochemistry, flow cytometry, polymerase chain reaction, fluorescent in situ hybridization, and gene expression profiling.  			

Whereas traditional statistical analysis, cluster analysis, and neural networks are available to tackle such analyses, their utility will become more limited as the number and diversity of input variables increase. An analysis technique that is particularly capable of handling such voluminous data is a machine learning approach called "genetic programming."

 Borrowing ideas from natural selection and population dynamics, genetic programming is an iterative analytical process that searches for computer programs that are good enough to survive in competition with others in a population of programs. The result is a set of computer programs that solves a particular problem, in this case the prediction of clinical response and/or tolerance to a specific therapy.  

Evolutionary Drug Development™ is a process developed by Genetics Squared that uses a proprietary implementation of genetic programming to describe a set of data, gaining insight into the data and suggesting how a drug can be best used for a particular patient population.

 This iterative process of analysis, research, and refinement affords powerful advantages over other approaches, namely: 1) the ability to combine very large and diverse data types (e.g., genomic, proteomic, medical history, etc.); 2) the ability to find novel combinations of factors; 3) the ability to combine variables in nonlinear ways; and 4) the generation of simple and readable rules that may support known mechanisms of action for specific targeted compounds and/or suggest novel molecular interactions that may warrant further investigation (Figure 1). 

A recent Phase II study conducted by a major pharmaceutical company had failed to meet internal thresholds for success with approximately 25 percent of patients experiencing stable disease (SD), as defined in the protocol and appropriately reflecting the natural history of the cancer under study. Team statisticians at the company had been unable to correlate the occurrence of SD with any of the biomarkers or other clinical variables captured.  			

The pharmaceutical company wanted the data analyzed to see if there was a correlation. They supplied to us approximately 30 demographic and medical history variables, efficacy outcomes, and four types of tumor biomarker values obtained by immunohistochemistry. Employing Evolutionary Drug Development™, a predictive rule was discovered very early in the analysis of baseline information that was greater than 70 percent accurate in predicting whether or not a patient would achieve SD (unpublished results). This rule used a single tumor biomarker that the clinical team had assumed was not important because it was highly expressed in all patients' tumors. Our rule discovered a difference between high and very high expression of this biomarker. While the rule was very good at predicting who would not respond (i.e., specificity), it was poor at predicting positive responses (i.e., sensitivity).  

If the drug were being developed to treat a non-life threatening disease and was known to have safety issues, then this would have been an excellent rule. However, because the compound was tolerable and was being developed for metastatic cancer, this rule would miss too many patients that could benefit from it. Therefore, subsequent data analyses were focused on identifying a new rule that optimized sensitivity versus specificity.  

The new predictive rule combined medical history and demographic variables with two biomarkers to produce a much more compelling rule with similar overall accuracy, but sensitivity over 90 percent. If this rule had been used to screen patients for the clinical trial, it would have missed only two patients and resulted in a 60 percent incidence of SD in this patient subpopulation—a compelling outcome for a compound being developed for a metastatic solid tumor. The pharmaceutical company was excited enough by these results to request reviews of two additional Phase II studies of this compound in other tumor types, as well as a clinical study of another oncology compound. These studies are ongoing.  

Practical implementation of personalized medicine

Challenges inherent in the practical implementation of personalized medicines include:

1) producing and validating reliable pharmacodiagnostic tools that can be used by community physicians to help them formulate treatment strategies for individual patients; and 2) convincing regulatory authorities that this novel method of patient selection will ensure adequate levels of patient safety. Matching patients to the most appropriate and promising therapeutic agents must be rapid, economical, accurate, and clinically practical.  							

Aside from reviewing responses to prior treatment modalities, patients and their tumors are tested against a variety of predictive rules and panels of biomarkers. These rules and biomarker data might be housed in large registries that can be accessed in real-time by the prescribing physician or dispensing pharmacist via the Internet or telephone to maximize distribution of drug to "safe responders."  

The clozapine patient registry managed by Outcome houses predictive rules along with specific patient information that permits ongoing checks to be made for specific patterns of response or toxicity each time a prescription is refilled. Using registries such as this as a model will help to ensure the continued safe and appropriate use of drugs after approval. Such successful integration of predictive rules and biomarkers with information technology permits the reliable point-of-care access that is key to enabling personalized medicine to quickly move from the laboratory to the clinic. 

The era of personalized medicine is here. Many medicines that have had their clinical development discontinued or that have been withdrawn from the marketplace due to lack of perceived benefit or excessive toxicity may be able to be rescued and successfully developed if a sensitive and tolerant patient subpopulation can be identified. By finding new and better defined niches for medicines of all types, many novel compounds will become available to those patients that are most likely to benefit from them, while also permitting the use of quicker and less expensive clinical trials during their development.  			

Evolutionary Drug Development™ is an implementation of genetic programming that is being used at the forefront of this effort, one well positioned for meeting the challenges of making sense of the exponentially increasing amount of available patient and tumor data that needs to be analyzed.  

Finding the right rules and markers is but the first critical step. The next step, moving personalized medicine from the laboratory to the clinic, will require increasingly sophisticated methods to deliver the right information rapidly and reliably to prescribers and pharmacists. To this end, real-time accessible, computational patient registries that are focused on appropriate drug distribution are already in use. These, together with cutting-edge technological approaches like Evolutionary Drug Development™, are spearheading the transition of personalized medicine from bench to bedside and hold much promise for rescuing many valuable compounds along the way.  

1.  Herceptin (Genentech): Full Prescribing Information, revised October 2003. 			

2.  M.E. Franks, G.R. Macpherson, W.D. Figg, "Thalidomide," 

3.  Clozapine (Mylan): Full Prescribing Information, revised January 2003. 

4.  Thalomid (Celgene): Full Prescribing Information, revised February 2004. 

 "Activating Mutations in the Epidermal Growth Factor Receptor Underlying Responsiveness of Non-small-cell Lung Cancer to Gefitinib," 

6.  Doctor Letter Regarding Iressa (gefitinib) ISEL Data (December 17, 2004): A double blind, placebo controlled, parallel group, mulitcentre, randomised, Phase III survival study comparing IRESSA (gefitinib) (250mg tablet) plus best supportive care versus placebo plus best supportive care in patients with advanced NSCLC who have received one or two prior chemotherapy regimens and are refractory or intolerant to their most recent regimen. AstraZeneca Pharmaceuticals LP, 2004.  

7.  Tarceva (Genentech; OSI Pharmaceuticals): Full Prescribing Information, initial November 2004. 

8. R. Simon and A. Maitournam, "Evaluating the Efficiency of Targeted Designs for Randomized Clinical Trials," 

9.  J.R. Koza, Genetic Programming (MIT Press, Cambridge, MA, 1992). 

10. D. MacLean, E.A. Wollesen, W.P. Worzel, "Listening to Data: Tuning a Genetic Programming System," Genetic Programming Theory and Practice II, U.-M. O'Reilly, T. Yu, R. Riolo, W.P. Worzel, eds. (New York, Springer Science+Business Media, Inc., 2005) pp. 245-262. 

is president and CEO of Genetics Squared, 210 South Fifth Avenue, Suite A, Ann Arbor, MI 48104, (734) 929-9475, fax (734) 929-9477, email; 

is president of Outcome, 210 Broadway, Cambridge, MA 02139, (617) 621-1600, fax (617) 621-1620.

A new paradigm that could transform a drug failure into a drug success would narrow the target population to those patients most likely to benefit from such treatment.

Richard Gliklich, MD

Articles

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Clinical Trials vs Registries

Keeping Approvals on Track

Rescuing Drugs Through Personalized Medicine