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Firstly we will consider the context of clinical trials. A traditional trial uses a method called Randomized Clinical Trials (RCTs) that usually allows us to confirm the effectiveness of a drug in the general population. This method is based on splitting a cohort in different groups of people in which some will receive a potential drug that will meet their needs and others will receive a placebo (drug with no active ingredient and will cause no effect). All new treatments need to be tested in clinical trials to find out whether they work , what side effects they have and whether they are as good or better than the standard treatment available. After a long development process researchers use randomise trials to be sure that the results are correct and not biased for any reason.

Watch the following video explaining the concept of randomization in research studies and what potential participants need to know when volunteering for a study with a randomized design.

Find out below the Cancer research UK video on how and why researchers use randomisation to test new treatments. National Cancer Institute also made available Randomization in Clinical Trials.

But, what happens when it is not possible to carry out RCTs such as in the case of rare diseases like CDG due to the extremely small size of the populations? In these situations data from observational studies could be regarded as the main factor in the regulatory decision-making. However, "there is a stronger scientific justification for deriving evidence of a drug effect from randomized controlled trials as compared to observational studies'' says the Food and Drug Administration (FDA) (1). There are cases where observational studies and randomized trials reach the same conclusion. But there are others that do not; although in addressing cases where it is impossible to create the so called “traditional trials”, Real-World Evidence (RWE) might be key as a complementary source to enhance the findings in a clinical trial setting. These conveniences are going to be addressed below where we will share how RWE has major benefits for rare diseases like the CDG.

The youtube channel OBRoncolog has developed a video named “ Real-World Evidence Compared to Randomized Clinical Trials” that is ideal for anyone who’s trying to understand the difference between RCT and RWE


Five facts why Real-World Evidence (RWE) as a complementary source to enhance the findings in a clinical trial setting for rare diseases like CDG


  • Better Individual Selection

RCTs set up a homogenous population for clinical trials. During initial clinical trials, Real-World Data (RWD) has a heterogeneous cohort and  if used correctly, the effectiveness of the orphan drug can be generalized, something that is extremely important in rare disease research like CDG (2). This population of individuals might be selected through their distinct variations that  their disease might have, something that is possible to recognize and understand because of RWD/E. The data collected can help to assess different individuals through inclusion and exclusion criteria previously chosen based on the data input in order to include a broad range of individuals in the study and possibly diminish the length of the trial.

  • Single Arm Study

Traditionally, clinical trials always had a placebo control group, but in the field of rare diseases that seems rather impractical due to the geographic dispersion of the low numbers of people living with the condition and the high costs involved. Researchers in the field of and people suffering from rare diseases seem to be big advocates of such single-arm studies.

RWE allows nonrandomized single-arm studies with external synthetic control arms (3) which is a control group that is created through the analysis of data collected from different observational studies about the people that live with the disease in question. The application of an external control arm is promising, but to support the efficiency of an orphan drug the control group (group of people that take the placebo) must have similar specific characteristics as the individuals who are tested during the trials (4). The parameters of selection are priorly assessed and can be applied in a statistical algorithm to search for proper matches. This type of methodology is based on prior natural history studies made to the condition in question and a group of that same cohort, which is administered an experimental therapy and is monitored continuously over time. This new approach can be used in different cases where there is a small cohort, such as new genetic therapies procedures (5). For instance, Leanne Larson, MHA, corporate vice president and worldwide head of real-world evidence for Parexel, carried out one of these trials with an external synthetic control arm in a phase II oncology study. Larson believes in the importance of RWE, but she adds that it is very difficult to work with due to the fact that the data provided has to be the most accurate and must fulfill the requirements as well as give the right information about the right cases which implies that some of the sources will end up dropped along the way. Nowadays, in the field of rare diseases, new observational studies are being made with potential applications as synthetic control arms (6). These studies aim to aggregate numerous registries of people living with a certain condition, and they are made through a number of years to understand the different factors that may or may not help a person to improve their health status. Moreover, it is recommended and stated in the guidelines published in 2018 by the FDA (1), as it was stated in another section, to use synthetic control arms based on natural history studies. Although typical synthetic control arm data comes from previous research, the FDA stated that RWD can be applied as the basis of this control arm in light of low number of people living with a rare disease to clinical trials which can be pertinent regarding diseases such as CDG.

A webinar entitled Using Real-World Data in Single-Arm Clinical Trials led by Syneos Health, describes the fundamentals of synthetic control arms with a focus on oncology trials, highlighting when they are done, why they are done, and how they are done.

At the following webinar named Synthetic Control Arms in Clinical Trials and Regulatory Applications, Arnaub Chatterjee is Senior Vice President of Product and Ecosystem at Medidata Solutions, discusses the methodology and applicability of synthetic control arms, especially those utilizing large clinical trial datasets, in biopharma R&D. Examples where synthetic controls have successfully been used in FDA applications are also discussed, and the emerging regulatory framework. Watch it here.

  • Decreased diagnosis time

A common issue in the CDG spectrum is the endurance of an odyssey diagnosis. This comes from the lack of awareness of doctors and other stakeholders in light of a deficiency in definitive diagnosis for different rare diseases (7). For many orphan disorders, the accurate diagnosis takes a long time and is replete with appointments, specialists from different areas of expertise, misdiagnoses, etc. This is a considerably demanding process for people who live with rare diseases like CDG and the standard treatment regimen currently established in hospitals might create unforeseen hurdles with their diagnosis until the accurate conclusion is even weighed on the table as a possible outcome. RWD is an essential asset to create algorithms that can be applied to create evidence and, consequently, quicken the process of diagnosis. Read more here.

  • Accelerating Orphan Drugs Approval

As previously noted, RWD and RWE are very useful in the study of rare diseases where it is not possible to generate a control group, resulting in the need of using data and evidence from previous research like natural history data from observational studies. In the same context, this overall context allows the accelerating approval of orphan drugs. The information collected from studies provides insights of how to better improve and leverage these trials as well as their. This way it is possible to fasten the research and might be a way to find a solution to people who live with certain condition unmet needs. 

For complementary reading: 

  • The Evidera white paper Rare Diseases and Orphan Drugs discusses the current state of moves to address challenges associated with current regulatory and reimbursement frameworks for patients with rare and orphan diseases. Download it here.
  • Check the The Syneos Health report entitled Real World Value: Advancing Payer Understanding of RWE in Rare Disease
  • Expanded Access

Nowadays, RWD can be useful in a lot of ways. New methods are being applied to extend the approval of various drugs. Regulatory agencies, such as the FDA and the EMA are raising the number of Expanded Access (EA) programs with the aim of increasing RWD (2). EA is the use of an unapproved drug or medical device under special conditions, usually people with serious or life-threatening conditions who do not meet the conditions to enter a clinical trial in progress.

The growing number of approvals comes as a response to the rising demands of people for therapies and the increase in applications of RWE in regulatory decision making. Traditionally, EA was used only for treatment purposes to find unmet clinical needs of people who live with certain conditions like CDG and not for research, but this has changed over the years and now EA data is a type of RWD that supports drug applications (2). Furthermore, some countries in the European Union prohibit the collection of data in EA programs stating that “no other data except pharmacovigilance data can be gathered which will only be used for the evaluation of the UMN (red: Unmet Medical Need/expanded access) program.” (8). Furthermore, the results of the collected data seem promising and in the long term might have a positive effect in the rare disease community like CDG.

Examples of EA

  • A clear example of EA achievement comes from a treatment applied in breast cancer which was at first practised only on women because the clinical trials only had female subjects. Notwithstanding, in the United States of America, a secure approval for male subjects was possible due mainly to electronic health records (EHRs) regarding its off-label use in male individuals (3).
  • Another example is the conditional approval of elosulfase alfa (Vimizin) for the treatment of mucopolysaccharidosis type IVa which is a rare disease (9). In 2015, The National Institute for Health and Care Excellence (NICE) conditionally approved and recommended an orphan drug, Vimizim, as a possible therapy against a rare limiting genetic disorder: mucopolysaccharidosis type IVa. In this same guidance, it is referred to the fact that this drug is very expensive, and, therefore, should be conducted experiments to generate real-world evidence about this drug and how it affects the disease in order to create “data directly relevant to patients in the UK”.  This precedent can potentially be put in an application in rare diseases like CDG as a mean to accelerate orphan drug approvals.

For complementary reading about Expanded Access:

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Alexandre Gil and Pedro Granjo from Sci and Volunteer Program Nova School of Science and Technology 2021.


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Page modified at Tuesday, May 11, 2021 - 09:50