CLINICAL TRIALS
Employing real-world evidence allows for the study of many aspects of diseases, such as natural history, patient populations, and outcomes, under everyday conditions. Therefore, real-world evidence has many applications in clinical research, ranging from optimising clinical trial design and population/outcome selection to reducing the burden of regulatory commitments. Sumeet Bakshi, Vice President, Real World Data Solutions, Certara’s Evidence, Value & Access group Richard Tao, Associate Principal Regulatory Writer and Submission Leads Member, Synchrogenix, Certara’s regulatory science company
Under clinical trial conditions, a patient with diabetes who is prescribed an anti-diabetic drug must adhere to the study protocol and their outcome is measured based on that protocol. If the patient misses several doses, their data may need to be removed (or censored) from the final analysis dataset. Poor medication adherence is not typically factored into a clinical trial. However, in the real world, people frequently forget a dose of medicine, take the wrong dose, or take it at the wrong time. Medication adherence is just one real-world example; there are many others that need to be considered when trying to truly understand patient outcomes. For example, inclusion and exclusion criteria for a clinical trial prevent people with specific comorbidities or prior treatments from participating in the trial. Many of these people are likely to receive the intervention in real life despite not qualifying for the RCT. A real-world study generally includes a wider variety of people and circumstances and better reflects everyday situations. However, the experimental design of traditional RCTs allows for easier isolation of the treatment effect of one therapy compared with another as it is less subject to the bias which can present challenges in analysis of Real-world Data (RWD). Thus, RWD are usually employed in conjunction with and in complement to RCTs rather than as a replacement for them.
Challenges Using Real-World Data
Despite their obvious advantages, the adoption of real-world studies involves challenges such as gaining access to and managing the heterogeneity and messiness of the data. The Real-world Evidence (RWE) currently being generated is predominantly from structured data, i.e., electronic medical records, Electronic Health Records (EHRs), and healthcare claims. These data sources, although large and complex, form the tip of the iceberg, as many other data sources, such as free-text entries, paper records, telephonic and video consultations, images, or video camera footage are now available and could form valuable RWE input. Increasing Adoption of RWD in Rare Diseases/Populations
Rare disease research is an area that can benefit greatly from using RWD. Many rare diseases are not well studied, their natural history is unknown, and the outcomes that should be targeted are unclear. Traditional RCTs include treatment and control arms in which participants receive the current standard of care or placebo. Of course, in the case of rare and orphan disease populations, a sufficiently powered traditional RCT may be very difficult to carry out due to recruitment challenges and the potential absence of a current standard of care. As a result,
single-arm trials are increasingly being relied upon as pharmaceutical companies focus on small populations in therapeutic areas of extremely high unmet medical need. This phenomenon is not only limited to rare and orphan disease populations, such as Batten disease and Lennox-Gastaut Syndrome, but also includes smaller underserved segments of more common diseases, such as HER2negative hormone-positive breast cancer or non-muscle invasive bladder cancer, where there is no current effective treatment available. Similar scenarios occur with some types of advanced cancers where the disease is both rare and life threatening, making it impractical and unethical to recruit a control population for a clinical trial. In these instances where it is not possible to establish a control group, regulators and payers are increasingly accepting single-arm trials, but they prefer to see some comparative data as part of the marketing authorisation submission. With single-arm trials, RWD can be used to generate an external comparator arm; a practical approach that also saves time and lowers costs. Creating an External Comparator Arm
Regulators are often interested in the use of so-called natural history studies to offer pure external comparators, especially in circumstances where there are no approved treatments or accepted standards of care. However, the term natural history is really a misnomer because all patients receive at least some kind of intervention in the real world. Even in cases where there is no standard of care, doctors always try to alleviate patients’ symptoms with some type of treatment. Consider Batten disease, which refers to a group of rare, fatal, inherited nervous system disorders that affects about 50 children in the UK. These children have about 20 to 25 seizures a day and reduction in seizure frequency is the desired outcome. Although there is no approved treatment, doctors do prescribe different
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