Real World Evidence (RWE) complements clinical trials and provides additional insights that are difficult to achieve in controlled environments. Here’s why:

[1] Sample Size and Diversity: Clinical trials often involve a relatively small and selected population, while RWE studies involve larger and more diverse populations. This allows for a better understanding of the safety profile of a drug among different demographics, including age, race, gender, and individuals with different comorbidities.

[2] Long-term Follow-up: Clinical trials usually have a limited duration, while RWE can provide long-term safety data, including rare side effects that may only become apparent over time.

[3] Real-World Setting: Clinical trials are conducted in controlled settings and follow strict protocols. The patients who participate are often healthier and more adherent to treatment than average. On the other hand, RWE reflects the real-world setting, capturing the effects of the drug when used in routine clinical practice, which can differ substantially from trial conditions.

[4] Poly Pharmacology (Concomitant Medications): In the real world, patients often receive combinations of treatments, and the effectiveness and safety of these combinations can be different than individual treatments. RWE provides information about these combinations, something that is difficult to study in clinical trials.

[5] Post-Marketing Surveillance: Once a drug is approved and in use, RWE provides a mechanism to monitor its safety in the larger population. Post-marketing surveillance can help to identify rare adverse events that were not detected in clinical trials due to smaller sample size.

However, it’s important to note that RWE and clinical trials each have their strengths and weaknesses. Clinical trials remain the gold standard for demonstrating efficacy and obtaining regulatory approval because they can establish causality via randomization. RWE, while providing valuable insights on effectiveness and safety, often comes from observational studies, where it can be harder to determine cause-and-effect relationships because of potential confounding factors. Therefore, both are needed and (traditionally) used at different stages of the drug development and monitoring process.