Which of the following is a real-world data source used to evaluate drug safety and effectiveness?

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Real-world data comes from information gathered outside controlled trial settings, reflecting how a drug performs in everyday clinical practice and in diverse patient populations. Wearable devices provide a prime source of this kind of data because they continuously monitor health metrics and activity in people as they go about daily life. This enables observing safety signals (such as unexpected changes in heart rate or episodes of arrhythmia) and effectiveness indicators (like improvements in activity levels or sleep quality) over extended periods and across real-world adherence patterns.

In vitro assays, by contrast, are conducted in lab dishes on cells or tissues and reveal mechanistic effects, not how a drug behaves in a living person. Animal testing offers preclinical safety and pharmacokinetic information but remains outside human real-world data. Preclinical computer modeling uses simulations to predict outcomes and does not produce observed data from real patients.