Clinical trial simulation is the use of statistical or computational models to estimate how a treatment, protocol, or patient group may behave before a real-world trial is run. In medicine, it helps researchers test scenarios, compare therapies, and estimate outcomes without exposing people to unnecessary risk.
From a cyber-security perspective, these simulations depend on sensitive clinical data and trusted model inputs. If an attacker alters records, poisons training data, or changes simulation parameters, the results can look scientifically valid while being wrong. That makes access control, integrity checks, audit logs, and model validation essential defenses. In real environments, simulation tools are also used defensively to stress-test trial designs, identify weak assumptions, and spot data-quality problems before they affect decisions.