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Driving Data-driven Medicine to Advance Personalized Care
Clinical trials are often designed with the participant’s everyday life in mind – trying to gather as much clinically-relevant data in a controlled manner as possible while allowing individuals to live their regular lives. However, it is true that trials are artificial environments, and participants are actively monitored to ensure their safety and to determine the efficacy of a drug in development.
Bridging Clinical Research to Real-World Patient Care Through Predictive Analytics
The ability to predict how a clinical trial participant will adhere to their treatment, and even respond to that treatment, has great promise to advance patient-centric clinical research. But, as we look to understand the impact a drug has on patients’ everyday health outside of a research environment, what happens to these unique, predictive findings around dosing and outcomes once a drug enters the real-world?
From Predicting Adherence to Health Outcomes – The Power of Predictive Insights
Clinical researchers have begun adopting predictive analytics to anticipate a patient’s engagement in a clinical trial, including if and how a patient will adhere to their treatment plan. As these models are fed more patient-level audio and visual data, they have the potential to open up a whole new world of a patient’s lived experience – from how a patient will respond to their medication, to the likelihood of developing side effects, to the broader trajectory of their disease.