Artificial Intelligence (AI) and Machine Learning tools are being leveraged across the clinical development landscape, delivering time and cost savings while reducing risk. The heuristics of AI may not be appropriate to solve problems in regulated environments – therefore we must be careful with one-size-fits-all approach for healthcare AI technology.
The current thinking is to break down barriers between departments, software, organizations and users in order to have a greater share of knowledge which can improve communication, data insight, creativity and loyalty. While this sentiment is still true the real-world application faces many issues such as technical incompatibility, regulatory requirements, privacy, data modelling and retrospective corrections.
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