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Given the lengthy, labor-intensive, and expensive process of bringing a new drug to market and conducting a clinical trial, clinical development stakeholders are constantly searching for technological solutions to automate workflows, streamlineoperations, reduce site and patient burden, and accelerate trial timelines.
This approach speeds up development, cuts costs, and opens up new ways to enhance patient care and streamlineoperations. AI then boosts these apps by automating tasks, making predictions, and offering smart guidance. Low-code platforms streamline the process of creating and approving clinical trial protocols.
McDonald’s is building AI solutions for customer care with IBM Watson AI technology and NLP to accelerate the development of its automated order taking (AOT) technology. For example, Amazon reminds customers to reorder their most often-purchased products, and shows them related products or suggestions.
This new initiative delivers customized, human-in-the-loop (HITL), tech-enabled solutions for hospitals, clinics, medical device companies, pharmaceutical companies, wellness brands, and healthcare service providers. Pharmaceuticals Supporting medication access, adherence programs, and compliance.
This becomes especially crucial when integrating AI and automation into the optimization ambitions. While these technologies have the potential to streamlineoperations, their effectiveness hinges on thorough design and execution to prevent complications and inefficiencies along the way of implementing.
Historical attempts at process improvement, from re-engineering to robotic process automation (RPA) have often fallen short of expectations. Currently, the focus in process optimization revolves around leveraging process mining and RPA tools with some Gen AI embedded, enhancing existing systems with automation and predictive analytics.
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