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Generative AI in Clinical Development: Unlocking Possibilities and Addressing Challenges | Blog

Everest Group

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, streamline operations, reduce site and patient burden, and accelerate trial timelines.

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Streamlining Clinical Trials with AI & Low-Code

Amzur

This approach speeds up development, cuts costs, and opens up new ways to enhance patient care and streamline operations. 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.

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The most valuable AI use cases for business

IBM Services

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.

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Premier NX Unveils Empathy-Driven Healthcare and Wellness Practice

Premier BPO

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.

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How to succeed with ambitious process optimization efforts

Capgemini

This becomes especially crucial when integrating AI and automation into the optimization ambitions. While these technologies have the potential to streamline operations, their effectiveness hinges on thorough design and execution to prevent complications and inefficiencies along the way of implementing.

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Will Gen AI fulfill the promise of process optimization?

Capgemini

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.