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Real-Life Science

From Idea to Impact: AI Use Cases That Delivered Real-Life Science Business Results

Thought Leadership7 October 2025531Views0Likes0Comments
Introduction Artificial Intelligence is redefining healthcare and life sciences. From improving patient care to accelerating drug discovery, AI is proving to be more than just a technological trend; it’s a critical enabler of innovation and efficiency. In this article, we explore real-world AI applications in clinical studies, pharmacovigilance, diagnostics, and medical operations. These use cases…

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AI in Evidence Generation

How HTA Agencies Are Evaluating AI in Evidence Generation

Thought Leadership8 September 2025262Views0Likes0Comments
As AI rapidly reshapes the evidence landscape, health technology assessment (HTA) bodies are beginning to define clear expectations for its use in submissions. At CapeStart, we work closely with life sciences clients navigating these changes—especially those integrating GenAI into literature reviews, RWE generation, economic modeling, Joint Clinical Assessment (JCA) support, Clinical Evaluation Reports (CERs), Patient…

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ROI of GenAI

How MadeAi™ Uses GenAI-Aided Review & AI as Reviewer to Beat Manual SLR Solutions

Thought Leadership6 August 2025236Views0Likes0Comments
In today’s fast-paced life sciences environment, literature reviews are critical—but they’re also time-consuming, labor-intensive, and increasingly expected to support regulatory, HEOR, and market access submissions while maintaining full transparency and traceability.  While traditional platforms offer useful automation features, most are either rules-based classifiers or structured workflow tools, limiting their adaptability and explainability. That’s where MadeAi™…

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Literature Review

How to Evaluate GenAI-enabled Literature Review Platforms: A Buyer’s Guide to Transparency, Accuracy, and Compliance

Thought Leadership23 July 2025373Views0Likes0Comments
The rise of generative AI (GenAI) is transforming how life sciences organizations approach evidence synthesis, regulatory submissions, and market access activities. As literature review workflows become more complex—and timelines more compressed—life science professionals are increasingly turning to GenAI-enabled platforms to streamline systematic literature reviews (SLRs), reduce manual burden, and scale evidence synthesis. However, evaluating…

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AI Implementation

The Biggest Challenges to Implementing AI in Life Sciences

Thought Leadership14 March 202598Views0Likes0Comments
The promise of Artificial Intelligence (AI) in life sciences is undeniable—offering advancements in drug discovery, clinical research, and evidence generation. Yet, many organizations still struggle to implement AI effectively. To better understand these challenges, CapeStart conducted a survey of 104 life science professionals, asking them:  What are the top three barriers to success for your…

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