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™…
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…
As the demands for faster, more accurate, and scalable literature reviews rise in life sciences, AI is no longer just a future promise—it’s a proven performance driver. Systematic literature review (SLR) teams, especially in HEOR and medical affairs, are adopting GenAI platforms not just for experimentation but to solve long-standing bottlenecks in screening, extraction, and…
At the ISPOR 2024 Conference in Atlanta, attending health economics and outcomes research (HEOR) professionals lamented the drudgery of systematic literature reviews (SLRs) as they envisioned the potential for generative artificial intelligence (GenAI) to fix it. With a single SLR estimated to take anywhere from six to 16 months to complete and cost an average…
