From promise to impact with gen AI in healthcare & life sciences
summary
ZS describes deploying Amazon Bedrock and SageMaker alongside vector databases and LLM Ops to fine‑tune models, run a Max.AI demo pipeline, and serve multimodal corpora. A tool called Alter Igo summarizes clinical protocols and links SDTM data; synthetic data and GANs cut patient drop‑off prediction error and speed trial screening by 99% reduction (260 to 2 days) while another project yields 10–20% efficiency gains and 50% faster tech transfer in supply chain.
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chapters (5)
- 0:00The promise of generative AI
- 2:34Value beyond productivity
- 6:36Life sciences use cases
- 11:28Technical architecture
- 15:27Strategy for long-term success
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