1、AI in Life ScienceFROM TRADITIONAL TO GENERATIVEAugust 20232IntroductionRecent developments in generative AI ignited a lot of interest towards artificial intelligence,traditional and generative.The new capabilities of responding to language prompts and creating different kinds of content not only ad

2、d new use cases but make the technology accessible to more users than ever,drastically lowering use barriers for non-tech professionals.At the same time,application of AI in Life Science has never been straightforward due to privacy and regulation concerns,data availability and challenges in stakeho

3、lder buy-in.The risks connected to patients well-being,healthcare professional trust and confidence,and impact on core product pipeline are always the top concerns in the industry.That is why in this overview we focus specifically on the application of AI,generative and traditional,in Life Science,i

4、ts potential impact,prospectives and challenges.This report covers 96 high-level AI use cases applicable in Life Science,grouped by topic and place in the value chain.There is often more than one single way to implement a use case,that is why we refrained from dividing them into generative and tradi

5、tional.We also looked at the potential impact and feasibility of the topics,barriers and trends that are present for AI in the industry.While for every organization implementation the impact of AI may look different,we hope that this overview will provide some inspiration and bring more clarity to h

6、ow AI can transform Life Science.AUTHORS SerikovaSenior Digital Strategy ConsultantTeun SchutteStrategy director and Healthcare&Life Sciences Practice leadMark de BlaauwSenior Data ScientistMarius BurgerDirector of EngineeringJorge Martnez BonillaApplication Security Engineer23Impact of the recent A