1、Integrating AI into clinical research:How AI is being used to enhance clinical developmentICON AI into clinical developmentExecutive summary 03Best practices in applying AI 05The AI regulatory landscape 08AI applications across the drug development lifecycle 09Early measures of effectiveness 11A wor
2、d about Generative AI 16Conclusion 17Authors 18 Further reading 19References 20 ContentsIntegrating AI into clinical development3As a disruptive technology,Artificial Intelligence(AI)is currently the subject of a great deal of excitement and hype so much so that it can be difficult to objectively as
3、sess its capabilities and promise.It is clear,though,that AI has the potential to transform business processes across the spectrum of clinical development from clinical trial design,through to recruitment and clinical operations,all the way to commercialisation and outcomes.AI can deliver reasonably
4、 unbiased and accurate insight into a situation,allowing human experts to make a clear decision.Human expertise should still be the final arbiter,but AI can have a very positive impact on the final outcome.While AI has engendered some degree of necessary caution in the pharmaceutical industry,adopti
5、on is steadily increasing.A 2024 global survey conducted by Tufts Center for the Study of Drug Development(Tufts CSDD)in conjunction with the Drug Information Association(DIA)found that 63%of respondents had at least begun to implement AI/Machine Learning(ML)to support drug development.Adoption rate
6、s were closely tied to trial volume.1 In our survey on digital disruption conducted with Citeline in late 2024,2 we learned that although companies are using AI heavily in single development programs,organisations are still struggling to incorporate the technology on a wider scale.While 70%of respon
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