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以患者为中心的药物研发的人工智能驱动方法。

Artificial intelligence-driven approach for patient-focused drug development.

作者信息

Karmalkar Prathamesh, Gurulingappa Harsha, Spies Erica, Flynn Jennifer A

机构信息

Merck Data & AI Organization, Merck IT Centre, Merck Group, Bangalore, India.

EMD Serono Research & Development Institute, Inc., Billerica, MA, United States.

出版信息

Front Artif Intell. 2023 Oct 12;6:1237124. doi: 10.3389/frai.2023.1237124. eCollection 2023.

Abstract

Patients' increasing digital participation provides an opportunity to pursue patient-centric research and drug development by understanding their needs. Social media has proven to be one of the most useful data sources when it comes to understanding a company's potential audience to drive more targeted impact. Navigating through an ocean of information is a tedious task where techniques such as artificial intelligence and text analytics have proven effective in identifying relevant posts for healthcare business questions. Here, we present an enterprise-ready, scalable solution demonstrating the feasibility and utility of social media-based patient experience data for use in research and development through capturing and assessing patient experiences and expectations on disease, treatment options, and unmet needs while creating a playbook for roll-out to other indications and therapeutic areas.

摘要

患者日益增加的数字参与度为通过了解他们的需求来开展以患者为中心的研究和药物开发提供了机会。在了解公司的潜在受众以推动更具针对性的影响方面,社交媒体已被证明是最有用的数据来源之一。在海量信息中进行筛选是一项繁琐的任务,而人工智能和文本分析等技术已被证明在识别与医疗保健业务问题相关的帖子方面很有效。在此,我们展示了一个企业级的、可扩展的解决方案,通过捕捉和评估患者对疾病、治疗选择和未满足需求的体验与期望,证明了基于社交媒体的患者体验数据在研发中的可行性和实用性,同时还创建了一个用于推广到其他适应症和治疗领域的操作手册。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/88b2/10601646/cff5729b677c/frai-06-1237124-g0001.jpg

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