Miruna Sasu
About Miruna Sasu
Miruna Sasu CEO
Miruna Sasu holds the position of Chief Executive Officer. She advocates for leveraging Artificial Intelligence (AI) to make data more approachable. According to her, AI allows users to query data directly, regardless of their computer science background. Sasu sees AI as a transformative tool in the realm of data accessibility.
Miruna Sasu on AI and Data Approachability
Miruna Sasu firmly believes that AI technology can democratize data usage. She emphasizes that AI enables users, irrespective of their computer science training, to query and understand data. Her views are rooted in the notion that AI simplifies data interaction, making it more accessible and practical for a broader audience.
Miruna Sasu and Life Sciences Data Integration
Miruna Sasu highlights the integration of outcomes data into commercial analyses as a major advancement in the life sciences sector. By integrating comprehensive datasets, she believes the industry can gain deeper insights and make more informed decisions. This approach is seen as a progressive step towards enhanced analytical capabilities within life sciences.
Miruna Sasu's Experience in Big Pharma
Miruna Sasu brings extensive experience from working in large pharmaceutical organizations. Her role involved acquiring datasets for various teams, underscoring her proficiency in data management and utilization in big pharma settings. This experience has equipped her with a nuanced understanding of the data needs and challenges in the pharmaceutical industry.
Miruna Sasu on Use of Real-World Data
Miruna Sasu advocates for the use of real-world data to significantly reduce research timelines. She points out that with real-world data, research that traditionally takes months can be completed in days. This accelerative capability is essential for faster innovation and development in research fields.
Miruna Sasu on Linked Datasets
Miruna Sasu emphasizes the critical importance of linked datasets in providing comprehensive and quick insights. By linking diverse datasets, she believes that more complete and efficient analysis can be achieved, enhancing decision-making processes across various sectors.