Heterogeneous Data Formats Prohibit Advanced Analytics and AI
The pharmaceutical industry is experiencing a surge in scientific data due to the growing complexity of new therapeutic modalities and the urgency to bring improved therapeutics to market more efficiently. However, this valuable scientific data is often trapped in on-premise instrument control and acquisition software, compounded by the challenge of dealing with diverse vendor-specific data formats, thus inhibiting the potential of AI.
Is Engineered Scientific Data the Force Multiplier for AI?
In this webinar, we will explore a use case involving a leading pharmaceutical company that aims to provide its scientists and engineers with analytics and AI-ready data across multiple laboratories, departments, and facilities.
By making this data available, scientists can leverage prior work to inform their actions and improve scientific outcomes. Moreover, they can identify and accelerate the most promising scientific strategies , leading to substantial time and cost savings.
This webinar will address several crucial aspects of maximizing the value of scientific data in the biopharmaceutical industry, including:
- Centralizing and harmonizing scientific data
- Improving collaboration and data sharing
- Leveraging Semantic AI in biopharma
- Managing diverse taxonomies efficiently
- Automating data preparation and engineering
Don’t miss this opportunity to discover how your organization can maximize the value of your data and accelerate scientific advancements through AI.