While the popularity of tools like ChatGPT have brought AI to the forefront of tech investments, nearly 73% of life science companies still struggle to adopt an appropriate AI technology.
Some of the biggest challenges to successful adoption are clearly defined use cases, appropriately trained AI that understands scientific concepts and approachable applications for leveraging AI with minimal technical expertise.
When deployed strategically, AI tools can revolutionize how organizations utilize data to discover insights that enhance the drug development life cycle. For example, AI is providing life science researchers with:
- Efficient ways for analyzing and predicting the performance of small molecules to help discovery scientists better prioritize the most viable chemical structures.
- Expanded access to data to more effectively determine drug toxicity and inform modeling.
- Automation of early drafting of reports and regulatory documents, allowing for faster time to submission.
On Dec 7th, Certara experts Heather Graham, Vice President Certara Drug Development Solutions and Sean McGee, AI Product Director gave a roundtable discussion on real-world applications for AI across the drug development cycle. During this discussion, you’ll learn:
- How Certara is using AI to drive early discovery, drug modeling, and regulatory writing
- Different tasks for AI and how to define them within your organization
- Key considerations for successful deployment of AI in drug discovery
- Strategic ways to begin deploying AI in your organization
