Maximizing the Value of Data in Process Development

Article
Drug substance
Industry trends
Process development

In a recent article in Chemistry Today, Snapdragon Chemistry’s David Ford discusses how AI and data science may fundamentally change how we approach process development and early deliveries of active pharmaceutical ingredients (APIs). He explains how leveraging data science may be crucial for making efficient experimental choices under time and resource constraints. Large language models (LLMs) and AI offer the pharmaceutical industry huge potential by:

  • Improving the searchability of historical data, which is often buried in extensive technical reports and presentations.
  • Ranking search results, streamlining the process of finding relevant information.
  • Reducing the chances of redundant work.
  • Enabling teams to deliver medicines faster.

However, David acknowledges that concerns regarding data privacy and the tension between model owners and users are warranted. The best AI models are owned by companies with vast resources, which introduces questions about the security and confidentiality of sensitive business/scientific documents used in AI-driven analysis. Despite these challenges, AI has significant potential benefits. Utilizing a structured approach, starting with standardized data capture and traditional statistical analysis, lays the groundwork for integrating more advanced AI tools in the future.

To learn more about the use of AI and data science in process development of APIs, read the entire article, “Maximizing the Value of Data in Process Development” in Chemistry Today.

View the full article (via Chemistry Today)