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3 Ways to Use AI in Life Sciences to Get Drugs to Market Faster

Victoria Ebel, Appian
May 21, 2024

Artificial Intelligence (AI) is beginning to transform the life sciences industry, offering opportunities to streamline processes and expedite the delivery of life-saving products to market. However, understanding how best to leverage AI for success can prove challenging. With an overwhelming amount of potential use cases for AI in life sciences, it can be difficult to choose the right course of action that delivers the most impact.

[Discover where the experts are seeing successful AI implementation in life sciences. View the guide.]

Here are 3 key areas where AI can improve workflows to bring treatments to market faster than ever before.

Top examples of using AI in life sciences

1. Using AI and process automation to optimize clinical operations

AI optimizes several aspects of the clinical process. Automation helps with the mass data collection required throughout a clinical trial by streamlining data capture processes. And automating data validation checks ensures the accuracy of data being collected and leveraged, minimizing errors and reducing the need for manual data entry. 

AI can also optimize the clinical trial timeline itself, speeding up the process. Automating workflows facilitates document exchange, protocol amendments, and site monitoring activities, improving communication and coordination across multiple stakeholders.

2. Optimizing manufacturing processes with AI features

By optimizing manufacturing processes, AI can reduce production costs, improve product quality, and increase manufacturing throughput, ultimately accelerating the production and delivery of drugs to market. This includes automating approval processes, task assignments, escalations, and notifications. 

Supply chain automation also helps to standardize processes across different production lines and manufacturing sites. Standardization improves the efficiency and consistency of processes, reducing the risk of errors and improving the overall quality of the products.

3. Streamlining regulatory compliance efforts

By streamlining regulatory compliance processes, AI can reduce the time and resources required to bring drugs to market while minimizing the risk of regulatory delays.

Automation can streamline the creation, review, approval, and storage of regulatory documents, including submission dossiers, study protocols, and standard operating procedures. Automated systems can help enforce version control, track document changes, and provide audit trails, ensuring compliance and reducing the risk of documentation errors.

Harnessing the power of AI in life sciences

AI can significantly accelerate processes in the pharmaceutical industry, from clinical to manufacturing and regulatory compliance. By harnessing the power of AI, pharmaceutical organizations can deliver these key benefits:

  • Optimized processes. Automate areas in processes that normally would be manual. This includes pre-populating fields in documentation or automatically sending and collecting executed documents, ultimately accelerating execution.

  • Simplified regulatory submissions. Automation helps to enforce important review and approval workflows and generate logs demonstrating actions taken throughout the submission process, helping to expedite audits. 

  • End-to-end visibility. Effective automation capabilities enhance process monitoring by automatically generating analytics, reports, and dashboards. This transparency encourages process improvements that help get products to market.

Discover more insights on the future of AI in pharma. View the guide.