Five Key Considerations for Integrating AI Into the Case Intake Process

Learn ways to optimize your PV strategy by leveraging new processes and technologies.

The most recent FSP trends report reveals artificial intelligence (AI) is one of several new technologies that are key in addressing some of today’s drug development challenges. With respect to pharmacovigilance (PV), the integration of AI into the case intake process offers significant potential benefits, including increased efficiency, consistency and cost savings. However, implementing AI-driven solutions requires careful consideration of several factors to ensure a successful and sustainable deployment. In this blog, PPD™ Functional Service Partnership (FSP) Pharmacovigilance solutions experts share five key considerations to keep in mind when integrating AI functionality into your case intake process, with insights on how these considerations may vary based on the size of the company.

1. Balancing automation with human input

AI significantly reduces the manual workload involved in data collection and entry, improving checks for completeness and validity. This allows human experts to focus on more critical tasks such as medical assessment and quality checking, thereby improving efficiency and reducing the time and costs associated with PV case processing.

Smaller/mid-sized companies may benefit from AI automation to handle routine tasks, freeing up limited human resources for more complex case assessments and reviews. However, they should ensure that the AI system is user-friendly and requires minimal oversight to avoid overburdening their staff.

Larger organizations may leverage AI to handle high volumes of data, but they must ensure robust oversight mechanisms are in place. Investment into more sophisticated AI systems and dedicated teams to monitor and refine AI outputs will ensure data integrity and compliance.

2. Handling variability in reporting formats

AI handles the enormous volume and variety of data sources, including unstructured text from electronic health records, literature and registries. This capability helps in sensibly using data and separating “the needles from the haystack” to address one of the key challenges in PV: the need for efficient and effective data handling.

Smaller firms may face challenges in managing diverse reporting formats due to limited resources. They should prioritize AI solutions that offer high flexibility and adaptability, reducing the need for extensive manual intervention.

Larger companies typically deal with a broader range of reporting formats and higher data volumes. They should invest in advanced AI systems capable of handling complex data extraction tasks across various formats, ensuring consistency and accuracy.

3. Assessing technology costs vs. return on investment

The cost of implementing AI should be weighed against the potential savings from reduced manual labor and faster processing times. AI helps manage the exponential growth in adverse event (AE) reports, making the investment worthwhile by improving overall efficiency and reducing long-term operational costs.

For smaller companies, the initial setup and ongoing maintenance costs of AI are significant. They should carefully evaluate the return on investment (ROI), considering both immediate efficiencies and long-term benefits. Cost-effective AI solutions that offer scalable options may be more suitable.

Larger organizations may justify higher initial investments in AI technology due to the potential for substantial efficiency gains and cost savings. They should model ROI over a longer period, factoring in the benefits of improved processing consistency and reduced case cycle times.

4. Selecting data extraction methods

AI-driven data extraction methods streamline individual case safety report processing by accurately extracting essential elements such as patient details, adverse reactions and medication information. This reduces the need for manual data entry and ensures completeness and validity for regulatory submissions.

Smaller firms should opt for AI solutions that offer reliable data extraction with minimal configuration and maintenance requirements. Solutions that handle both structured and unstructured data efficiently will be beneficial.

Larger organizations should invest in sophisticated AI systems capable of extracting data from diverse sources with high accuracy. Implementation of more complex extraction methods and continuous refinement will ensure optimal performance.

5. Balancing technology integration with team engagement

Successful AI integration requires a collaborative approach between technical expertise and intelligent technology. By enhancing human intelligence rather than substituting it, AI ensures that the PV system meets its objectives and benefits all stakeholders.

Smaller companies should focus on AI solutions that are easy to integrate and require minimal training. Engaging the team early in the process and fostering a culture of innovation is crucial for successful implementation.

Larger organizations should invest in comprehensive training programs and change management strategies to ensure team engagement. Designing specialized teams around new technologies and promoting continuous improvement maximizes the benefits of AI integration.

Harnessing the power of AI-driven solutions for PV

As AI evolves, its role in case intake will expand. AI technologies and tools will offer pharmaceutical companies a pathway to more agile and reliable PV practices while driving significant operational efficiencies. Integrating AI into the case intake process offers numerous benefits but requires careful planning and consideration of various factors. By balancing automation with human input, handling variability in reporting formats, assessing technology costs vs. ROI, selecting appropriate data extraction methods, and ensuring team engagement, organizations will successfully enhance efficiency and compliance in their PV systems through AI-driven solutions. Beyond case intake, integrating AI and clinical development further transforms drug development processes, enabling smarter workflows and better outcomes.

Advanced systems enhance patient safety monitoring

Today’s PV systems face complex and evolving global regulations driven by growing adverse event volumes and new streams of data.¹ PPD™ FSP Pharmacovigilance solutions leverage new technologies, analytics, process improvements, and automations to gain efficiencies, improve quality, increase consistency, accuracy, and reliability, and reduce the PV cost burden. We are committed to continuously advancing our systems, processes and technologies. With our expertise in industry best practices, requirements and the latest innovations, we create tailored solutions to optimize your PV tech strategy.

¹ Transforming pharmacovigilance systems: Automation, Tech, Analytics | Deloitte US