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Driving Medical Affairs Strategy in Rare Disease with AI-Powered Insights

A Pioneer in Neurological and Rare Disease Innovation

The company is a global biotechnology pioneer dedicated to discovering and developing innovative therapies for people living with serious neurological and neurodegenerative diseases. Their Rare Disease Medical Affairs team focuses on advancing treatments for devastating conditions that currently have high unmet medical needs.

 

Challenges: Manual Insights Process and Medical Impact Blindspots

 
Prior to their AI transformation, the Medical Affairs organization struggled with a manual process for collecting and analyzing insights that was described by internal staff as "very painful" and inherently inefficient. Insights were predominantly siloed within field interactions recorded by Medical Science Liaisons (MSLs), failing to incorporate critical perspectives from medical information, congresses, advisory boards, or external literature such as publications.
 
This fragmentation led to significant delays in identifying and disseminating crucial trends, as senior staff were forced to spend an estimated 10-20% of their time on the manual review and categorization of data. Ultimately, this tactical burden prevented the team from accurately assessing the real-world impact of medical affairs activities on the behaviors and clinical outcomes of the medical community.
 
 

The Mandate: A Unified Platform for Medical Intelligence

The Medical Affairs team required an insights and impact measurement platform powered by generative AI to revolutionize analysis and provide timely, actionable measures of impact. This system needed the capability to ingest proprietary structured and unstructured data from multiple internal sources, including CRM databases, medical information systems, and standard Office files such as PowerPoint, Word, and Excel.

A central objective was the ability to trend the impact of medical affairs over time, specifically measuring changes in the sentiment, behaviors, and outcomes of the medical community resulting from various tactics. To satisfy rigorous compliance standards and support effective change management, the platform had to extract data from external literature sources while documenting original data sources for all generated content to ensure complete source verification.

 

The Journey: Validating Domain Expertise through Side-by-Side Comparison

The organization conducted a rigorous evaluation of several specialized technology vendors, narrowing the field to finalists that offered both advanced technology and industry-specific context. While multiple providers offered basic AI tools, the company sought deep Medical Affairs domain expertise to ensure the technology could be applied meaningfully without requiring extensive explanation of clinical applications.

The selection was solidified during a live side-by-side comparison for senior leadership—many of whom were initially technology skeptics. By demonstrating a live AI-generated summary against a manual summary from a previous busy month, the champion converted leadership by showcasing dramatic time savings and high-fidelity results.

 

Why Sorcero: Medically-Tuned AI with Source-Verified Trust

  • Medically-Tuned AI: Sorcero’s Agentic AI framework was purpose-built for life sciences, accurately understanding complex scientific semantics and abbreviated field notes often misinterpreted by that general-purpose AI.

  • Deep Domain Expertise: The company selected Sorcero because the team’s extensive Medical Affairs experience meant they understood strategic expansions and application needs without requiring explanation.

  • Ready-to-Deploy Customizable Platform: The organization viewed Sorcero as a "functioning package" that was mature enough for enterprise use yet offered the flexibility to be configured for specific rare disease data models.

  • Workflow-Centric Innovations: The platform delivered "home run" features such as the Insights Kanban, which provided a structured, visible workspace for team members to collaboratively validate and escalate insights.

  • Source-Verified Trust: A critical differentiator was the platform's ability to show exactly where it retrieved its answers, satisfying compliance requirements and building the trust necessary for successful user adoption.

 

Quantifiable Outcomes: Accelerating Strategic Decision Making

Implementation delivered immediate, measurable value across the Medical Affairs function:

  • 70% Efficiency Gain: Reduction in time spent on weekly insight analysis, allowing staff to shift from operational to strategic work.

  • 90% Faster Ad Hoc Investigations: Questions that previously took 5 hours over multiple days to answer (e.g. "What are HCPs saying about a competitor drug?") now take 30 minutes, including fact-checking.

  • Unified Medical Intelligence: Successfully combined dozens of data sources, including CRM interactions, surveys, and external publications, into a single platform to get insights across them.

  • Strategic Advisory Board Selection: Evaluated 40 potential advisory board members to rank and narrow the list to the 12 most relevant candidates based on specific insights, instead of randomly choosing.

  • Rapid Enterprise Rollout: Moved from contract completion to a functioning, data-populated platform in approximately 12 weeks.

 

Before and After: From Operational Grunt Work to Proactive Medical Affairs Strategy

Feature
Before AI Transformation
After AI Transformation
Analysis Focus
Operational: Senior staff spent 10–20% of their time manually pulling and categorizing data from Excel.
Strategic: Senior staff focus on high-level analytics to drive strategic clinical and business impact.
Data Scope
Fragmented: Insights restricted to field interactions, with medical info and external sources siloed.
Unified: Single source of truth combining dozens of internal and external data sources.
Response Speed
Slow: Ad hoc leadership requests required multiple days and intensive manual verification.
Instant: Thorough investigations completed in 30 minutes with full citations and source verification.
Decision Making
Reactive: Decisions often based on anecdotal evidence or random expert selection.
Proactive: Strategic selection of experts and tactics based on longitudinal trend visualization.

70% Less Time

spent on weekly insight analysis

10x
Faster

ad hoc evidence investigations; 5 hours spent over multiple days now take 30 minutes

Ready to Deploy

Enterprise-ready, and flexible to configure

quote

Sorcero has not only the technology available from day one but knows how to apply it to our needs without us having to explain how we work.

Medical Director
Rare Disease