Why AI matters at this scale

Viatris Connect operates as a critical digital and patient support arm of Viatris, a global pharmaceutical giant with over 10,000 employees. Its mission centers on connecting patients, healthcare providers, and pharmacies to support access to a broad portfolio of medicines. At this enterprise scale, operational complexity is immense, spanning global supply chains, high-volume manufacturing, stringent regulatory compliance, and direct patient engagement. Manual processes and siloed data systems struggle to keep pace, creating inefficiencies that impact cost, speed, and patient care. Artificial Intelligence presents a transformative lever, capable of processing vast datasets to uncover insights, automate complex tasks, and predict outcomes. For a company of this size and in the pharmaceutical sector, AI adoption is not merely an innovation but a strategic imperative to maintain competitiveness, ensure supply chain resilience, improve patient outcomes, and navigate an increasingly data-driven healthcare landscape.

Concrete AI Opportunities with ROI Framing

1. Supply Chain & Inventory Optimization: The global pharmaceutical supply chain is notoriously fragile. AI-powered demand forecasting and inventory management can analyze historical sales data, regional disease trends, and logistical variables to predict drug needs with high accuracy. This reduces costly stockouts and excess inventory, potentially saving tens of millions annually. Furthermore, AI can simulate disruptive events (like raw material shortages) to recommend proactive mitigation strategies, protecting revenue and ensuring patient access.

2. Enhanced Pharmacovigilance & Compliance: Monitoring drug safety (pharmacovigilance) involves manually reviewing millions of adverse event reports, a slow and expensive process. Natural Language Processing (NLP) AI can automatically scan and categorize reports from healthcare providers, patients, and literature, accelerating the detection of potential safety signals. This reduces manual labor costs, speeds up reporting to agencies like the FDA, and potentially identifies risks earlier, protecting patient safety and avoiding costly late-stage drug issues.

3. Personalized Patient Support & Adherence: For patients on chronic therapies, medication non-adherence leads to worse health outcomes and higher system costs. AI can analyze anonymized patient data (with consent) to segment populations and predict which patients are at risk of lapsing. It can then trigger personalized, automated support—such as tailored reminder messages, educational content, or alerts to healthcare providers. Improving adherence rates directly boosts patient health and can increase the effective demand for therapies, creating a clear ROI through better health outcomes and sustained product utilization.

Deployment Risks Specific to Large Enterprises

Implementing AI in a large, regulated pharmaceutical enterprise like Viatris Connect carries distinct challenges. Integration Complexity is paramount; legacy ERP (e.g., SAP) and CRM (e.g., Salesforce) systems are deeply embedded, and AI solutions must interoperate without disrupting critical operations, requiring significant upfront investment and change management. Data Governance and Privacy risks are severe, as AI models require access to sensitive patient and commercial data, demanding robust compliance with HIPAA, GDPR, and other global regulations to avoid legal penalties and reputational damage. Finally, Regulatory Scrutiny is intense, especially for AI used in manufacturing or clinical support. Models may require validation akin to medical devices, necessitating extensive documentation, auditing trails, and potential pre-market reviews by bodies like the FDA, slowing deployment and increasing cost.