5 min 
Introduction
Medicine is becoming more personalized and identifying patients, especially those with rare diseases, poses significant and costly challenges. These individuals often represent small, dispersed populations with narrow windows of treatment and frequently endure prolonged misdiagnoses due to the complexities of their conditions. While advancements in technology have led to new treatment options for several rare diseases, the process of identifying, diagnosing, and initiating treatment for these patients is still slow and challenging.
Artificial Intelligence (AI) offers a pivotal approach for companies to enhance their ability to swiftly and accurately identify patients with rare diseases and engage healthcare providers (HCPs) at the right time. By integrating AI into patient discovery processes, commercial teams can overcome the challenges of fragmented data, limited patient insights, and slow response times.
AI can be a game-changer to optimize patient treatment and recovery while preventing discontinuation, reducing missed opportunities, and lowering operational costs.
Finding the Right Patients in Rare Disease Treatment
Precision medicine has revolutionized healthcare, delivering remarkable benefits through Immunotherapies and targeted therapies for breast cancer, lymphomas, leukemias, and myelomas and even rare cancers such as rare blood disorders, bile duct cancer, salivary gland cancer, esophageal cancer, etc. These innovations have transformed patient care by focusing on smaller, highly specific patient populations, particularly in rare diseases.
However, the very nature of these diseases makes patient discovery exceedingly challenging. The rarity of these conditions often leads to patients being underdiagnosed or misdiagnosed. Complicating matters further, diagnosing these rare diseases typically involves intricate procedures and the collaboration of multiple specialists, each understanding the nuances of narrow treatment windows and varied treatment pathways.
It is critical to engage healthcare providers (HCPs) and inform them about specific treatments at the precise moment necessary for effective intervention. However, the complexity of these cases makes it challenging to obtain real-time data and transform it into actionable insights through traditional methods, underscoring the need for advanced approaches to patient discovery.
The Power of AI in Patient Discovery for Rare Diseases and Precision Medicine
Artificial Intelligence (AI) is revolutionizing patient discovery in rare diseases and precision medicine, offering groundbreaking data analysis capabilities and algorithmic insights that can transform care. Here’s how AI is making a significant impact:
Patient Pathway Insights
AI-driven analysis integrates multiple data assets to generate insights into patient clusters and journeys. By analyzing hundreds of possible clinical pathways, AI can predict trends and forecast demand with unprecedented accuracy.
Predictive Targeting
AI enables predictive targeting of the right HCPs by answering questions about who to target and why. Advanced models analyze patient and HCP data to predict likely patient starts or discontinuations, allowing for more efficient and effective outreach.
Hyper-Personalized HCP Engagement
AI facilitates personalized engagement with HCPs by providing contextual insights for each opportunity. This allows representatives to deliver tailored messages to each HCP, focusing on value-add interactions with those treating rare disease patients.
Next Best Action Recommendations
AI delivers timely alerts with recommendations on who to engage and what to say. Field teams receive triggers that help them focus on the right HCPs with the right message at the right time. Clinical pathway triggers assist in identifying new patient starts or indicators that might lead to patient discontinuations.
By leveraging these AI-powered capabilities, healthcare professionals can significantly improve patient discovery and care in the realm of rare diseases and precision medicine.
AI-Driven Patient Discovery: Commercial Benefits & Improved Patient Outcomes
As pharmaceutical margins continue to be squeezed and the pressure to compete and achieve more with less intensifies, AI presents commercial teams with innovative ways to lower costs, improve patient identification and enhance competitive performance —ultimately leading to better patient outcomes.
Cost Efficiency and ROI
AI can dramatically reduce the high costs of patient discovery in rare diseases by improving precision and speed. Instead of broad, inefficient outreach, AI pinpoints eligible patients and the HCPs most likely to diagnose and treat them. This targeted approach minimizes wasted marketing spend on broad, ineffective campaigns, accelerating patient identification, and ensuring resources are directed toward high-value opportunities. The result is a stronger return on investment, improved patient engagement, and earlier access to life-changing treatments.
Increased Market Share and Competitive Edge
AI can unlock competitive advantages by identifying overlooked patient subgroups and emerging treatment opportunities. By analyzing for example epidemiological data, prescribing behaviors, and real-world evidence, pharmaceutical companies can engage new patient populations ahead of competitors. This early-market entry accelerates treatment adoption, strengthens HCP engagement, positions companies as leaders in niche therapeutic areas and ensures that patients receive appropriate therapies sooner. In an otherwise fragmented landscape, AI-driven insights enable tailored outreach and strategic brand positioning, expanding market share while addressing critical unmet medical needs.
Improved Customer Satisfaction and Loyalty
AI-driven strategies significantly improve satisfaction and loyalty by ensuring healthcare professionals (HCPs) and patients receive highly tailored interactions and treatments.
For HCPs, AI optimizes communication, delivering the right message through the most effective channels at optimal times. This targeted approach not only enhances the HCP’s experience with biopharma companies but also improves diagnosis and prescription accuracy, directly helping enhance patient outcomes and driving HCP satisfaction. As a result, HCP loyalty to the drug brand strengthens, as they value the support that enhances their clinical decision-making.
For patients, AI can help physicians identify diseases more accurately and prescribe the most suitable medications. This leads to improved patient outcomes and satisfaction, as they receive more effective treatments with fewer trial-and-error approaches. This in turn can help lower treatment discontinuation rates and enhance patient trust in the healthcare system.
Since acquiring a new customer costs five times more than retaining an existing one, AI serves as a powerful tool to build long-term loyalty with HCPs and patients. By improving engagement and ensuring more effective treatment pathways, AI-driven insights benefit the bottom line while making a meaningful impact on patient care.
Real-World Impact of AI-Driven Patient Discovery
In the real-world, AI is already making a considerable impact in accelerating patient identification and improving treatment outcomes in rare diseases and precision medicine.
At Verix, our AI-powered platform for optimizing pharma commercial strategy and execution has demonstrated exceptional results. Biopharma companies have used Verix to help them predict critical points of intervention for identifying, converting and retaining patients with rare diseases.
For example, working with a leading biopharma, we leveraged our advanced data analysis and predictive modeling to uncover undiagnosed and misdiagnosed patients, reduced time to diagnosis and optimized HCP engagement with interventional messaging to reduce discontinuations. Taking 6 weeks until implementation, the company witnessed immediate results with Tovana’s triggers performing 12x better than baseline. Read the full case study here.
Another client partnered with Verix to optimize HCP targeting and patient retention. Within weeks, the Verix platform enabled a data-driven, timely approach—delivering engaging, tailored messaging to the right HCPs at the most opportune moments. This enhanced engagement, reduced patient discontinuation rates, and boosted new patient acquisition, ultimately capturing new growth opportunities and improving overall treatment adoption.
“In the rare disease sector where we operate, capturing every opportunity in a timely manner is crucial, and the insights provided by the platform, Tovana, allowed us to do just that.” – National Sales Director, Oncology, Specialty Medicine Company
Conclusion
It is clear that AI-driven patient discovery is no longer a futuristic proposition but is now a reality transforming how pharmaceutical companies approach precision medicine and rare diseases. By leveraging cutting-edge AI technologies, biopharma companies can now identify and engage patients earlier, reduce misdiagnosis, and optimize treatment strategies. Beyond improving patient care, AI delivers a crucial competitive advantage, streamlines operations and maximizes ROI.
About Verix We at Verix are leading the charge in this transformation, offering powerful AI solutions that streamline patient discovery in rare diseases and enhance healthcare outcomes. Discover how Verix can help you identify patients earlier, optimize commercial operations, and reduce costs. Learn more here: https://verix.com/.
