Market access teams at pharmaceutical and life science organizations (LSOs) are critical to commercial success.
If it weren’t for their work pricing, launching, and negotiating reimbursement, many currently available drugs and treatments would not be covered by health insurance or might only be available at much higher prices, making them less accessible to people in need. Furthermore, drug pricing and marketing would be much less transparent and consistent, leading to confusion and frustration among patients and healthcare providers.
But market access teams still face a number of data and analytics challenges that can hinder their ability to carry out this work effectively. This post will explore these in more detail and outline how AI-powered approaches can help. 🦾🤖🦾
In This Post
Why market access data analysis is so hard today
Data informs—or should inform—pricing, reimbursement, and market access strategies. But most access teams struggle with effectively gathering and analyzing data for several reasons:
- Increasing volume and complexity of data: There is tons of data out there (reimbursement, real-world data, syndicated data from places like IQVIA and Symphony, etc.). Volume and variety are growing. Finding relevant and meaningful information is increasingly challenging. Pharmaceutical and life science companies risk losing market share if they fail to act quickly to market changes.
- Legacy systems, siloed data, and lack of standardization: Most pharmaceutical firms still rely on some mix of new and legacy CRM, ERP, EMR, and claims management systems. This limits the availability of up-to-date data and firms’ ability to integrate and analyze data from multiple sources. Oftentimes, even if data from various sources is available in a centralized location, integrating and analyzing differently structured data can be very challenging and time-consuming for market access teams.
- Need for technical analytical skills: Like other industries, market access teams face a technical talent shortage, leading to a gap in their ability to extract insights from data.
If these data challenges weren’t enough, LSOs additionally face evolving health models/markets (e.g., increasing vertical integration of payers, PBMs, and specialty pharmacies; more significant influence of physician networks on prescription patterns; healthcare M&A activities impacting pricing negotiation, etc.) and mounting pressure to demonstrate therapeutic value and health outcomes due to rising drug costs and the growth of high-cost drugs, leading to governments, payers, and health systems pushing back.
When LSOs are forced to manually piece together and analyze siloed, shifting data, they can delay critical decisions (or make them in a rushed manner), ultimately costing them untold millions of dollars and risking market share loss.
How AI-powered analytics can help market access teams
AI-powered analytics tools can help market access teams automate and simplify key pieces of their data analysis, resulting in better-informed access, pricing, and product launch decisions.
AI-powered analytics can help market access professionals
AI-powered analytics is specifically well suited to help access teams:
- Self-serve answers quickly for better, data-driven decisions by rapidly exploring formulary, claims, and target list data in natural language (i.e., in a Google-like search interface and automated data visualization of results).
- Speed up time to insights by getting to the root cause of access changes and payer behavior changes faster through ML/AI-powered diagnostic analytics.
- Unlock the value of Big Pharma data by easily connecting, blending, querying, and drawing insights from a variety of internal and syndicated data sources (e.g. Symphony, IQVIA, etc.) via no- and low-code analytics to reveal previously unseen connections.
- Rapidly experiment with and scale real-world data (RWD) use cases.
- Free up time and reduce risk by automating manual formulary monitoring for an up-to-date understanding of the market landscape—i.e., what brands are on the market, what their coverage looks like, and the impact of payer access.
- Anticipate payer and PBM responses to new product launches or indication expansions.
Auto-visualized results of a query regarding market share of a particular drug category
In addition to helping LSOs negotiate favorable market access, AI can help them:
- Scale data-powered functions, such as customer engagement programs and field sales/performance, via accessible, robust data and analytics capabilities.
- Support a broad range of end-user personas in one integrated, multi-persona analytics platform that helps everyone—from highly skilled data scientists or data engineers, to analysts, to the casual user who consumes data through ad hoc search and dashboards.
Explore the unknown and reduce bias by having more people explore new data, spotting insights that could have otherwise gone unnoticed in existing data, all while minimizing human biases and accelerating time to insight.
The evolving market access team's data and analytics toolbelt
AI-powered analytics tools complement traditional business intelligence tools. 🤝
Traditional BI tools are great at providing recurring, parameterized reports, and pre-canned dashboards of key metrics—whereas AI-powered analytics are ideal for ad hoc analysis and root cause identification to rapidly uncover why those key metrics are changing by automatically parsing millions of variables to surface likely drivers and correlations.
AI + BI fulfills the promise of self-service analytics for market access teams to rapidly generate their own analysis and insights from Big Pharma data.
Market access use cases of AI-powered analytics
AI-powered market access analytics is useful for a number of use cases:
1. Predict Impact of Access Changes
AI-powered automated insights quickly highlight the impact of access changes across payers to better inform contract discussions/negotiations to ultimately drive profitability.
2. Market Access Performance Optimization
Combine performance and formulary data to identify favorable access segments with growth opportunities.
Automated insights showing drivers of market access change
3. Contract Performance and Compliance Monitoring
Automate manual formulary monitoring for access and brand performance changes by comparing actual performance of contracted deals with PBM services and health plans vs. historical deal assumptions (which typically go untracked) to inform future contract decisions.
4. Product Launch Planning
Utilize predictive and prescriptive analytics to significantly improve upon traditional market research and data analysis techniques for product launch planning.
5. Highly Personalized HCP Content
Blend multiple data sources, such as medical claims and formulary coverage information, to enable HCPs to understand coverage levels.
AI is also useful in other commercial pharmaceutical applications, such as:
- Commercial effectiveness (e.g., ML-powered HCP targeting)
- Marketing (e.g., segmentation, targeting, or orchestrated engagements via omnichannel analysis)
- Quality and manufacturing (e.g., automated root cause analysis of quality issues)
- Patient journey monitoring and modeling
- Early drug discontinuation prediction
…and much, much more.
Real-world stories of AI-powered market access success
Several innovative pharmaceutical firms of various sizes already leverage AI to augment their market access functions. Here are a few examples of success:
Global Life Sciences Organization’s Market Access Team Develops Data-Driven Targeting Methodology That Drives 66% Growth in Patient Starts and Saves $1.6M
The market access insights team at a global LSO was relying on offshore technical resources to deliver target lists to the business using legacy BI tools and Excel. It was taking months to recommend strategic changes around underperforming areas.
This delay would have caused this LSO to miss its growth targets. After implementing Tellius, the market access team was able to efficiently develop data-driven targeting methodologies and grow new patient starts by 66% without doubling the size of the team, saving $1.6 million in resources.
The team is now able to iterate in real time with the business, resulting in improved decision-making across brands.
Midsize LSO Detects Market Share Drop and Rapidly Course-Corrects, Driving $7M+
A midsize life science organization’s market access team detected a 12% drop in market share for a particular drug. Using AI-powered analytics, the firm identified the systemic drivers of underperformance and growth opportunities, informing pull-through strategy.
The resulting course correction drove an increase in the brand’s market share by 7%, contributing $7.19 million in sales; reaching underserved HCPs using new channels to achieve a 43% increase in demand; and improving response time to market changes by using Tellius Auto-Insights to identify drivers behind trend breaks.
Young Biotech Company Successfully Shifts Gears from R&D to Commercialization Mode, Achieving 10X Improvement in Productivity Using AI
A biotech firm used AI to successfully shift gears from R&D mode to commercialization mode upon FDA approval of an innovative new treatment.
While the firm had an extensive R&D team, the market access and key accounts management teams lacked resources and had limited access to payer and plan performance information via predefined dashboards and dependency on their small IT team, causing productivity to lag significantly.
The firm implemented Tellius and achieved a 50% reduction in dependency on IT through natural language search, automated visualizations, and self-service dashboarding capabilities.
The result was a 10X improvement in productivity; earlier identification of market threats and faster responses, thanks to ML-powered insights and anomalies; and quicker identification of market opportunities and strategic industry shifts.
Conclusion
Market access teams at any size firm and analytics maturity level can benefit from AI-powered analytics. We’re honored to call several of the top 20 global pharmaceutical companies our customers, and our platform is continuously informed by our deep understanding of LSOs’ data and analytics challenges.
Check out our market access use case to learn how our platform can help you mash up third-party, sales, and marketing data across multiple sources to get diagnostic and proactive intelligence to fuel decisions.
