MMIT (Managed Markets Insight & Technology)

There is no doubt that payers in the U.S. are investing heavily in AI, but there is much uncertainty about how this technology is currently deployed. While the industry’s AI conversation has focused on generative tools and administrative efficiency, payers are increasingly deploying AI in utilization management, clinical pathways and contracting.

A midsize pharma company launched an oncology therapy with a novel drug delivery mechanism to reduce tumor toxicity. As the company’s market access team had secured favorable formulary placement with most major payers, it expected a steady uptake curve. However, adoption rates remained low. The manufacturer needed a better understanding of how IDNs might be negatively impacting its brand’s utilization.

Understanding the complexity of the payer market requires more than just enrollment data. MMIT’s Landscape iQ solution provides a clear, detailed view of how the market is changing and which entities are driving access — connecting lives, plans, organizations, geographies, relationships, and historical context in one interactive tool.

Launching a new therapy is one of the most consequential moments in a pharmaceutical brand’s lifecycle. As we’ve said before, you only launch once! The difference between brands that achieve their uptake goals and those that fall short often comes down to one factor: how quickly can a team identify problems and adapt their strategy accordingly? Many manufacturers enter a brand’s launch year with carefully developed forecasts, access assumptions, and adoption targets.

As artificial intelligence (AI) transforms how life sciences organizations access and analyze real-world data (RWD), one challenge looms large: ensuring that these powerful tools are used appropriately. RWD can illuminate patient outcomes, accelerate research, and guide better decision-making—but only when it’s handled ethically, transparently, and within the boundaries of contractual and regulatory use. Here are some ways to avoid the misuse of RWD with AI.

Biomarker testing is a cornerstone of modern oncology, transforming how clinicians diagnose, stratify, and treat cancer. By identifying particular genetic, molecular, or protein characteristics in a patient’s tumor or blood sample, biomarker tests provide invaluable insights into disease behavior and a patient’s potential response to various therapies. In recent years, advances in next-generation sequencing (NGS) have dramatically shortened turnaround times without sacrificing accuracy.

Machine learning (ML) and natural language processing (NLP) are reshaping how life sciences organizations uncover patients, engage providers, and improve access to therapies. By connecting rich real-world data with advanced analytics, these technologies reveal deeper patient journey insights that strengthen commercialization and market access strategies.

Urinary tract infections (UTIs) rank as the most common bacterial infection for women worldwide. Between 50-60% of adult women experience at least one UTI in their lifetime, and approximately 25% of them suffer recurring infections, defined as two or more episodes within six months.

Discover how a leading healthcare IT company enhanced prescription benefit verification for its clients using MMIT’s analytics platform. By leveraging Rx BIN/PCN/Group data, the company delivers accurate, patient-specific coverage information for potential prescriptions. Physicians can now use the company’s platform in near-real time to identify a patient’s coverage details and eligibility requirements for any medication—without needing to submit a claim.

As an integral member of the MMIT sales team, Bryan Nieves is responsible for identifying and pursuing new opportunities to provide real-world data and clinical expertise to pharma companies. He establishes new client partnerships and expands existing partnerships with legacy clients who are now facing additional needs. Tell us a little bit more about your role.