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Case Study: A Clinical-Stage Biopharmaceutical Company Saves $800K in Data Costs and Doubles Patient-Level Data Coverage with Medidata AI

Jan 24, 2023 - 3 min read
Case Study: A Clinical-Stage Biopharmaceutical Company Saves $800K in Data Costs and Doubles Patient-Level Data Coverage with Medidata AI

Summary

After investing years and significant resources in clinical development and R&D, clinical-stage biopharmaceutical companies only have one shot to successfully launch their product. A huge part of setting a company up for success is having access to the right patient-level data and operational data to guide your commercialization decisions.

But with over 50 different commercially-available real-world data (RWD) providers today, finding the right third-party vendor with the highest data coverage in your disease area can be an extremely time consuming, costly process—one where the stakes are too high to make the wrong decision. 

A clinical-stage biopharmaceutical company found themselves grappling with this very problem—overwhelmed by the number of data sources to choose from and unsure of which vendor to pick. Medidata AI partnered with this company to help them find the right dataset to fit their needs.

Customer

This mid-sized company develops transformative medicines in neuroscience and immuno-oncology. Their first FDA-approved treatment is a specialty medicine for patients with a psychiatric disorder.

Challenge

In preparation for their first commercial launch, the company was looking to buy patient-level data from a third-party vendor. However, the commercial team was overwhelmed by the number of data sources to choose from and was unsure of which vendor to work with. After conducting internal research, the company ended up purchasing a sub-optimal dataset—one that had very low coverage in their disease area.

The nature of this psychiatric disorder makes it difficult for treatment to reach key specialty groups. Because the condition is often viewed as a side effect, doctors are less likely to treat it. In addition, there had not been a launch of a novel compound in this disease area for 10 years. Given these stakes, the company did not want to make another misstep. They needed a data-driven approach to help them:

  • Find a high-coverage, reasonably priced dataset
  • Gain a better understanding of the market and patient journey
  • Create a targeted marketing and sales strategy

Solution

The company partnered with Medidata AI’s Commercial Analytics team to help them find the best data source to support their launch. Medidata AI’s Data Due Diligence offering helps companies build a best-in-class data stack to support current and future data needs. Leveraging over 15+ years of commercialization expertise, Medidata AI’s data-agnostic philosophy follows an empirical approach to understand the pros and cons of each dataset—including applicability, feasibility, cost, and delivery timeline.

The Medidata AI team analyzed all the available vendors on the market to find a dataset that fit the company’s budget and coverage requirements. Specifically, hospital and emergency room (ER) data—which is often lacking in third-party datasets—was essential to understanding this company’s disease area. With access to the largest real-world data network through partnerships with HealthVerity, Datavant, and others, the Medidata AI team delivered recommendations to the company in just four weeks.

Results

The Medidata AI team identified the best patient-level data to track psychiatric events to improve the accuracy of brand forecasts and analyst guidance and to optimize sales efforts. Not only did the selected dataset capture double the patients, but the Medidata team also negotiated a discount on behalf of the company that resulted in $800,000 in savings. 

The charts below show part of the extensive analysis Medidata performed to find the best dataset to support this company’s launch. 

Patient level data analysis - Medidata AI

This dataset answers some key questions for the company that will inform their commercial strategy, including:

  • The treatment journey for psychiatric patients in the U.S.
  • How psychiatric patients flow through the health system
  • The drugs patients receive throughout their treatment journey
  • Pockets of undertreated/underserved psychiatric patients
  • Whether artificial intelligence and machine learning can be applied to assist in drug discovery

Armed with these insights, the sponsor is now able to refine their marketing strategy to optimize effectiveness and resource efficiency. The company will continue to work with Medidata AI to gain more insight into the patient journey post-launch. 

About Medidata AI

Medidata AI Commercial Analytics provides the advanced analytics services and data expertise that give drug manufacturers a 360-degree view into the performance of their product, making sure the right patient gets the right treatment at the right time. 

Whether launching a new product or supporting a mature one, commercial launch teams need powerful AI and ML analytics capabilities that quickly ingest data and deliver fast, accurate insights to stakeholders across the organization—no matter where they are in the product life cycle. Our data agnostic philosophy, deep life sciences domain, and data ecosystem expertise let manufacturers turn their data into a competitive advantage and reach peak sales faster.

Learn more about Medidata AI.

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Case Study: A Clinical-Stage Biopharmaceutical Company Saves $800K in Data Costs and Doubles Patient-Level Data Coverage with Medidata AI