Webinars starting with C

Insights at the intersection of claims and integrated delivery network data can empower pharmaceutical and medical device companies to identify and prioritize high-value sales targets and opportunities. With many internal layers, connections, and networks invisible to outsiders, the modern Life Sciences universe has created new challenges for brand teams at pharmaceutical and medical device companies.

In recent years, Life Sciences organizations have operated in a challenging healthcare environment. Value-based care reimbursement models seek to improve outcomes while reducing costs; patient access to high-cost branded therapies is sometimes restricted; and acquisitions among hospitals and physician practices are now commonplace. One result of the altered operational landscape is a new model for care delivery: the Integrated Delivery Network (IDN).

Join Rebecca Hauck and Anja M. from LexisNexis® Health Care to learn how you can bring clarity to this complex universe by combining IDN provider and facility level data with medical claims volumes to help Life Sciences organizations determine the value of IDNs for a particular therapy area. These insights help transform challenges into opportunities by optimizing business processes, increasing market share, reducing coverage gaps, and improving revenue growth.

Presenters:

• Rebecca Hauck, LexisNexis Health Care
• Anja Maciagiewicz, LexisNexis Health Care

Use of advanced analytics has been widely accepted by pharma companies in both drug discovery and development phases as well as for developing commercialization strategies. With the growing richness of new-age data sources like Real-world data, the application of advanced analytics has become relevant in place of conventional analytical methods.

In this webinar, we will be taking you through the application of advanced analytical techniques in building deeper understanding of a therapeutic area by analyzing the patient, provider and disease related factors that are driving treatment choices. We will be discussing the complexities that exist in Real-world data sources and how to systematically navigate through the same in making them analytics-ready. We will also be covering best practices in utilizing popular unsupervised classification techniques.

Presenters:

• Srikanth Katasani, Principal Consultant, D Cube Analytics
• Swetank Gupta, Associate Consultant, D Cube Analytics

Pharma organizations are undergoing changes where the focus is more on transformative medicines catering to unmet need and on smaller agile R&D cycles. Tackling a complex ecosystem of patients, providers, payers, and regulators among other entities requires organizations to strengthen their predictive modeling capabilities. Traditional predictive modeling can be complemented further through application of System Dynamics, Networking Modeling, and Simulation. These models enable future insights while utilizing historical behavior, provide the ability to incorporate real-world feedback instead of reliance only on linear cause-effect relationships, and account for a more exhaustive set of parameters that capture customer interactions.

Various industries are utilizing these System Dynamics and Network Modeling techniques to enhance models for product launch, market mix, and ROI optimization, among others. Pharma companies can benefit from these methods to improve their commercialization effectiveness across similar problem areas. One such instance is where we helped a pharmaceutical company leverage system dynamics to model the effect of a biosimilar launch on the market share. Being able to simulate the impact of a biosimilar launch made the organization more proactive and nimble in modifying strategies. In this webinar, we will look to answer two key questions:

• How have network modeling and system dynamics been applied by pharma and organizations across other industries to drive business value?
• How can these techniques help pharma commercialization teams tackle the uncertain and complex ecosystem?

Presenters:

• Sridhar Turaga, Head of Technology, Mu Sigma Inc.