Webinars

Pharma spends nearly $4 billion a year on direct-to-consumer (DTC) advertising with no signs of slowing down. Yet, many pharma companies still struggle to analyze and optimize linear TV and digital marketing because they don’t know which components most effectively drive patient behavior and impact sales. By linking TV and digital ad exposure to health data in a privacy-safe way, clients can customize metrics to measure real world health actions and ultimately ROI.

In this webinar, we will demonstrate closed-loop measurement success through a client’s experience analyzing a specific TV campaign’s reach to a qualified audience and the campaign’s success in prompting action (for example: visiting a doctor, scheduling a screening, getting a script for the brand, etc.). Attendees will learn from this real-world example how closed-loop measurement provides best practices for directly measuring an advertisement’s impact on the patient journey and collaborating with creative and media agencies.

Presenters:

• Greg Fry, Patient and Consumer Marketing Analytics, ZS Associates

In the last few years, many companies have started to implement AI/ML practices to elevate user experience. Common examples of AI/ML include movie recommendations on Netflix, self-drive cars from Google, and photo tagging face recognition on Facebook. Pharmaceutical companies are also exploring ways to leverage AI/ML to improve the efficiency of their Operations and Sales teams. For example, AI/ML techniques can be used to perform early-stage error detection during data ingestion processes, leading to significant time and cost reductions. Additionally, AI/ML techniques can be utilized to increase the efficiency and effectiveness of sales representatives by providing them suggestions on next best actions. Throughout this session, we will be covering use cases of advanced AI/ML techniques to help pharmaceutical companies answer three key questions when working on Commercial Operations projects:

• How can AI/ML techniques help improve incentive compensation execution?
• How can AI/ML assist the sales reps in determining the next best target to call on?
• How can AI/ML help with optimizing territory alignments?

Presenters:

• Tej Pandey, Lead, Commercial Excellence, Axtria;
• Ellie Houck, Consultant, Commercial Excellence, Axtria; and Landi Huang, Consultant, Commercial Excellence, Axtria

There is a lot of focus and investment in developing multiple analytical models each year by Insights and Analytics (I&A) teams. However, only a select few models are making the cut and being leveraged for translating strategy into actionable deployment. The objective of this webinar session is to provide an overview of various popular analytical models being leveraged across the Pharma Commercial Operations value chain. Additionally, the evolution/emerging industry trends will be addressed.

Presenters:

• Vineet Rathi, Principal, Axtria
• Erik Christianson, Director, Axtria

In order for pharmaceutical companies to achieve favorite formulary position, they are providing more discounts and rebates to payers. In addition, the key account management (KAM) team is also investing significant effort with HS/IDNs for influencing treatment guidelines. Manufacturers must consider the influence of payers and providers on treatment decisions and reconfigure their strategy and operations. The objective of this webinar session is to provide an overview of the HCP scoring and segmentation approach based on payer and IDN influence, and how HCP scoring can be leveraged to optimize call plans.

Presenters:

• Rakeshkumar Shingala, Associate Director, Axtria
• Anuj Sheoran, Senior Manager, Axtria

Rare diseases contribute a significant burden of illness due to the challenges associated with diagnosis. For the ~8,000 adult-onset or age-neutral rare diseases, patients can wait years between symptom onset and diagnosis leading to disease progression and poor outcomes. Biopharma companies struggle to efficiently engage and educate providers on rare diseases because most providers will see less than a handful of patients with a given rare disease over the course of decades of practice. Powered by large, provider identified clinical encounter data sets, machine learning models can now be used to compliantly “identify” providers who are managing patients with undiagnosed rare diseases.

Presenters:

• Aswin Chandrakantan, M.D., Head of Product, Chief Medical Officer, Komodo Health
• Neeraja Krishnaswamy-Bhagavatula, Alnylam

While many organizations are experimenting with machine learning in various corners of the organization, many are asking how to create something more robust. “How do we move from small, one-off experiments to something more repeatable and scalable?”. In this webinar, we’ll present a point-of-view on the critical elements and capabilities your organization will need to get there.

Presenters:

• Phil Daniels, VP, Data Ops and Analytics Platforms, Indegene

As the stakes get higher for pharma companies vying for a physician’s time, HCP preferences need to be closely monitored to justify their investments in the channel mix. The sustained demand for medical representatives over the years has forced many manufacturers to rethink the effectiveness of their digital channels and raise questions about the way forward. This webinar takes a look at how HCP behavior has changed over the last few years, what new parameters influence prescription and why pharma companies should relook at their website quality to support physicians.

Presenters:

• Mike Steward, Chief Analytics Officer, Indegene

Nearly half of all launches fail to meet first-year financial expectations. From the moment commercial planning begins, new product launches face a gauntlet of challenges. By applying a scoring model to new product launches, four archetypal launch profiles have been identified. Each Launch Archetype is defined by the product’s ability to fulfill a currently unmet need in the market and level of differentiation.

Understanding which Archetype defines a product’s launch can increase its chance of succeeding. Each Archetype comes with its own set of considerations, marketing implications, and associated launch challenges. Thus, a product’s Archetype should factor into key aspects of the launch plan including the product’s positioning, critical success factors (CSFs), key performance indicators, and the promotional budget.

Key Takeaways:

• An understanding of Launch Archetypes and their market profiles
• Science Sells
• Market Shaping
• Emphasize the Difference
• Who Benefits
• Strategic trends among Market Shaping launches
• Market factors influencing the trends
• Brand team responses to trends
• How to use Archetypes when developing a launch plan
• Identifying strategic themes
• Enhancing product positioning
• Developing Critical Success Factors
• Determining promotional investment

Presenters:

• Darin DeCarlo, Senior Principal & Segment Lead, Commercial Services, US - IQVIA
• Bill McClellan, CoE Leader, Launch Excellence, Commercial Services, US – IQVIA

The previous webinar focused on the strengths and weaknesses of each type of patient-level data. As you learned, while there are many strengths in each type, there are also gaps. Many of these gaps can hinder answering your complete research question. So how can you use real-world data and not compromise your research? The answer is in integration, bringing these datasets together.

This webinar will examine different methods for integrating RWD so that you can answer your patient-centric research objective. As part of this integration, the webinar will also examine how integrating other types of datasets with traditional RWD can offer unique insights in ways that could never be done before. Specific user cases and research questions will be examined to help illustrate RWD integration.

Presenters:

• Tom Haskell, Global Head of Data Analytics, Kantar Health

Organizations are transforming their sales functions from being reactive to proactive, and from intuition-driven to insight-driven. The emergence of vast amounts of sales and patient level data from multiple sources and platforms has provided companies with more information than they’ve ever had before. Machine learning is a branch of artificial intelligence that enables computers to recognize patterns in existing data, update with new patterns from incoming data and continuously optimize recommendations. Innovative machine learning methods, together with clinical insights and continuous model enhancements, provides superior proactive and precision targeting results. It allows sales functions to improve their sales performance and effectiveness.

In this webinar, we will discuss the following aspects:

• Business objectives and benefits of proactive sales strategy
• Proactively identify sales potentials among targeted universe
• Help sales functions update/prioritize their target and call focus with patient insights
• Improve sales performance
• Outline of machine learning methodology and process
• Data collection, cohort define and feature calculation
• Model build and selection
• Model validation & application
• Model enhancements and validation on precision targeting
• Model introduction: Logistic, Random Forest, XBG, Deep learning
• Enhancement: Stacking, Ensemble, etc (flexibility of using models)
• Demonstrate how proactive and precision targeting optimizes sales performance
• Illustrate how to validate model accuracy on a timely manner
• Describe case study objective
• How selected model is implemented
• Validation on precision on a timely manner
• Other insight of targeting in a timely manner
• Patient profile
• Doctor insight

Presenters:

• Li Zhou, Sr. Principal, Advanced Analytics Organization, Global, IQVIA
• Zhang Zhang, Manager, Advanced Analytics Organization, IQVIA
• Lynn Lu, Senior Principal, Advanced Analytics Organization, IQVIA