Webinars

We will convene one or more life science analytics experts to explore the advantages of using commercial and Medicare data to understand patient journeys. The experts focused on cancer care/rare disease will discuss insights gained from time-based analysis and use it to find newly diagnosed patients and patients where disease progression has required changes in LoT.

The webinar will discuss the following questions:

• Why is it important to follow the patient journey:
• From pre-Medicare eligible to Medicare eligible?
• From the first line of treatment to later lines of therapy?
• How to evaluate the drugs in the market basket?
• What’s the lookback period?
• What are your best practices for asserting with combos or line switching?
• How to leverage data to better manage provider outreach?

Panelists:

• Ashish Patel, Chief Growth Officer and co-founder, CareSet
• Amy Bamford, Business Development Director, CareSet
• Tom Boulay, Deciphera, Senior Director of Commercial Insights

In today’s world of rapidly evolving analytics, legacy reporting and BI platforms hinder a company from using analytics to its full potential due to the associated technology barriers, limited capabilities and long development cycles. The promise of competitive differentiation is driving commercial organizations to invest in AI/ML powered analytics. Secondly, AI-powered insights coupled with enhanced user experience and productivity allow businesses to engage customers more effectively. As a result, there is an increase in AI adoption for meaningful business insights that are easier to access, faster and cost-effective compared to the legacy solutions.

Join us in this interactive panel discussion to hear from industry stalwarts how AI/ML/NLQ powered analytics enable accelerated insights and improve customer engagement for business success.

Key discussion points:

• Business impact of democratized access to data insights and customer engagement
• Role of AI/ML in the evolution of analytics: data integration at scale, expedited insights cycle and improved customer engagement
• Key factors to consider for successfully utilizing AI/ML: richer data sources, 360 degree view and domain focus
• Top themes for life sciences enterprises and commercial organizations for deploying AI/ML

Moderator:

• Richard Clements, VP Marketing, WhizAI

Panelists:

• Dharmesh Thakkar, Sr. Director - Commercial Operations, Janssen Pharmaceuticals
• Stuart McGuigan, Senior Advisor, McKinsey & Co (former CIO Johnson and Johnson)
• Manesh Naidu, Consultant

Asthma presents a large burden to the U.S. healthcare system:

• Estimated prevalence of 26 million
• Annual health expenditure of approximately $50B
• Severe flare-ups account for 1.7 million emergency department visitsannually

An unmet need for more advanced treatment persists.

In this webinar, Pfizer and Veeva will discuss how they modeled asthma exacerbation risk factors. Using longitudinal medical and pharmacy claims data, they investigated:

• The landscape of asthma in the U.S.
• COVID-19-related trends
• Which risk factors predict asthma exacerbations across all providersettings

Their findings show how patient data can be integral to identifying the right patient sub-groups for drug development and to inform better disease management strategies for patients.

Speakers:

• Andres Quintero, M.D., M.P.H., M.B.A., Global Medical Affairs Director, Glucocorticoid Portfolio Lead, Pfizer
• Patryk Skowron, Ph.D., Data Scientist, Veeva Systems - Commercial Analytics

The amount of data available across marketing channels has exploded in recent times, leading to information overload without true insights. Our panel of experts with extensive experience in storytelling and insight mining will discuss how complex data can deliver easily understandable insights that drive action.

Panelists:

• Robert (Bob) Allen, Lead, Worldwide Engagement & Channel Planning, US/Canada Oncology at Bristol Myers Squibb
• Lisa Hernandez, Senior Director, US Omnichannel Marketing, Daiichi Sankyo Inc.
• Siva Tallavajhala, Director, Omnichannel Mktg Innovation & Development COE, Menarini-Stemline
• Vandana Singh, Principal, Omnichannel Practice, Axtria
• Devesh Verma, Principal, Omnichannel expert, Axtria

AI-ML can be used across various use cases in Bio Pharma. While popularly known to be used for identifying and accelerating new drug discovery & clinical applications especially in precision medicine, there is relevant and powerful application within the commercial setting as well to enable the right patients access to the right treatment at the right time.

In this presentation, Definitive Healthcare will showcase use cases across functions.

• A primary care drug hone & target to optimize a narrow strategic opportunity successfully (T2d)
• An expensive first in class statin with a niche indication find appropriate patients & broaden access
• Enabled a Biotech to get to market faster via accelerated enrollment
• Optimized patient compliance and reduced Patient Support Program spend via targeted interventions thru AI-ML predictive risk scoring of patients for non-compliance along with AI to determine top reason for non-compliance enabling right intervention at right time for right patient within Patient Hub

Real world data is increasingly being drawn upon by the Life Science industry to inform a broad range of business functions throughout the product life cycle, including clinical trial support, market insight, comparative effectiveness, understanding existing care standards and much more. And despite the richness of insight available through E.H.R and claims-based data assets, we sometimes encounter concerns from end users about the data quality, and its ability to support the analytic goals of an organization. Oftentimes, such complaints are the result of misconceptions around what RWD reflects vs. their desired analytic purpose.

This discussion will provide a useful snapshot into some common pitfalls we encounter when it comes to data interpretation, use and expectations – along with recommendations as to how they can be managed/avoided.

Legacy self-service analytics require extensive data model training and deep technical knowledge to be used effectively. The alternative is developer-driven dashboards that have too broad a scope and are not unique to each user request, territory, or country. Every new data insight requires the creation of a unique dashboard, custom-built to address the specific needs of each request. These dashboards have long development cycles and can only answer the specific analytics questions for which they are built. With existing solutions it is difficult for business teams — especially non-technical users in sales and management positions — to use reporting and analytics to its full capacity.

These problems hurt an enterprise pharma’s competitive advantage in the industry.

Join us in this interactive presentation session to hear from industry stalwarts how life sciences-trained, AI-powered analytics enables accelerated decision-making to drive commercial success.

Key Discussion Points:

• The historical role of commercial insights and the exponential evolution of data and insights and what it means for commercial operations
• Key capabilities to look for when reimagining commercial insights and the role of AI, ML, and NLQ
• The business impact of democratizing access to insights to help business users make smarter, faster decisions at significantly lower cost

A new era is dawning in analytics, but organizations must be thoughtful in what augmented analytics technologies they incorporate to achieve the holy grail – a one-stop-shop where users can connect to all data, easily share all the insights across the business and do this for real-time and batch use cases. In this live webinar, hear from two leading data and analytics technology experts as they discuss:

• What do the next generation business insights solutions look like and how augmented analytics technologies fit into this vision
• How this solution can be commercial ready and coexist in your current ecosystem
• Where people and process come into the picture and considerations from an organization's perspective
• The challenge of bringing this all together so business users and analysts will use its full potential

Provider affiliations, between practitioners and facilities and facilities and IDNs, have been a foundational element of pharma analytics. Yet, building accurate provider affiliations is hard. One reason is scale. With millions of links across HCPs (healthcare professionals) and healthcare organizations (HCOs), manual or survey-based methods are limiting.

In this webinar, Compile, Inc. will describe a novel approach to constructing affiliations. Using a combination of graph networks and data triangulation, the drawbacks of individual data sources are mitigated. Further, participants will learn how graph structures are well suited in capturing the complex hierarchy that characterizes health systems today. Finally, the webinar will explain how this new affiliation structure, with quantitatively scored links, can help in common pharma use cases from sales attribution to account-based targeting. The webinar will be targeted toward data and analytics savvy audience.

The landscape in which pharma companies have been operating was changing even prior to the COVID-19 pandemic. The pandemic accelerated changes that were already happening.

• Industry’s access to healthcare professionals (HCPs) is diminishing
• Promotional materials need to be more personalized for the HCP to engage with them
• Broader changes in the healthcare market (centralization of healthcare organizations, broader restrictions on healthcare expenditures, regulations such as the Sunshine Act, etc) have diminished demand for reps
• Today’s HCPs demand more choice in both the message, frequency, and the medium

While untangling all these trends is a difficult task, Veeva has created a framework that is flexible enough to encompass the data available on many of these trends. In addition, this model takes into account that there is heterogeneity in the marketing approaches of different companies, and in how effective they have been in adopting each channel.