Webinars

In today’s cutthroat life sciences marketplace, commercial effectiveness in all its parts has never been so important. From field force effectiveness to optimization of promotional investment through to Next Best Action implementation, tailoring the customer experience through content and tactics is the focus. Cross-functional coordination across teams and operationalizing at scale are the goal. Come join Nabha Subramanya, VP of Data Science at Trinity Life Sciences and Anushank Anand, Director in Trinity’s Analytics practice, as they walk through the evolving omnichannel landscape and touch on the data science platforms and capabilities—as well as the “life sciences”-specific insights and expertise—that drive commercial success:

• Building an ML ecosystem
• Calibrating promotional strategies and campaigns in response to outcome and response metrics
• Operationalizing your ML systems

Not only are artificial intelligence (AI) and machine learning (ML) two of the hottest buzzwords in the life science industry, but the underlying technology is changing the entire landscape of pharma, biopharma, and biotech. Increasingly, these companies are utilizing AI/ML analytics to inform decision making across the development lifecycle – reducing costs and shortening timelines associated with traditional data analysis.

In this session, industry experts will share how powerful AI / ML analytics can be used in pre- and post brand launch to provide treatments more quickly to patients, followed by specific applications to:

• Identify early signs of disease
• Speed up clinical trial patient recruitment
• Predict patients likely to respond to treatment options
• Monitor adverse events and side effects
• Estimate high-risk and rare disease patients
• Understand patient’s journey from multiple lenses
• Maximize promotional marketing and budget allocation

The Pharmaceutical Industry is experiencing significant shifts across the value chain: from the increased focus on SDOH & health equity, to deep tech being embedded across touch-points; with new stakeholders & potential partnerships, emerging channels, the lasting pandemic effect on public distrust, compliance shifts and regulatory challenges; this is a time to Disrupt or Be Disrupted. We will share insights, action and provocations with relevance for Pharma companies exploring growth drivers, resilience through external changes and the application of AI, Data, Automation & Analytics.

Presenters:

• Sagar Shah, Head, Pharma Practice & Responsible AI, fractal.ai

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