Webinars

Join our webinar to learn about an innovative system to significantly ease the discovery of pharmaceutical insights! Dive into the automated low-code/no-code process to swiftly create a dynamic data foundation and feature store. Introducing the novel utilization of Large Language Model (LLM) for fast, natural-language-based queries, significantly slashing time and costs. This isn't just theory; it's a proven solution vetted by top pharma companies. Don't miss out—register now for an exclusive look into the future of streamlined, efficient pharma data utilization!

In this webinar you will hear about:

• Fast-track auto-creation of a dynamic data foundation
• Low-code/no-code simplicity for seamless integration
• A demo of our Lightning-fast queries with Large Language Model (LLM)
• Proven solution validated by leading pharma companies
• Exclusive insights into the future of efficient pharma data utilization.

Speaker: Shahar Cohen CTO at Verix

Shahar heads Verix’s AI lab, leading the innovation behind the Tovana™ platform. A Data science researcher with 20 years of experience in starting and leading complex data ventures. He co-founded two AI / Machine learning startups: Optimove and YellowRoad, and worked as a consultant and hands-on service provider with more than 50 organizations, in a variety of domains: NLP, Reinforcement Learning, Deep Learning, Classic Supervised & Unsupervised Learning and in many verticals.

Join our insightful webinar to explore the dynamic intersection of artificial intelligence and life sciences. In this session, we will delve into the groundbreaking advancements in generative AI and large language models (LLMs) and their transformative impact on advanced analytics in life sciences. Our experts will guide you through the latest trends, challenges, and opportunities that AI-driven analytics offer in this rapidly evolving field.

Key Learnings:

• Understanding AI in Life Sciences: Gain a comprehensive overview of how AI, particularly LLMs, are revolutionizing analytics.
• Practical Applications and Case Studies: Discover real-world examples where generative AI and LLMs have significantly advanced actionable insights for commercial organizations.
• Buy vs Build: Explore the strategic decision-making process on Buy vs Build when navigating the choices for AI and large language models in life sciences.

Don’t miss this opportunity to stay ahead in your field. Register now to secure your spot in this enlightening journey into the future of life sciences powered by AI. Join us to be a part of this innovative conversation and transform the way you understand and utilize generative AI and LLMs in life sciences.

Speakers:

• Amitabh Patil, Co-Founder and CTO, WhizAI
• Saurabh Kelkar, Director, Account Management, WhizAI

Reliable data projections is a cornerstone of analytics in the Life Sciences industry, from market share tracking, territory sizing, to incentive compensation and more. Since projections rely heavily on claims, which are not a random sampling, the foundation of these analyses often suffer from biases and gaps. This makes projecting data difficult and time-consuming, often leading to incorrect results. 

Understanding true market dynamics requires a diverse set of deeply characterized sources, as well as coverage profiles of each contributing source to enable the calculation of reliable insights. 

Join Dr. Paul Gurney, Senior Vice President, Data Product Management at Komodo Health, in an upcoming webinar to learn about Komodo’s best-in-class projection methodology and real-world example outputs.

In this session, Dr. Gurney will share:

• Our methodology behind the most robust projections available (74% higher than legacy aggregators), and how it differs from traditional approaches
• Avoiding and accounting for areas of low visibility when projecting subnationally
• Creating outputs on metrics of interest beyond NRx and TRx

Even as digital investments increase, the field force remains the primary means of customer engagement for pharma companies and is their biggest promotional investment. As a means of providing guidance to the field, traditional call planning occurs infrequently and in cycles, oftentimes failing to incorporate the latest data available to drive rep activity and customer interactions. Dynamic Targeting leverages digital investments by bringing data and insights to the field force in a more timely manner, enabling more real-time, data driven decisions. Using the latest customer and data insights, Dynamic Targeting provides clear, effective, guidance to empower field teams to optimize brand reach and drive exceptional customer engagement.

In this webinar, we will explore the following with industry leaders Stephanie Odutola and Owen Morris from AstraZeneca:

• Laying the groundwork: defining Traditional Call Planning, Next Best Action, and Dynamic Targeting
• Ensuring stakeholder buy-in
• Evolving the Commercial Operations function to support Dynamic Targeting
• Overcoming the barriers to Dynamic Targeting adoption
• Measuring the impact of Dynamic Targeting
• Making the leap from Dynamic Targeting to full Omnichannel Orchestration

Better understanding of content and content insights are moving the vision of transforming and optimizing the content supply chain closer to reality. Learn how to lead your organization toward a data- driven approach to marketing using the “right content” with Kate Greengrove, head of U.S. commercial strategic operations and capabilities, GSK, and Kumar Saurabh, global lead for content transformation, ZS.

They’ll discuss how companies can:

• Start small and bring incremental changes to the current ways of working
• Use data and insights to create and use high-performing content
• Predict content engagement even before deployment to enable better content planning .

Artificial intelligence is pushing the pharma industry forward, but where does the road go? Artificial intelligence (AI) and machine learning (ML) are revolutionizing how pharma organizations operate to identify treatment-ready patients, accelerate drug discovery, size marketing, enhance post-launch promotional marketing, and much more. To put a spotlight on both the biggest benefits and concerns regarding the use of AI/ML in pharma, Definitive Healthcare reached out to pharma companies through an online survey conducted in July 2023. We learned from leaders, decision-makers, end-users, and other professionals how the use AI/ML today, and what their hopes and concerns are for the future to create the "September 2023 Industry Report: Use of AI/ML in Life Sciences".

During this webinar we’ll discuss some of these survey results and interviews and share our thoughts on the future of AI/ML in the future of pharma and the overall healthcare market. Webinar attendees can receive the full report and an opportunity to connect with our panelists in a follow-up conversation.

Pharma’s investment in digital has grown significantly in the last few years, fueled by the proliferation of digital channels and evolving customer preferences. This has made customer journeys very complex, with customers choosing how and where to interact with your brand in a unique and on-demand manner. With these trends in play, we must ensure a holistic measurement approach towards measuring and optimizing omnichannel campaigns.

In this webinar, we discuss orchestrating various analytical approaches, such as Marketing Mix Modeling, attribution modeling, and campaign analytics in tandem at varying cadences to enable outcomes-driven omnichannel campaigns. We will also discuss how Marketing Mix outputs must evolve to inform downstream Next Best Action recommendations.

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