2024 Fall Symposium - Agenda

Fall Symposium • Chicago, Illinois • October 3-4

Symposium Sponsors

Axtria
Opitmize Rx

THURSDAY, OCTOBER 3, 2024

07:30 AM - 08:30 AM

Breakfast

08:30 AM - 08:35 AM

 Welcome & Opening Remarks

More information coming soon!

Speaker: TBD

08:35 AM - 10:05 AM

 Workshop 1: Leveraging Causal Inference Methods to Measure the Impact of DMA-Level DTC Marketing Campaigns

This session will explore the challenges and solutions associated with measuring the impact of DMA-level Direct-to-Consumer (DTC) marketing campaigns in the pharmaceutical industry. Participants will examine various causal inference methods, including Coarsened Exact Matching (CEM), One-to-One Matching, and Synthetic Control. Through real-life applications, attendees will gain practical insights into the strengths and weaknesses of each method, empowering them to make informed decisions and optimize marketing resource allocation. The session aims to enhance the expertise of business analytics professionals by providing actionable insights into advanced causal inference strategies.

Speaker: Thomas Boyle, Mengyao (Vivian) Zheng

10:05 AM - 10:30 AM

Poster Break

10:30 AM - 12:00 PM

 Workshop 2a: Accelerating Pharma Business Analytics with AI-Ready Data Products Strategy

This workshop offers a deep dive into transforming data management within the life sciences industry. You'll discover how a data products strategy can unify fragmented data landscapes, decentralize ownership, and harmonize data across regions, brands, and therapeutic areas. We’ll highlight how leveraging Analytical-Ready, Report-Ready, and Generative AI-Ready Data Products drives faster analytics, reduces operational costs, and fosters innovation. Through real-world case studies and actionable insights, you’ll learn how this approach accelerates time-to-insight, enables self-service analytics, and empowers AI solutions—while significantly enhancing data quality, trust, and overall operational efficiency.

Speaker: Rajesh Choudhary, Ed Scura, Jaan Nashin Singh


 Workshop 2b: Enabling EDA Automation for Commercial Analytics using LLM

More information coming soon!

Speaker: Jalpeshkumar Chavda, Sriram Ananthakrishna

12:00 PM - 01:00 PM

Lunch

01:05 PM - 01:50 PM

 Breakout 1a: Methodological Advancements to Get More from Your Retrospective Match Analyses

Retrospective Matching Analyses (RMA) are often relied upon to conduct impact assessments of promotional/educational activities when a randomized control trial is not feasible; despite the ubiquity of RMA applications in practice, many practitioners of the techniques may be unaware of their pitfalls when not properly deployed. Moreover, recent literature in the RMA space has demonstrated that even some of the most traditional of RMA methods need to be revisited and in some cases even abandoned (most notably Propensity Score Matching). In this presentation we will provide an overview of the fundamental assumptions underpinning RMA. Additionally we will provide a survey of traditional methods and highlight the shortcomings/requirements of each.

Speaker: Nathan Corder


 Breakout 1b: AI-Powered LoE Forecasting: A Novel Approach to Sales Erosion Prediction

Loss of Exclusivity (LoE) is a critical event in the product life cycle, leading to sales erosion of branded products due to competition from generics. Traditionally, the ranges for sales erosion post-LoE are estimated through Analogue Analysis, which involves a collaborative cross-functional effort for data gathering and attribute selection. However, this process is often cumbersome and time-consuming, with a high probability of errors or missing crucial information.

To address this challenge, we developed a UI-driven analogue selection app that uses AI algorithms to measure product similarity. This app allows users to quickly run different simulations to select the best analogues and estimate the final erosion curve in just a few clicks, without any data processing or manual analysis. The app features a comprehensive repository of approximately 300 analogue products from different therapeutic areas, along with 50+ selection attributes developed in collaboration with medical, commercial, and access experts. It employs state-of-the-art supervised and unsupervised machine learning models for analogue selection and generates additional insights for strategic decision-making.

This session will provide an in-depth look at the development and implementation of the analogue selection app, showcasing its impact on reducing time and effort in analogue identification and improving the accuracy of sales erosion estimates post-LoE.

Speaker: Sunil Kushwaha, Aayush Tandon

01:55 PM - 02:40 PM

 Breakout 2a: Enhancing Patient Analytics: Merck’s AI-Driven Platform for Superior Data Accuracy and Insights

This session will provide an overview of Merck’s innovative in-house solution designed to enhance patient analytics, thereby achieving launch excellence in the Pulmonary Arterial Hypertension market. The key takeaway for the audience will be to recognize the immense potential of machine learning and artificial intelligence in driving analytics across commercial functions.

Speaker: Anuya Aher, Tejesvi Tadepalli


 Breakout 2b: Utilizing AI to Identify Unrealized Opportunities and Optimize End-to-End Field Force Operations

This presentation will showcase how Bayer has fundamentally transformed Field Force Operations into a practical and sophisticated one using an Artificial Intelligence/Machine Learning-driven approach across 3 primary sub-functions - Design & Planning, Execution and People.

Speaker: Eren Sakinc, Saurabh Sarker

02:45 PM - 03:30 PM

 Breakout 3a: AI Driven Customer Experience in Oncology

In today's rapidly evolving oncology landscape, organizations must embrace the power of predictive analytics and AI-driven capabilities to enhance customer experience. By strategically deploying AI-powered solutions, we can streamline workflows, personalize engagement, and improve outcomes for healthcare providers, patients, and their caregivers. We should aim to harness AI capabilities to anticipate customer needs, optimize touchpoints, and deliver a seamless, data-driven customer experience that sets a new standard of excellence in the oncology space.

Speaker: Srikanth Polireddy, Mohit Singla


 Breakout 3b: Transforming Segmentation Strategies with AI and Machine Learning

HCP segmentation, also known as customer segmentation, is the process of dividing healthcare professionals (HCPs) into distinct groups based on certain characteristics or criteria. This segmentation helps pharmaceutical companies to better understand their customers and tailor their marketing strategies and communication efforts accordingly.

Speaker: Sathyan Kallamparambil

03:30 PM - 04:00 PM

Poster Break

04:00 PM - 05:00 PM

 Panel Discussion: Building the Future: Hiring for AI-Powered Business Analytics in Pharma

More information coming soon!

Speaker: TBD

05:00 PM - 05:10 PM

Day 1 Reflections

05:30 PM - 07:00 PM

Networking Reception

FRIDAY, OCTOBER 4, 2024

07:30 AM - 08:30 AM

Breakfast

08:30 AM - 08:35 AM

Final Day Welcome

08:35 AM - 09:20 AM

 Case Study 1a: AI-Enabled Action Alerts to Enhance Field Effectiveness

In today’s promotional environment, it is critical to arm the field force with actionable recommendations to maximize their time with the right customers focused on the right activities. Through our Action Alerts program, Astellas and Axtria partnered to deliver clear, concise recommendations to the field and create awareness in areas such as Rx Abandonment, Sample Optimization, Team Coordination, and other key areas of rep success. This program took the NBA (Next Best Action) concept, optimized it using AI, and implemented it through practical, easy to understand suggestions to the field, with the goal of increasing Rx uplift, keeping reps focused on the highest potential customers, and changing rep behavior through enhanced engagement and execution of these practical suggestions. This presentation will show how Astellas and Axtria worked together to leverage data, convert it to useful rep suggestions, and ultimately improve brand performance for through better field execution.

Speaker: Steve Bull, Sachit Dwivedi


 Case Study 1b: TBD

How Gen AI can be integrated to perform data transformation and extract key insights out of it.

Speaker: Sriram Ananthakrishna, Jalpeshkumar Chavda

09:20 AM - 09:25 AM

Break

09:25 AM - 10:10 AM

 Breakout 4a: Multi Waypoint Enrichment: An Optimized Approach to Plug Gaps and Enrich Real World Data

More information coming soon!

Speaker: Arindam Paul, Atharv Sharma


 Breakout 4b: Enhancing HCP Behaviour Understanding With Multimodal LLM Profiling For Personalized Outreach

During the session we will presents a methodology leveraging multimodal LLMs to profile HCP behavior for personalized outreach. By fusing structured and unstructured data, the approach provides deeper insights into factors driving HCP decisions, enabling customized targeting for business objectives like understanding declining patient starts or drug adoption trends. The methodology also incorporates LLM-driven agents to interpret patient journeys and HCP timelines, enhancing content relevance. Overall, this framework significantly improves personalized communication strategies, offering actionable insights for marketing and clinical teams to enhance HCP engagement.

Speaker: Prabhu Prakash Kagitha, Maharshi Yeluri

10:10 AM - 10:35 AM

Poster Break

10:35 AM - 11:20 PM

 Breakout 5a: HCP Prioritization - Improvements in Process, Inputs, and Algorithms to Make the Most Accurate Predictions

How should we select the most optimal targets for our pharmaceutical marketing efforts? This session explores one practical solution - figuring out who is likely to prescribe our products. At the core of the solution are machine learning models that find patterns in the data and get an accurate prediction for the future. But as you'll see a practical end-to-end solution requires many more components!

Speaker: Devika Kaushal, Sai Rithvik Kanakamedala


 Breakout 5b: TBD

More information coming soon!

Speaker: Shunmugam Mohan, JP Tsang

11:25 AM - 12:10 PM

 Focus Session: TBD

More information coming soon!

Speaker: Sayan Das, Naga Subramanya Nabha

12:10 PM - 12:20 PM

Closing Reflections