WEDNESDAY, OCTOBER 23, 2019 |
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08:50 AM - 09:00 AM |
Welcome from PMSA |
09:00 AM - 10:00 AM |
Keynote Speaker: Marco Giannitrapani, Head of AI & Predictive Analytics Finance, Novartis |
10:00 AM - 10:45 AM |
Leveraging Geographic Features in Predictive Modeling with Panorama Speaker: Jean-Patrick Tsang, Bayser |
10:45 AM - 11:00 AM |
Break |
11:00 AM - 11:45 AM |
A Simple Process of Using Regression to Estimate Individual Physician Valuation from Brick-Level Data Speaker: David Wood, Axtria |
11:45 AM - 12:30 PM |
How Can Data Scientists Survive Under Data Protection Restrictions? – GDPR, CCPA and Beyond Speaker: Jessica Santos, Kantar Health |
12:30 PM - 01:30 PM |
Lunch |
01:30 PM - 02:15 PM |
Personalized Marketing, Personas, Predictive Analytics Speaker: Igor Rudychev, AstraZeneca |
02:15 PM - 03:00 PM |
EU KOL Analytics and Challenges Learn how real-time profile information helps drive launch and commercialization strategies. Hear best practices for identifying, researching, and informing interactions with scientific experts. Speaker: Kilian Weiss, Veeva |
03:00 PM - 03:15 PM |
Break |
03:15 PM - 04:00 PM |
Using an Evidence-Based Approach to Multi-Channel Marketing (MCM) Optimization The explosion of numerous promotional and communication channels raises many questions regarding optimizing channel investment. More importantly, it has become critical to identify which channels to use across various HCPs (e.g. office-based GP and specialists, hospital-based specialists) and across product portfolios (inline/mature vs. newly launched brands). An evidence-based approach is needed to make both strategic and tactical decisions with confidence. While there are multiple ways to evaluate multi-channel promotional effectiveness, a focus on the aggregated impact of channels on sales is the key to measuring ROI. Going a level deeper, linking HCP level promotional activities with the most granular HCP/segment sales data available in EU in accordance with data privacy laws can help uncover how different promotional activities impact various segments over time. Using a customized advanced analytics approach to quantify impact in a robust and accurate manner can yield previously unrealized HCP/segment-level insights, recommendations and optimization. Once in place, the model new data is periodically evaluated providing sustainable channel optimization and fine-tuning. Speaker: Mario Müller, Associate Director, Data Science, IQVIA |
04:00 PM - 04:45 PM |
Roundtable Discussion: Taking EU Data to the Next Level: From Data Issues to Data Modeling: New Generation of EU Data Moderator: Jean-Patrick Tsang, Bayser Panelists: Valerie Alleger, Bayer; Manuel Ackermann, Novartis; Christy Gaughan, Roche; Igor Rudychev, AstraZeneca |
04:45 PM - 05:30 PM |
Using AI and Machine Learning to Help Drive Patient-Centric Brand Management in the EU Given the increasing importance of patient centricity, it has become paramount for brand managers to incorporate patient-centric approaches as part of brand strategy. To better understand drivers of brand performance and market potential, approaches that combine social media channels, anonymized longitudinal patient level data and AI/machine learning techniques can uncover brand strengths and growth barriers while quantifying the value of each patient segment. This abstract investigates patient journey, initiation drivers, socio-demographic variables, co-medication and side effects as determinants of brand success. We also examine similarities across patient profiles at various stages in the patient journey, the impact of various treatments and how to cluster patients. Finally, a deeper look at patient lifetime value assessments can indicate brand priority areas and patient upside potential. Speaker: Agnieszka Wolk, Ph. D, Senior Director, Data Science, IQVIA |
06:00 PM - 08:00 PM |
Reception |
THURSDAY, OCTOBER 24, 2019 |
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08:45 AM - 09:00 AM |
Welcome |
09:45 AM - 10:30 AM |
Understanding the Voice of the Patient in Two Case Studies: Rare Diseases and Parents as Caregivers & Applying Machine Learning to Social Media Speakers: Ben Collins, Boehringer Ingelheim; Anne Bichteler, Semalytix |
10:30 AM - 10:45 AM |
Break |
10:45 AM - 11:30 AM |
A Driverless Alternative to Pharma Forecasting Speakers: PKS Prakash, ZS; Priyanka Halder, ZS |
11:30 AM - 12:15 PM |
Assessing and Improving Brand Perception through Social Intelligence Speaker: Jeff Wray, Decision Resources Group |
12:15 AM - 01:00 PM |
Lunch |
01:00 PM - 01:45 PM |
Panel Discussion: Taking EU Analytics to the Next Level: Analytics Approaches Using New Generation of EU Data Moderator: Christy Gaughan, Roche Panelists: Ben Collins, Boehringer Ingelheim; Jason Carlin, Novartis; Catherine Bolliet, Roche |
01:45 AM - 02:00 PM |
Break |
02:00 AM - 02:45 PM |
Future of Health Trends Speaker: Fabio Sergio, Fjord |
02:45 AM - 03:30 PM |
Analytics Translators in Pharma Speakers: Alex Davidson, McKinsey; Karl Goossens, QuantumBlack |
03:30 PM - 04:00 PM |
AI in Pharma Commercial – The Challenge of Context The challenge of useful application of AI in a large variety of fields has to do with understanding of context. Richness and openness of context distinguishes areas of as-of-yet limited success of AI in comparison with applications like image recognition and game-playing. In the world of commercial pharma the problem is multiplied by manifold. For a CRM system there are TWO customers – the sales representative and the physician, or THREE if one counts the patient. That means that three contexts have to ‘merge’ to make for successful interactions, and each of these is complex by itself. We exemplify AI’s context challenge and highlight the key success factors for dealing with it using a two case-studies involving making useful & personalized suggestions for communications between sales representatives and HCPs. In one case the emphasis is on the communications channel, in the second the focus is on contents. In each case we show the key elements of context and explain how they are tracked and used. The use cases provide a useful illustration of what AI really means – what a well-rounded AI applications addressing a complex business problem should consist in, and it illustrates the need to go well-beyond Machine- or Deep-Learning alone. Speaker: Pini Ben-Or, Chief Science Officer, Aktana |
04:00 PM - 04:30 PM |
Wrap Up |