2019 European Summit

European Summit • Basel, Switzerland • October 23-24

Summit Sponsors


08:50 AM - 09:00 AM

Welcome from PMSA

09:00 AM - 10:00 AM


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


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


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


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



08:45 AM - 09:00 AM


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


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


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


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