Agenda

In this way, artificial intelligence (AI) systems are finding more and more niches in which they can improve our capabilities not only physically but also intellectually. In recent years, we focussed on a systematic collection o data to get a deep understanding of biological entities and the relations among them. Starting with the classification and current developments in the field of AI, this talk will give an overview how the data collected, curated and employed. In specific, how such data can used to develop practical applications for biological sequence analyses, how to combine multiple data modalities to identify disease-causing biomarkers, and how to develop explainable application for drug repurposing and repositioning.

David Alderman, President & CEO of Molekule Consulting, a keen observer of these market currents, will compellingly argue that sustained competitive advantage hinges not solely on algorithmic power, but on mastering the enduring art of Human Intelligence (HUMINT). This we define as the strategic collection, interpretation, and dissemination of human-sourced insights to understand motivations, anticipate actions, and navigate complex relationships. Where AI adeptly charts past trends and may code the future, the HUMINT “Algorithm” navigates the present and anticipates the future by decoding the unspoken concerns of regulators, the subtle below-the-radar maneuvers of competitors, and the cultural nuances defining success in diverse global markets. Molekule Consulting, leveraging its deep expertise across the globe, will reveal why a purely data-centric approach, for all its analytical prowess, risks overlooking crucial human factors – a decisively risky blind spot in a market driven by human decisions. They will champion HUMINT as an indispensable, often underestimated, guide for navigating biopharma’s complex landscape, offering actionable strategies to assert market leadership. Because, ultimately, even in the data-rich world of biopharma, it’s the human element that remains decidedly… pivotal. Join us to discover how to gain a decisive edge by embracing the human factor, and learn how HUMINT can be applied to achieve success not just in Europe biopharma, but worldwide.

Salvador Carlucci, whose landmark 2005 Nature Biotechnology articles reshaped how biotech approached competitive intelligence, unveils the dramatic evolution of CI in the age of artificial intelligence. This provocative session bridges his original framework with cutting-edge AI capabilities, revealing unexpected synergies and disruptive opportunities. Discover how today’s most forward-thinking pharma companies are supercharging their CI methodology—from intelligence gathering to strategic decision-making—through sophisticated Agentic AI integration.

This presentation will delve into how AI and ML technologies are redefining data collection and analysis to accelerate insights, improve precision, and ensure global accessibility.
Key discussions explore AI’s role in enhancing data collection, streamlining panel recruitment, and ensuring global compliance while enabling data-driven decision-making in healthcare. A spotlight is placed on real-world applications, including oncology research, showcasing improved patient care and outcomes. Insights into AI’s potential to address geographical and behavioral constraints emphasize its role in ensuring access to underserved regions.
The revolutionize healthcare insights, underlining Borderless Access’ commitment to innovation and ethical data practices and the journey toward a data-driven healthcare future.

Forecasters often rely on secondary data analogs to model the effects of timing and order-of- entry, but these estimates often fail to capture the unique characteristics and market situation for pipeline products. This presentation shares new tools for modeling timing and order-of-entry that combine methods based on secondary data with new metrics from survey-based demand research. Accuracy of the methodology is demonstrated with several case studies.

b) Where to start – Building Cross-Functional Teams: Collaborative war gaming thrives when R&D, regulatory, marketing, and CI teams work together. This integration helps simulate a competitor’s behavior and anticipate market shifts from multiple angles.
c) How does this work? Red Team vs. Blue Team Dynamics: A core element of war gaming involves having a “Red Team” play as the competitor and a “Blue Team” as your organization. This dual perspective ensures all possible outcomes are considered and prepared for.
d) Data-Driven Simulations, a way to enhance war -gaming: Integrating real-world data such as patents, market research, and regulatory filings—combined with AI and machine learning—creates simulations that reflect potential market scenarios with high fidelity.
e) How Do You Prepare for High-Stakes Decision-Making?:Real-time exercises preparing teams to make critical decisions under pressure, building the adaptability needed for sudden market shifts.
f) Continuous Improvement through Post-Game Analysis: After each simulation, detailed debriefs help teams identify strengths and areas for improvement. This process creates a living playbook that evolves, preparing your team for future challenges.
g) Real-life case studies- either by presenting my own or involve the audience.

b) The Social Media Dilemma: Monitoring competitors’ social media can offer critical insights, but it also raises questions about privacy and ethics. Where should we draw the line?

c) Avoiding the Espionage Trap: CI in a heavily regulated sector can veer into dangerous territory if not handled with care. How can organizations ensure that their CI efforts remain on the right side of the law and ethics? Given the musical chair within the industry, at times “secret sauce” might be share unintentionally.

d) Creating Ethical CI Frameworks: The key is to develop a transparent yet impactful CI strategy that provides actionable insights while maintaining high ethical standards.

AI and advanced data techniques help transform raw data into actionable intelligence, guiding better treatment strategies and innovations.

In this presentation, you will learn:
How does AI enhance data enrichment in rare diseases?
What are the challenges in combining lab and real-world data?
How do P&I techniques turn raw data into clinical use?
Why is data quality crucial for rare disease outcomes?