Max Liu
Senior Software Engineer - Early Science
AstraZeneca
Cathy Lui
Partner
Orrick
Mark Kiel
Chief Science Officer
Genomenon
The promise of AI in science depends not only on powerful models, but on the ability to connect fragmented systems and harmonize diverse data sources. Today’s laboratories face significant challenges: siloed infrastructures, inconsistent data formats, and AI tools that cannot easily work together. This presentation examines how interoperability—across data, platforms, and AI agents—is the key to unlocking scale. We will explore strategies such as adopting open standards, building modular architectures, and enabling AI-to-AI collaboration to ensure data and tools flow seamlessly across disciplines. By creating FAIR, AI-ready data environments and fostering connected ecosystems, we can transform scientific workflows into integrated, predictive, and collaborative systems. The result: smarter labs, faster science, and breakthroughs that accelerate discovery.
Wolfgang Colsman
Founder & CEO
ZONTAL
With nearly 30 years of visionary leadership, Wolfgang Colsman serves as the Chief Executive Officer of ZONTAL, a pioneering enterprise platform transforming the way organizations manage and preserve their digital information. Under his leadership, ZONTAL has become a catalyst for change across industries, redefining how data is captured, connected, and safeguarded for long-term value.
Before founding ZONTAL, Wolfgang spent over two decades at OSTHUS as Chief Innovation Officer and Chief Technology Officer, where he guided large-scale digital transformation initiatives. His ability to bridge cutting-edge technology with real-world business needs helped establish OSTHUS as a trusted, vendor-agnostic partner driving innovation for global enterprises.
Beyond his corporate achievements, Wolfgang has left a lasting mark on the life sciences and technology ecosystems through his leadership at the Allotrope Foundation and the Pistoia Alliance Methods Hub project. By championing data standards, interoperability, and collaborative infrastructures, he has empowered industries to break down silos, accelerate discovery, and unlock new opportunities for digital transformation. These efforts continue to shape how organizations think about data as a strategic asset rather than a byproduct.
Recognized for his ability to anticipate technological shifts and inspire collaborative progress, Wolfgang has become a respected voice in the digital landscape—bringing together vision, strategy, and execution to create sustainable impact.
ZONTAL
Website: https://zontal.io/
ZONTAL provides the premier data platform tailored for the life science industry. Our platform is at the forefront of digital transformation, delivering innovative solutions that address the intricate challenges faced by large-scale enterprises. Our services streamline IT processes, facilitate the integration of AI/ML applications, accelerate product time-to-market, and enhance regulatory compliance.
With a global presence encompassing the US, Europe, and Asia, ZONTAL is well positioned to offer seamless support to our clients worldwide. Our network of dedicated integration and service partners enables us to deliver our expertise and solutions in any country and across all time zones, ensuring our customers receive unparalleled support wherever they are.
- Learn how AI models enhance physics-based simulations to predict molecular interactions and optimize drug design.
- Discover the synergy between machine learning and classical methods to accelerate screening and improve the accuracy of drug discovery.
Sreyoshi Sur
Former Scientist, Molecular Engineering & Modeling
Moderna
Tarun Walia
Senior Director, Decision Science
Novo Nordisk
JC Pan
VP, Cloud Supply Chain Sourcing
Microsoft
JC Pan leads Cloud Sourcing, Sustainability, and Security (CS3) at Microsoft, where he oversees the sourcing and supply chain for cloud hardware and services—critical to Microsoft’s role as a global cloud service provider. A recognized expert in supply chain operations, JC Pan has been with Microsoft for seven years, during which his strategic leadership has been instrumental in navigating complex challenges and advancing the company’s supply chain capabilities.
Before joining Microsoft, he spent eight years at Dell, driving supply chain strategy and transformation, and previously served as a project lead at McKinsey & Company for three years, bringing deep consulting experience to his operational leadership.
How the partnership between people and AI can elevate efficiency and reduce friction in payment integrity.
Prasanna Ganesan
CEO
Machinify
Machinify
Website: https://www.machinify.com/
Machinify is redefining payment integrity with AI-powered solutions designed to be frictionless, intelligent, and future-ready. Trusted by over 60 health plans, Machinify simplifies the complexity of healthcare claims with a platform that coordinates, validates, and pays claims with precision. Backed by cutting-edge technology and healthcare expertise, Machinify delivers cost savings, operational clarity, and strategic insight—empowering payers to take full control of their payment operations.
Machinify Solutions
Machinify offers a unified platform for payment integrity, combining pre-pay and post-pay solutions to detect, prevent, and resolve improper payments across the claim lifecycle.
- Pre-Pay Adjudication & Accuracy: Automatically identify potential errors or duplications before claims are paid, reducing downstream recovery efforts.
- Post-Pay Analytics & Recovery: Leverage advanced AI to uncover patterns, prioritize audits, and streamline recovery with high accuracy and minimal friction.
- Audit & SIU Support: Equip Special Investigation Units and audit teams with AI-enhanced tools to detect fraud, waste, and abuse faster and more effectively.
- Configurable, Modular Platform: Tailored to integrate into existing workflows with flexibility and speed, enabling rapid value without disruption.
Machinify’s intelligent platform unifies fragmented payment integrity processes, empowering payers to reduce costs, increase efficiency, and improve payment accuracy at scale.