Medidata NEXT NY 2026 Event Brief
The life sciences industry is navigating a period of continuous disruption driven by scientific complexity, operational pressure, regulatory modernization, and the rapid rise of AI powered technologies. These forces are reshaping how therapies and medical devices are discovered, developed, manufactured, and delivered. Organizations are being pushed to move from siloed systems to unified experiences, adopting future ready infrastructure and operating with lifecycle intelligence rather than transactional processes.
At NEXT New York 2026, I had the privilege to sit down with:
- Anthony Costello, Chief Executive Officer, Medidata
- Lisa Moneymaker, Chief Strategy Officer, Medidata
- Wayne Walker, SVP, Head of Data Experience, Medidata
- Tom Doyle Chief Technology Officer, Medidata
- Patrick Johnson Executive VP, Research and Development, Dassault Systèmes
Across these conversations, a unified narrative emerged: Dassault Systèmes and Medidata are aligning their strategies to redefine the Life Sciences lifecycle through unified data, virtual twins, and an expanding family of AI agents.
A Sector Under Pressure and in Transition
Source: Axendia, Inc.
Life Science companies are being pushed to move beyond episodic transformation and adopt continuous evolution supported by future ready infrastructure capable of handling accelerated development cycles and rising expectations for transparency and trust.
Costello offered a candid assessment of the structural challenges facing the industry.
“It is a complex ecosystem… molecular discovery, patient regulation, virtual twins of factory processes, all of it is so far apart from each other and on different platforms.”
He emphasized the need for modernization without disruption: “We have built an industry on decades of acquisitions, legacy systems, and specialized tools… The question is how we make it all feel unified without forcing anyone to re-platform.”
Fragmentation across discovery, development, manufacturing, and regulatory domains is no longer sustainable. Meaningful connectivity becomes the natural next step.
Connectivity as the Foundation for Transformation
Fragmented technology landscapes shaped by decades of acquisitions, point solutions, and bespoke integrations continue to limit visibility and slow innovation.
Connectivity has become a strategic imperative, enabling organizations to move from data to intelligence and achieve end to end continuity across discovery, development, manufacturing, and quality. Harmonization is no longer optional; it is the foundation for lifecycle intelligence.
Source: Axendia, Inc.
Johnson described connectivity as the most immediate and impactful opportunity for transformation: “The low hanging fruit is really the connectivity between the different solutions, Biovia tying into Medidata, tying into Delmia with OneLab, tying into Enovia for quality.” He emphasized that connectivity unlocks deeper lifecycle understanding. “Once you connect and once you can model the situation, what I call the 360-degree understanding, you move from simply optimizing processes to elevating the entire industrial asset.”
Connectivity establishes the foundation for the shift from static digital representations to dynamic virtual models that support exploration and prediction.
From Digital to Virtual: The Evolution of the TWIN Paradigm
The shift from digital to virtual reflects the industry’s move toward context rich, model driven environments that support exploration, prediction, and optimization. Virtual twins are emerging as the backbone of the virtual plus real enterprise, where real world operations and virtual models continuously inform each other to drive resilience, speed, and quality.
Source: Axendia, Inc.
Johnson explained the distinction clearly: “A digital twin is just a replica of an instant photograph of a situation. A virtual twin lets you do what if, so you can explore… It is about all the potentials.”
Simulation is becoming a powerful accelerator, enabling organizations to reduce reliance on traditional models, compress timelines, and improve predictability. Moneymaker noted the regulatory momentum: “We have already done a lot within silico trials… We even have some FDA approval and partnership with them around that.”
Walker extended this vision into a future where digital twins of patients reshape development: “If clinical research was a new discipline today… we would be developing digital twins of patients and running therapeutics through them to see how they respond.”
Simulation lays the groundwork for the next leap: intelligence that acts in context.
AI Agents as the New Operating Layer
AI agents represent a shift toward context engineering, systems that understand roles, tasks, and intent, and deliver insights in the flow of work. Instead of navigating siloed platforms, users will increasingly rely on role aware, domain specific agents that orchestrate actions across the lifecycle. This marks a transition from system centric to intelligence centric operations.
To underscore how transformative this model will be for users, Johnson framed the agents not as tools but as collaborators: “Each agent has its own personality, its own strengths, its own domain of expertise… almost like virtual colleagues you can rely on.”
Source: Axendia, Inc.
Costello emphasized that agents make complexity invisible: “With Aura, Leo, Marie, and DOT working together, customers will be able to ask a question and get an answer without navigating the underlying systems.”
Together, they form a coordinated layer of virtual colleagues that support users across the lifecycle.
Agents also serve as the practical mechanism for harmonization, bridging systems, data, and workflows without requiring users to understand the underlying architecture. They reduce cognitive load and system friction, allowing teams to focus on decisions rather than navigation. And as operations scale, agents become essential rather than optional, enabling organizations to operate with speed, consistency, and intelligence across the lifecycle.
Johnson reinforced the shift toward knowledge driven intelligence: “We are transitioning from an API paradigm to a knowledge and know how protocol exchange.”
Continous Innovation: The New Normal
Organizations can no longer rely on multi-year implementations or static operating models. The pace of change demands a shift from episodic change to continuous evolution, supported by infrastructures and cultures that enable ongoing adaptation, rapid iteration, and operational resilience.
Walker was direct about the shift required: “There are no longer going to be projects or implementations that take 18 months. It is going to be continual change.” He also addressed cultural resistance: “There is one way AI will take your job, and that is if you do not get on board.”
Sustaining continuous innovation requires trustworthy, interoperable data that can support reliable insights and intelligent automation.
Data Quality, Interoperability, and Trustworthiness
Data remains the industry’s most valuable and most underutilized asset. Data trustworthiness and interoperability are now foundational requirements for lifecycle intelligence. Without harmonized, high quality data, AI systems cannot deliver reliable insights, and organizations cannot move from insight to action.
Moneymaker reinforced the need for trustworthy data foundations: “We can interrogate the data much more holistically… but fundamentally, we cannot invent people that were not there.”
Walker echoed the risks of poor governance: “I do not trust the quality of the data that I have… Governance, master data management, and trustworthiness are the biggest barriers.”
Improving data quality also strengthens the industry’s ability to address persistent challenges in patient experience, site burden, and diversity.
Patient Centricity and Diversity
Improving patient experience, reducing site burden, and expanding representation are essential to building inclusive, resilient clinical ecosystems. Technology must enable, not overwhelm, patients, investigators, and care teams while supporting more personalized and equitable participation.
Source: Axendia, Inc.
Moneymaker emphasized the operational barriers that limit diversity: “A lot of the diversity profile we are chasing lives in localized centers that have historically avoided clinical trials because of the burden.” She reinforced the need for better representation and data completeness: “We cannot invent people who were not there… We have to understand what is missing and how we capture that data going forward.”
Addressing these challenges requires a unified experience that brings insights, actions, and workflows together across the lifecycle.
Toward a Unified Experience Across the Lifecycle
The industry is shifting from siloed systems to unified experiences, where intelligence orchestrates insights and actions across the lifecycle. Achieving this requires more than platform consolidation; it demands agent driven orchestration that unifies insights, actions, and workflows across domains. The future enterprise will be defined not by a single interface, but by a coordinated, intelligence powered operating layer.
Walker described this unified experience as a single, insight driven environment:
“Ultimately, what we will get to is one single experience, a clinical research platform… giving you insights into what you need to know and the tools to act quickly.”
Johnson connected this directly to agent orchestration: “Agents will not just answer questions; they will coordinate across systems… They will be the connective tissue that brings the entire platform together.”
Together, these themes point to a future where intelligence, connectivity, and harmonization redefine how life sciences organizations operate and innovate.
In Brief
NEXT New York 2026 offered a clear view into how Dassault Systèmes and Medidata are shaping the future of the life sciences lifecycle. The event highlighted the urgency of unifying data, the shift from digital to virtual models, the rise of intelligent agents, and the operational pressures reshaping development and delivery.
Lifecycle success will depend on connected data foundations, context aware intelligence, and harmonized experiences that reduce friction across discovery, development, manufacturing, and clinical operations.
Organizations that modernize their data foundations and embrace intelligence driven operations will be positioned to convert complexity into clarity and disruption into advantage.
We will continue to provide updates on Medidata and Dassault Systèmes as they become available.
To discuss how this initiative impacts your organization, click on this link to schedule an Analyst Inquiry on this topic.
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The opinions and analysis expressed in this post reflect the judgment of Axendia at the time of publication and are subject to change without notice. Information contained in this post is current as of publication date. Information cited is not warranted by Axendia but has been obtained through a valid research methodology. This post is not intended to endorse any company or product and should not be attributed as such.