AI is redefining how clinical trials are designed and executed. A major obstacle to complete transformation is tapping into the data that offers novel, well-governed insights. Drawing on the industry’s largest trial operations dataset: schedules of assessment, amendment drivers, trial benchmarks, and site performance trends, Advarra offers a unique, ethically grounded data foundation. Building on this vantage point, the session will share a vision for how AI can transform the drug development lifecycle from end to end, along with real-world applications already shaping the future of trials.
Mike Eckrote
Senior Vice President of Strategic Solutions & Technology
Advarra
Mike Eckrote is Senior Vice President of Strategic Solutions & Technology at Advarra, where he leads efforts to advance innovative approaches to clinical research and development. He brings more than a decade of experience in real-world data, technology solutions, and clinical trial optimization, with leadership roles spanning HealthVerity, Medable, and Medidata Solutions. Throughout his career, Mike has specialized in applying AI/ML, real-world evidence, and data-driven strategies to improve trial design, site selection, and patient outcomes.
Advarra
Website: https://www.advarra.com/
Advarra breaks the silos that impede clinical research, aligning patients, sites, sponsors, and CROs in a connected ecosystem to accelerate trials. Advarra is number one in research review services, a leader in site and sponsor technology, and is trusted by the top 50 global biopharma sponsors, top 20 CROs, and 50,000 site investigators worldwide. Advarra solutions improve collaboration, transparency, and compliance to optimize study design and operations. With unmatched trial operations data, and an ongoing investment in AI innovation, Advarra continues to reimagine what’s possible in clinical research. For more information, visit advarra.com.
The promise of AI in pharma is hindered by fragmented R&D data silos and the infrastructure gap between cloud-native research and on-premise manufacturing. This session presents an architectural blueprint for a unified, hybrid data platform designed to bridge these divides, creating a seamless R&D-to-manufacturing continuum.
We will explore how to first connect R&D data into a powerful knowledge graph. Next, we detail how to compute on this unified data by securely deploying NVIDIA's advanced AI models as microservices within a sovereign cloud environment. Finally, we demonstrate how a true hybrid architecture can bridge the cloud-native lab to the factory floor, unifying CMC and manufacturing data for end-to-end optimization.
Rameez Chatni
Global Director, AI Solutions, Pharmaceutical & Life Sciences
Cloudera
Cloudera
Website: https://www.cloudera.com/
Cloudera is a hybrid platform for data, analytics, and AI. With 100x more data under management than other cloud-only vendors, Cloudera empowers global enterprises to transform data of all types, on any public or private cloud, into valuable, trusted insights. Our open data lakehouse delivers scalable and secure data management with portable cloud-native analytics, enabling customers to bring GenAI models to their data while maintaining privacy and ensuring responsible, reliable AI deployments. The world’s largest brands in financial services, insurance, media, manufacturing, and government rely on Cloudera to use their data to solve what once seemed impossible—today and in the future.
Frédéric Chabot
Head of Corporate Development
MindWalk
Frédéric Chabot is the Head of Corporate Development at MindWalk, focusing on M&A, strategic partnerships, and corporate initiatives. He began working with IPA in 2017, contributing in various roles before assuming his current position. With over 26 years of experience in finance and corporate strategy, he navigates biotech investments and market expansion.
Previously, he served as an International Liaison at Contact Financial, an advisory firm specializing in capital raising and investor relations for TSX and TSX-V listed companies. Over nine years, he worked on investor awareness programs and fundraising initiatives, supporting startups and early-stage companies.
MindWalk
Website: https://www.mindwalkai.com/
MindWalk is a Bio-Native AI company transforming drug discovery and development. Powered by patented HYFT® technology and the LensAI™ platform, MindWalk unifies sequence, structure, function, and literature into a single computational language and closes the loop with an integrated, full-stack wet lab. The platform supports rapid epitope mapping, de novo molecular design, in silico vaccine exploration, and population-scale biologics analytics that help turn insights into validated candidates at speed.
SPOC Proteomics
Website: https://spoc.bio/
SPOC Biosciences’ sensor-integrated proteome on chip (SPOC) synthesizes 192-1152 proteins (full-length, peptides, miniproteins) or antibody (VHH, scFv, Fab) drugs directly on biosensor chips (SPR, MALDI) for library-scale kinetic affinity screening supporting AI-enabled and traditional antibody discovery pipelines. SPOC KinetiKx datasets include on-rate (ka), off-rate (kd), affinity (KD), and residence time (t1/2). SPOC’s proprietary Protein NanoFactory production system utilizes cell-free expression with simultaneous capture-purification directly onto SPR chips, reducing time and cost for library-scale dataset generation compared to traditional recombinant protein workflows. SPOC HyperKinetiKx SPR Product Suite supports antibody drug discovery efforts for affinity ranking (AffiRank), affinity maturation (AffiBoost), epitope binning (EpiScope), epitope mapping (AminoMap) and polyreactivity screening (ReactiScan). SPOC HyperSynaptiKx SPR Product Suite is specifically designed to produce on-demand, large-scale, high-resolution datasets for validation and training in AI-driven drug discovery and development. HyperSynaptiKx SPR assays include lab-in-the-loop services for wet lab testing in DBTL cycles (BuildLoopIQ) and customer-defined antibody vs target library-on-library screening (ContactIQ).
1. Transforming Real-World Data into Structured, Usable Intelligence: Using our enterprise-level RWD ecosystem, Zephyr built PRISM—an AI-enabled clinical inference engine that converts messy, multi-modal patient data into structured, inference-ready patient journeys. PRISM unlocks the full potential of RWD for scalable clinical insights, machine learning development, and validation.
2. Multi-Modal AI for Predictive Modeling and Expression Reconstruction: Zephyr’s AI models predict drug response and reconstruct gene expression from clinically available inputs such as NGS data from commercial LDTs and whole-slide images (WSI). These capabilities enable retrospective validation of treatment predictions across oncology, linking molecular and clinical outcomes in real-world settings.
3. Partner-Ready Software for Rapid Co-Development and Clinical Integration: Zephyr’s foundation models can be fine-tuned for new assets, diagnostics, or therapeutic areas using partner data—delivering bespoke, AI solutions that integrate as software directly into existing R&D and clinical workflows. Our infrastructure also supports rapid clinical intelligence queries and cohorting, empowering data-driven decision-making from discovery through commercialization.
Zephyr AI
Website: https://www.zephyrai.bio/
Zephyr AI is a precision-medicine company unifying enterprise-scale real-world data with multi-modal AI to deliver actionable, biologically interpretable insights across the therapeutic lifecycle—from discovery to clinical deployment. Our software-native, AI-enabled modules predict drug response and reconstruct gene-expression signatures from clinically available DNA-based inputs and drug metadata, and can be fine-tuned to novel therapeutics or diagnostics. Pilots stand up in weeks, informing patient stratification, trial optimization, label expansion, and indication discovery.
PRISM, our SOC 2/HIPAA-aligned data and compute infrastructure, powers rapid cohort construction, synthetic control arms, and real-world validation with intervention-specific risk modeling. Through Aster Insights™ and the ORIEN Total Cancer Care® study, Zephyr provides access to deeply annotated oncology assets—lifetime-consented patients with linked clinical, exome, transcriptome, and whole-slide imaging—to enable fit-for-purpose data generation. We partner with biopharma, diagnostics, and digital-pathology leaders, integrating seamlessly into existing workflows with no new assays required. Together with a rigorous validation engine grounded in real-world outcomes, Zephyr bridges experimental and clinical domains to extract signal from heterogeneous data, de-risk development, and bring effective therapies to patients sooner. Our mission is to make precision medicine accessible and immediate—turning fragmented data into confident, patient-impacting decisions at scale.
Data powers the engine of artificial intelligence (AI), but not all data is created equal. While software capabilities are rapidly accelerating, the biopharma industry still largely lacks the intelligent hardware needed to generate clean, contextualized, and high-quality data that AI and machine learning (ML) models require to deliver on their promise.
Explore how today’s in silico process development tools for bioreactor scaling and mechanistic modeling of chromatography can help you get it right the first time now, and why the next generation of intelligent hardware will be critical to unlocking the full potential of AI/ML in biopharma.
Tobias Hahn, PhD
R&D Director, GoSilico
Cytiva
Tobias Hahn is R&D Director of chromatography mechanistic modeling activities at Cytiva. As former co-founder and CEO of GoSilico, now part of Cytiva, Tobias is responsible for delivering simulation software and workflows for in silico process development. He received his undergraduate education in computational mathematics and technical physics in Karlsruhe and Stockholm, earning his PhD in chemical engineering from Karlsruhe Institute of Technology (KIT). During his doctoral studies, he utilized his background in mathematics and software engineering to create the simulation software now known as GoSilico™ chromatography modeling software.
Cilon Li
Sr. Director of Engineering, Digital Products Development
Cytiva
Cilon Li is a digital and IT executive with over 15 years of experience in healthcare and biopharma. He is a strategic leader with a proven track record in driving digital transformation across supply chain management, product management, and R&D. At Cytiva, Cilon drives the company’s digital strategy and expanding product portfolio, encompassing Internet of Things (IoT), data analytics, AI/ML, software as a service (SaaS) and enterprise applications to help customers progress their digital biomanufacturing journeys.
Cytiva
Website: https://www.cytivalifesciences.com/about-us
Cytiva is a global life sciences leader dedicated to helping customers discover and commercialize the next generation of therapeutics. Together, we bring dedicated technical expertise and a broad portfolio of tools and technologies that enable the development, manufacture, and delivery of transformative medicines to patients. Visit cytiva.com to learn more.