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All attendees are cordially invited to the Pistoia Alliance Sponsored Welcome Drinks Reception and Pre-Registration in the Grand Ballroom Pre-Function Area. A unique opportunity to network and collect your badge before the rush!
Nicole Crane is a Senior Principal with Accenture’s Labs group. She is a thought leader within Accenture’s Research and Labs practices and steers lab innovations, including those driven by agentic AI. She has 15+ years of work experience in the Life Sciences, specializing in R&D processes and technologies. She gained her experience working with various industries, including Pharma, Healthcare, Government, and academia. In her time before Accenture, Nicole spent more than a decade as an R&D Scientist, with both deep and broad experience in benchtop, analytical, pre-clinical, and clinical research.
Mark Fish is the Vice President & General Manager of Digital Lab Solutions at Thermo Fisher Scientific. Mark’s role focuses on the innovation and execution of Thermo Fisher’s Automated Digital Lab Solutions portfolio, as we enable our customers to reimagine their laboratory processes with leading-edge digital, laboratory and automation capabilities. With over 20 years of laboratory informatics experience, Mark has focused on building long-term, trusting customer relationships, and delivering valuable, strategic solutions to address industry challenges. Throughout his career, Mark has held significant positions at Thermo Fisher Scientific, Accenture, Brooks Life Sciences, and Brooks Automation. With his extensive experience, Mark has developed a deep understanding in the laboratory informatics and laboratory automation spaces.
At last year’s Congress, I outlined the data ecosystem required for the Lab of the Future; this year, I will update our progress toward an integrated Lab of Tomorrow built on AI and digitalization, data, automation, and talent. I will present examples, including agentic AI for target identification and validation, generative molecular design, and a unified de novo discovery platform, as well as the automated discovery engine we are building to advance programs, while continuously improving our models. Finally, I will describe how we have moved beyond pilots to scale AI across the organization, supported by dashboards that track measurable impact.
Dave Dorsett brings over 30 years of experience in R&D informatics within the global pharmaceutical, chemical, and consumer goods industries. He has a proven track record of architecting, designing, and delivering both commercial and in-house informatics solutions across the entire R&D spectrum, from early research through late-stage development and manufacturing.
SAFe and Scrum Product Manager with 19+ years of biotech industry experience in product management and analytical method development, qualification, and validation. Business owner who deployed and maintained numerous validated platforms ranging between 200-1800 users. Designed and implemented an instrument data capture product as custom code which was then converted to vendor core product supporting file-based, serial and chromatography data system instruments across Process Development. SAFe epic owner for Attribute sciences responsible for developing requirements, communication, and training for over 300 users.
Marc is a Lead Product Manager for Process Development at IDBS. Prior to that role, he was a Director of Strategic Solutions, developing the enterprise-level IDBS Polar BioPharma Lifecycle Management solutions. With over 15 years of experience working in the pharmaceutical sector implementing and leading digital solutions and strategies, Marc is an expert in laboratory and operational technology, laboratory informatics and system integration and leads a team of technological and domain experts committed to the development of Polar Solutions. Before joining IDBS in 2021, he worked at Lonza Biologics and Angel Biotechnology, and holds a BSc (Hons) in Pharmacology from the University of Sunderland.
Dave Dorsett brings over 30 years of experience in R&D informatics within the global pharmaceutical, chemical, and consumer goods industries. He has a proven track record of architecting, designing, and delivering both commercial and in-house informatics solutions across the entire R&D spectrum, from early research through late-stage development and manufacturing.
This talk will examine how data is generated today and how it is expected to evolve in the near and far future. It will highlight what is currently working, outline key challenges, and explain why in silico-only experimentation is not yet mature due to data gaps, as well as discuss approaches to address and refine these gaps.
Turning lab data into iterative decisions and reliable actions. A scalable autonomy playbook: how to move from “self-driving lab” concepts to self-driving operations that consistently deliver cycle-time and productivity gains. The closed-loop model that makes it real: turning lab data into repeatable decisions and next-step execution (with clear human decision points and escalation paths). Trust at scale: the minimum governance required—traceability, auditability, and control—so autonomy accelerates output without increasing risk or rework.
Autonomous laboratories are rapidly moving from vision to operational reality—and reshaping competitive advantage in life sciences R&D. In this session, Ginkgo Bioworks founder and CEO Reshma Shetty explains the difference between autonomous labs and traditional lab automation workcells. Drawing on real deployments, including collaborations with OpenAI and Pacific Northwest National Laboratory, she will highlight how to deploy, scale, and extract value from autonomous labs—along with the strategic and technical hurdles to overcome in building next-generation R&D infrastructure.
Reshma Shetty co-founded Ginkgo Bioworks in 2008. Reshma has been active in the field of synthetic biology for nearly over 20 years, co-organizing the first international conference in the field in 2004. In 2008, Forbes magazine named Reshma one of Eight People Inventing the Future and in 2011, Fast Company named her one of 100 Most Creative People in Business. In 2014, Ginkgo became the first biotech company to participate in YCombinator. In 2018, Business Insider named her one of the most powerful female engineers. In 2019, BIO recognized Reshma with the Rosalind Franklin Award for Leadership in Industrial Biotechnology and Agriculture. In 2021, Ginkgo Bioworks became a publicly traded company on the NYSE with the stock ticker DNA. Reshma was a member of the U.S. Department of Defense’s Defense Science Board from 2022-2025. Reshma Shetty has a B.S. degree in Computer Science from the University of Utah and a Ph.D. in Biological Engineering from MIT.
Maintain reliability with high-fidelity ML models for property prediction and retrosynthesis in fast moving design environments. Bridge the gap between dry-lab modeling and wet-lab execution to ensure that models drive decisions. Compress the design make test analyze cycles through seamless integration of predictive analytics
Karl Leswing is the Vice President for Machine Learning at Schrödinger. In this role, he oversees the research and execution of machine learning applications for Schrödinger’s digital chemistry platform. In 2017, he was a visiting researcher at the Pande Lab, working on using deep learning techniques for drug discovery. During that time, he co-authored MoleculeNet, a benchmarking paper analyzing machine learning techniques for chemoinformatics. Karl received his undergraduate degree from the University of Virginia and a Master’s in machine learning from Georgia Tech.
This talk will outline why a context-graph-driven workflow management approach is required to coordinate, collect, and contextualize data across scientists, software systems, robots—including instruments, liquid handlers, and process equipment—and AI agents. It will also explain why an integrated data and knowledge management system, supported by ontologies, is a prerequisite for integrating AI into life science CMC workflows.
Shruti Vij is the Director of Innovation and AI Strategy at RDU IT, leading the shift from incremental optimization to horizon oriented solutions and embedding innovation as a strategic capability to shape the enterprise roadmap. Partnering across science, technology, and the business, she designs and scales AI enabled platforms and operating models that accelerate discovery, de risk decision making, and unlock new value at both portfolio and program levels while preparing organizations for what’s next.
She brings a cross functional trajectory spanning engineering, imaging, product strategy, and applied data science across the value chain. Previously, she developed clinical decision support and digital health solutions at Philips Healthcare, applied product strategy to AI driven solutions at PerigonAI and led data science for cell therapy process development at Takeda. Her rigorous academic foundation and hands on clinical translational research coupled with business acumen shaped by growing up in a family owned enterprise equip her to lead change with a distinctive, outcomes focused perspective.
Vasu Rangadass, Ph.D., is the Founder and Strategy Officer at L7 Informatics, Inc., a leader in life sciences workflow and data management.
Previously, Dr. Rangadass was the Chief Strategy Officer at NantHealth, following its acquisition of Net.Orange, the company he founded, to provide an enterprise-wide platform to simplify and optimize care delivery processes in health systems.
Before Net.Orange, Vasu was the first employee of i2 Technologies (currently Blue Yonder), which later grew to be a global company
An ecosystem-driven ELN is key to realizing the full value of Sapio ELaiN’s co-scientist capabilities. By integrating specialist informatics and domain-specific applications directly into the scientific workflow, ELaiN allows researchers to use trusted, validated tools without switching systems or duplicating effort, while preserving a single experimental record. This talk highlights a live use case with OpenEye, Cadence Molecular Sciences, showing how integrated cheminformatics and molecular modeling within ELaiN enable more efficient, reproducible, and insight-driven ligand- and structure-based discovery.
PhD scientist with a degree in computational chemistry with a publication record for the early-stage discovery and design of potential drug candidates targeting Gram-negative bacterial pathogens. Also, a record of demonstrating to scientists, sales representatives, and business professionals the value of science-based software solutions to improve productivity, accelerate discovery, reduce time to market, and lower costs.
I’m a technology-driven product leader with deep expertise in AI, informatics, and digital solutions for life sciences R&D. With a strong foundation in chemistry, biology, and neuroscience, I’ve built my career at the intersection of science and technology—moving from bench research to product management, marketing, sales, and IT leadership. I believe software product management is a career, not just a role on a Scrum team. Success in this space requires a blend of strategic vision, technical fluency, and customer empathy. The skills I’ve developed—bridging science, technology, and business—are not only critical in life sciences but also highly transferable across industries. My focus remains on leveraging AI and digital innovation to drive meaningful impact in complex, data-driven environments.
JG Brasier is a Senior Data Scientist in the Data Strategy and Solutions team at Vertex Pharmaceuticals. He designs algorithms that leverage cutting-edge AI and Machine Learning technologies to solve complex business critical problems. He has previously developed custom solutions for manufacturing, quality, and supply chain teams and has extensive experience with dealing with QMS and RIM data. Prior to joining Vertex, JG was a Data Scientist at Moderna where he was the technical lead for GenAI projects in CMC . He holds a M.S. from Harvard University and a M.Eng. from ESPCI Paris.
PhD scientist with a degree in computational chemistry with a publication record for the early-stage discovery and design of potential drug candidates targeting Gram-negative bacterial pathogens. Also, a record of demonstrating to scientists, sales representatives, and business professionals the value of science-based software solutions to improve productivity, accelerate discovery, reduce time to market, and lower costs.
This talk provides a brief overview of how AI is being applied across pharmaceutical R&D and where the field stands today. It highlights how AstraZeneca is using frontier AI, including foundation models and agentic frameworks, to support end-to-end clinical development from drug discovery to patient delivery, and closes with a realistic view on what AI can achieve in the near term.
The challenge isn’t just building better models, but building the intelligence agents and systems that connect them. Data, compute, and models are fragmented across internal teams, external partners, and heterogeneous infrastructure, making centralized training and inference impractical. Without moving data or models, federated computing seamlessly enables policy-driven execution of AI workloads across organizational and infrastructure boundaries. This presentation will focus on the underlying technical architecture, including: Federated execution patterns, Model abstraction and routing, Secure sandboxed compute, Governance mechanisms for enforcing data locality, IP protection, and auditability. Learn how federated approaches support training, inference, and agentic workflows, while remaining cloud agnostic, and compatible with existing R&D workflow.
Mohit Goel is a visionary technology leader transforming biopharma, life sciences, and laboratory automation through AI, robotics, and intelligent systems. With deep expertise in systems engineering, software architecture, and autonomous technologies, he is shaping the Lab of the Future, where AI-driven automation accelerates scientific discovery and biomanufacturing at scale.
As the Head of Systems Integration at Moderna, Mohit leads enterprise-wide technology innovation, building next-generation automation platforms that seamlessly integrate AI, robotics, and digital ecosystems to optimize laboratory and manufacturing operations worldwide.
A key driver of global biotech innovation, Mohit serves on the Executive Committee for multiple SLAS tracks, influencing automation, AI, and robotics adoption across life sciences. He is also a Senior Member of ISA and an active member of IEEE, IEEE RAS, IEEE EMBS, and ISPE, shaping the future of biotech at the intersection of AI and advanced automation. Passionate about bridging technology and science, Mohit is building the intelligent, connected, and scalable laboratory ecosystems that will define the next era of biotech innovation.
Etai Jacob, PhD, leads Applied Data Science & AI for Oncology R&D at AstraZeneca, where he scaled global teams of data scientists, computational biologists, and AI researchers to operationalize AI across discovery through clinical development. His work focuses on decision intelligence for drug R&D: integrating multimodal data, deploying predictive biomarker and patient-stratification models, and designing benchmarking and evaluation frameworks for foundation and agentic AI systems. Etai brings 20+ years of cross-industry experience and a track record of converting advanced methods into measurable R&D impact.
Dr. Vlysidis obtained his PhD in Chemical Engineering at the University of Minnesota, Twin Cities, studying and modeling the stochasticity of biochemical reaction networks. With over 6 years of experience in the industry, he has made significant contributions to the fields of scientific software development and engineering. Currently serving as a team leader at AbbVie, Dr. Vlysidis’ primary focus is on supporting the biologics organization in capturing and analyzing experimental data. He possesses a deep understanding of protein properties and leverages innovative protein language models to further enhance research in this area. Prior to joining AbbVie, he worked at Intel, where his expertise was instrumental in supporting R&D research on semiconductors and cutting-edge technology. With a strong academic background and industry experience, Dr. Vlysidis is dedicated to driving advancements at the intersection of chemical engineering, software development, and AI/ML models.
Adrish Sannyasi is an accomplished AI solutions leader with deep expertise in cloud data platforms, artificial intelligence, and healthcare and life sciences applications. He has consistently leveraged data and AI technologies to address complex industry challenges and drive measurable business outcomes across the healthcare and life sciences ecosystem. As Vice President of Customer Solutions and Delivery at Rhino Federated Computing Platform, Adrish helps organizations advance their AI initiatives across a wide range of projects, including large language models, protein language modelling, molecular property prediction, healthcare data analytics, EHR data harmonization, and medical imaging AI. Adrish holds a bachelor’s degree in electrical engineering from Visvesvaraya National Institute of Technology (India), an MBA from the University of Maryland, and a Graduate Certificate in Biomedical Data Science from the Stanford School of Medicine.
In this presentation I will run through the journey that GSK DMPK has taken to move into an automated lab environment. This will include the steps we took to semi-automate our lab based equipment and processes. How we built an end to end data workflow for the seamless support of our projects DMTA cycles. Then finally highlight the on going plans to build a fully automated DMPK platform to align with GSK Research’s plans for ‘lab-in-a-loop’.
VCEL is undertaking a multi-year, multi-phase journey to move from paper-based processes to a digital LIMS application, guided by a clear transformation vision, defined objectives, and planned outcomes. Achieving success requires the right expert partners and strong coordination across those partners throughout the journey.
Craig joined Vericel in 2017 and brings more than 20 years of leadership experience in the life sciences industry across a broad range of biotechnology organizations. He leads the company’s enterprise information technology strategy, enabling scalable, compliant, and high-performing operations across the organization. Craig’s background includes progressive technology and regulatory leadership roles at Genzyme, Biogen, AVEO Oncology, BioVex, Amgen, and Karyopharm Therapeutics. Craig holds a B.S. in Microbiology from the University of Massachusetts Amherst and an M.S. in Regulatory Affairs from Northeastern University.
I am energized by bringing data together to transform the way my colleagues make decisions. I am known for building lean, high-performing teams at the intersection of scientific disciplines to deliver gains in experimental efficiency. My high learning agility and extreme ownership enable me to cut through ambiguity to uncover clarity and direction. I build trust with my colleagues by co-creating and communicating a vivid picture of the future, delineating clear expectations, and operating with authenticity and integrity in everything I do.
With over 25 years of experience in sales and strategic account management in laboratory informatics, I contribute to advancing diagnostic testing and laboratory workflows as Director of Global Scientific LIMS Sales at Clinisys. My expertise spans team leadership, international sales, and business profitability, enabling organizations to adopt innovative digital solutions tailored to their needs. At Clinisys, I focus on driving business growth by developing strategies, managing key accounts, and aligning go-to-market approaches across diverse industries, including life sciences, healthcare, and public health. Dedicated to empowering laboratories, I aim to streamline workflows, enhance health outcomes, and support the digital transformation of laboratory systems worldwide.
Jonathan Gilbert leads the growth of the Lilly TuneLab Ecosystem on the east coast of US and Europe. Jonathan received his PhD from MIT in Chemical Engineering and has spent his last decade plus in biotech at multiple companies ranging from the Seed stage to early clinical public companies. Immediately prior to Lilly, Jonathan lead Corporate Development and Strategy at Entact Bio.
Albert Wang is Executive Director of Research IT Emerging Methods & Technologies at Bristol Myers Squibb. In this role, he is responsible for accelerating biomedical research through the exploration and adoption of foundational machine learning approaches and related technologies. He has 20+ years of experience in designing and building information systems for accelerating all phases of drug research & development, from early target identification to biomarker discovery to post-launch medical research. He has a Bachelor’s degree in Biomedical Engineering and a Masters degree in Bioinformatics from the University of Pennsylvania.
Jonathan Gilbert leads the growth of the Lilly TuneLab Ecosystem on the east coast of US and Europe. Jonathan received his PhD from MIT in Chemical Engineering and has spent his last decade plus in biotech at multiple companies ranging from the Seed stage to early clinical public companies. Immediately prior to Lilly, Jonathan lead Corporate Development and Strategy at Entact Bio.
Wan-Chih Su, Ph.D., is a Principal Scientist at Genentech, where she focuses on developing innovative high-throughput analytical platforms to support small molecules and new drug modalities, including oligonucleotide and peptide drug product development. Her research focuses on high-throughput chromatography, capillary electrophoresis, and spectroscopic methods for impurity profiling and characterization of complex formulations, including mRNA-lipid nanoparticle systems. Before joining Genentech, she earned her Ph.D. from the University of California, Davis, and has since contributed to advancing analytical strategies that bridge fundamental biophysical and separation sciences to biopharmaceutical applications. Her recent work highlights the development of high-throughput analytical methods for quantifying mRNA-LNP formulations.
Vimaldev Devaraja is a seasoned Technical Product Leader with over 20 years of experience delivering lab execution, data management, and automation solutions in the pharmaceutical R&D space. He currently serves as a Principal Platform Engineer at Johnson & Johnson, where he leads multi-million-dollar Lab Automation initiatives and the development of a next-generation GxP-compliant LIMS platform to support clinical studies, including advanced virology and qPCR workflows. Vimaldev specializes in architecting Lab Workflows that unite LIMS, ELN, reagent management, and analytical systems, enabling end-to-end digital continuity and improved scientific outcomes. His work includes strategic roadmaps integrating various BioAnalytical assays, migration from Biovia to LV ELN, and implementation of LabVantage analytics and automated barcode systems—all aligned to GxP and data integrity standards.
Prior to J&J, Vimaldev served as Program Manager at Merck, where he led global teams across the U.S., India, Prague, and Canada, modernized lab infrastructures, introduced DevOps culture, and improved critical GxP system reliability through observability and automation. Across his career, he has managed more than $10M in portfolios, overseen 250+ GxP applications, and driven modernization, cloud adoption, and AI-assisted workflows across global lab environments.With deep expertise in scientific informatics, automation architecture, and regulated lab
ecosystems, Vimaldev brings a pragmatic and future-focused perspective to transforming laboratory operations through intelligent, autonomous, and compliant digital systems.
Justin is a senior director of LIMS strategy at Veeva Systems, focused on the optimization of quality through the modernization of quality control. As a laboratory informatics professional, he brings nearly 20 years of experience partnering with manufacturing and quality organizations to optimize efficiency, accessibility, quality, and compliance through digital transformation.
-Key levers where data can be used to increase pipeline throughput and reduce cost
-How we capture business processes to improve efficiency
-Near-real-time multi-modal data integration for early-phase clinical trials to improve decision making
I am passionate about leveraging data and cutting-edge technologies to improve cancer drug development and advance personalized medicine—matching the right patients with the right treatments. Throughout my career, I’ve collaborated with clinical teams to champion data-driven decision-making. My personal experiences with cancer drive my commitment to developing knowledge systems that integrate clinical, imaging, and biomarker data. These systems provide real-time access to high-quality information, enhancing our ability to make timely, informed decisions. I believe that by harnessing comprehensive cancer data, we can deepen our understanding of cancer biology and drug mechanisms while minimizing potential side effects. Ultimately, curing cancer is a team effort requiring diverse expertise and leadership founded not just on vision, but on empathy that recognizes the human behind each patient.
Chris leads IT and Data Science Solutions Consulting at Benchling, supporting pharma and biotech organizations evaluating enterprise R&D data platforms. With a Ph.D. in Integrative Life Sciences and experience in bioinformatics, genomics, and IT systems, he partners with data and technology leaders navigating platform consolidation, AI enablement, and federated data strategies. His presales role provides unique exposure to strategic decision-making across organizations – the gap between what executives prioritize, what IT can deliver, and what scientists actually adopt. He brings perspective on where enterprise data strategies succeed, where they stall, and the organizational dynamics that determine outcomes.
Start with scientific outcomes, not technology
The Lab of the Future should be designed around accelerating decisions, reproducibility, and insight. Tools are a means, not the strategy.
Build a connected system, not a stack of tools
Instruments, ELN/LIMS, automation, and analytics must operate as one ecosystem with clear data flow, ownership, and integration, otherwise digital transformation stalls.
Build a digital backbone before you chase AI
AI only works when data is accessible, contexualized, and trusted. My focus is on enabling clean data flows, consistent meta-data, and scientific context first, so advanced analytics and AI can actually deliver value later.
Invest in people and ownership as much as platforms
Product ownership, change management, metric tracking, and scientist partnership are what turn digital capability into sustained impact. Product Oriented Teams are responsible for outcomes, adoption, and evolution, not just system uptime. This is the chicken vs. pig analogy for breakfast sandwhiches… one is involved, the other is committed.
Next-gen research agents are “context hungry.” As agents take on more complex scientific questions and multi-step tasks, they require richer, more structured metadata to stay accurate, explainable, and useful. Early agent optimization experimentation is giving us early signals on what types of metadata are needed.
As the demand for metadata increases from next-gen agents, there is now more impetus to evolve from our traditional manual methods of metadata capture within ELN/LIMs/Request forms to automated workflows enabled by the lab of the future. Automation of our labs isn’t only for people but their future digital assistants as well!
Steven Winig is the Executive Director of Technology and User Services (TUS) at Novartis Biomedical Research. The TUS organization enables 5,300 researchers across multiple international campuses. Before joining Novartis, Steven held senior IT leadership roles at the Massachusetts Institute of Technology, served as a Principal at American Management Systems, Inc., and was a Director at Computer-Ed, Inc. He holds a BS in Computer Science from The Johns Hopkins University and lives by the mantra that relationships matter. Known as the resource of last resort, Steve is often called upon to tackle the most nuanced challenges. Interestingly, his college advisor stating that AI will be the future has proven to be prophetic, albeit a few decades early.
Gene leads the Discovery Technology Strategy service line within the Discovery practice at ZS, where he works with many top pharmaceutical companies on multi-year research digital transformation programs. He has extensive experience leading large cross-functional teams to modernize discovery workflows and platforms and is passionate about applying innovations in data and technology to propel the future of drug discovery.
The talk will cover the use of AI across multiple scientific workflows, using real-world examples such as small-molecule design, computer vision to extract insights from cell imaging, advanced analysis of behavioral studies, and LLMs for scientific writing and documentation. The overarching message is that AI point solutions are maturing and becoming broadly available across the industry, with strong potential to drive efficiency gains and faster, better-informed decisions. Scientific AI has become and will continue to be an essential part of how CROs operate. At the same time, differentiation will not come from AI alone. Human expertise remains critical, and the most effective models will keep experienced scientists firmly in the loop. The winners in the CRO sector will be those that combine deep scientific expertise with strong data strategies, robust information security, and a clear commitment to client confidentiality.
The AI narrative in life sciences is built on a flawed assumption: that if we centralize and clean enough data, intelligence will emerge. But without an explicit model of how science is executed — how materials are defined, how processes unfold, and how decisions are made — data lacks the structure required for reproducibility, automation, and trustworthy AI. Scientific work today is fragmented across instruments, systems, and teams. Materials are inconsistently represented, process logic is implicit, and context is lost between experimentation and analysis. Without a common language that connects materials and processes, automation becomes brittle and AI cannot reason with fidelity. Reframing science as an executable system changes the equation. When both material representation and process modeling are defined with precision, they create the scaffold that gives data meaning — enabling scalable automation, explainable outcomes, and AI that can support next decisions, not just summarize past results. This is the foundation for a true Lab of the Future: a connected system spanning research through manufacturing, where experiments, materials, workflows, and decisions form a coherent whole — accelerating the path from molecule to market.
I am a digital and tech senior leader with purpose, presence and agility. I bring a track record of successful digital strategy development and value delivery at scale, with extensive experience in broadening impact, building connections, and developing organizations. I am known as a collaborative partner and engaging communicator with contagious positive energy. My superpower is connecting with people and building a culture where individuals come together and shine. My multi-year global work assignments in China and the UK give me a unique perspective to relate to the international teams I lead. My purpose to positively impact human lives carries through into my work as a foster parent in our community and my seat on the board of a non-profit.
My organization is driving a digital revolution of the next-generation of labs and plants for Sanofi scientists. Our teams deliver digital products and services that enable robust and effective lab and plant operations, while capturing trusted AI-ready data.
Our scope includes instrument connectivity, data automation, experiment and results capture, laboratory workflow solutions, as well as digital manufacturing solutions. We enable all of Sanofi’s R&D labs, across research, pre-clinical and CMC, spanning all pharma modalities and vaccines. We are also driving digital transformation in the manufacturing environment for CMC pilot plants and enable launch excellence in digital technical transfer to commercial scale manufacture.
Michael Swartz is Chief Strategy Officer responsible for driving Dotmatics long-term strategicinitiatives and accelerating the delivery of value to Dotmatics’ global scientific customer base.Michael previously served as Senior Vice President of Enterprise Product Strategy, where he playeda pivotal role in the development of Dotmatics Luma, the company’s Scientific Intelligence Platform. A recognized pioneer in the digital transformation of life sciences R&D, Michael brings more than 25years of experience bridging science and software to modernize laboratory workflows and unlock thepower of data. Prior to joining Dotmatics, Michael was Vice President of Software Solutions andStrategy at PerkinElmer Informatics (now Revvity), where he led portfolio strategy for industry-leadingplatforms including Signals, ChemDraw, and Spotfire. He has also held leadership roles at CambridgeSoft, including Vice President of Knowledge Management.
Building a self-driving laboratory requires more than just automation; it requires closing the loop between digital hypothesis generation and physical execution. In drug discovery, the disconnect between the “dry lab” and the “wet lab” remains a primary bottleneck. Overcoming this is the critical step toward creating autonomous, learning-driven systems that evolve with every experimental cycle. In this presentation, we introduce Connect Discover, a joint venture between BenchSci and Thermo Fisher Scientific. This end-to-end solution bridges the gap by integrating:
• The Digital: BenchSci’s ASCEND platform, driving AI-powered hypothesis generation and experimental design.
• The Physical: Thermo Fisher’s Connect Enterprise solution, translating digital intent into bench-ready protocols via advanced lab automation.
By seamlessly reintegrating experimental results to inform the next iteration, this partnership transforms fragmented workflows into a high-velocity discovery engine. Drawing on real-world constraints faced by preclinical scientific teams, we will share key learnings on how this closed-loop approach adapts to diverse research environments and accelerates the journey from data to drug candidate.
Jonathan Lippy leads a global team leveraging state-of-the-art automation and data technologies to deliver end-to-end capabilities with a focus on speed and portfolio impact across all therapeutic areas and modalities. With 29 years of experience in drug discovery, Jonathan has driven transformative strategies delivering next-generation AI-driven automation capabilities and workflows. Prior to joining J&J, Jonathan spent 22 years at Bristol-Myers Squibb, where he led the Kinome Hit-to-Leads Platform and Screening Operations team and was a member of the Discovery team for SOTYKTU®.
As SVP of Strategic Alliances, Casandra Mangroo plays a pivotal role in forging and nurturing key partnerships that drive BenchSci’s mission to accelerate preclinical drug discovery. Leveraging her deep understanding of the scientific landscape and BenchSci’s innovative ASCEND platform, Casandra collaborates closely with top pharmaceutical executive leadership and other strategic partners to identify and cultivate mutually beneficial alliances. Her focus is on creating impactful collaborations that translate organizational research goals into tangible solutions, ultimately empowering scientists with cutting-edge technology. Casandra brings a wealth of experience in understanding the needs of research scientists and translating them into strategic initiatives. As the former SVP of Product & Science, Casandra was instrumental in shaping BenchSci’s product vision over the past 8 years, leveraging AI technology through the ASCEND platform to accelerate preclinical drug discovery for scientists in leading research laboratories. She works closely with executive leadership, as well as technical, scientific, and commercial teams, to explore collaborative opportunities that expand BenchSci’s reach and impact.
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.
Dr. Petrina Kamya is a computational chemist specializing in computer-aided molecular design with a career spanning academic research and industry leadership roles. She earned her Ph.D. in theoretical chemistry from Concordia University, where she researched RNA structure interactions and small molecule design. Transitioning to industry, Dr. Kamya joined Chemical Computing Group (CCG) in Montreal where she played a pivotal role in sales and business development, focusing on molecular modeling software tailored for pharmaceutical and biotech companies and academic institutions. At Certara, she consulted for pharmaceutical companies, offering strategic insights on market access and drug commercialization.
Matthew Davis is Senior Partner and Head of Pioneering Intelligence, an initiative of Flagship Pioneering that harnesses AI to accelerate innovation in the life sciences & beyond. He joined Flagship in 2024 as Chief AI Scientist for Ignacio Martinez’s Pioneering Business Unit working in sustainability and health ventures.
Prior to joining Flagship, Matt advanced innovation at leading human genetic diagnostics companies. He served first as Head of AI & Data at Invitae, where he led strategic business development in AI/ML and grew a team to apply machine learning to clinical interpretation, scalable operations, and personalized patient insights. His team’s application of probabilistic machine learning to variant interpretation led to the resolution of tens of thousands of clinical human variants. He later led the technical transformation of Sema4/GeneDx as Chief Product and Technology Officer.
He began his career at IBM working in Linux development and high-performance computing, which led him to academic research in systems and computational biology. He worked with pioneers at UT Austin and UC Berkeley applying machine learning to high throughput morphological phenotyping, x-ray crystallography, and transcriptional regulation.
Matt returned to computer science as a group leader at IBM Research, founding a team to research multimodal AI agents and human-computer interaction. In addition to developing several enterprise software products in this space, Matt continued to author papers and patents in the fields of NLP, AI, HCI, and biology. He holds a Bachelor’s degree from UT Austin and a Ph.D. from UC Berkeley.
David Cooney is the Head of GTM strategy at Sigmatic Sciences and former Strategic Client Partner at Causaly AI and former Associate Partner at McKinsey, focused on AI in life sciences R&D. He has led GTM strategy, value proposition design, and enterprise partnerships across top-20 pharma, building multimillion-dollar pipelines and shaping AI product-packaging and partnership
Keenan Lacey is a Sr. Scientist at Regeneron Pharmaceuticals, where he applies AI-enabled and data-driven approaches to accelerate the discovery and evaluation of novel therapeutic
targets across immunology and infectious disease. His work integrates human biology and translational insights to inform early-stage drug development and strategic decision making. Previously, Keenan led research in host-pathogen biology and vaccine development at NYU Langone Health. He holds a PhD in Immunology and brings deep expertise at the intersection of translational science and innovation in biopharma.
With twenty years of experience at the intersection of life sciences and technology, Saurabh’s work is guided by a single mission: improving biopharma R&D productivity. He leverages his expertise in strategy, data & analytics, and AI to solve the complex challenges facing today’s biopharma organizations. For biopharma companies, he cuts through the AI hype to implement technologies that deliver tangible results. For deep tech startups, he translates breakthrough science into go-to-market strategies that solve real-world R&D problems.
Saurabh previously led strategy, operations, and analytics at Takeda, Pfizer, and PwC. This background gives him fluency in both the language of science and the logic of algorithms. He holds an MBA from MIT Sloan, an MS in Chemical Engineering from Carnegie Mellon, and dual degrees in Biotechnology from IIT Delhi. Saurabh lives in Brookline, MA, with his wife and two children.
Matthew Davis is Senior Partner and Head of Pioneering Intelligence, an initiative of Flagship Pioneering that harnesses AI to accelerate innovation in the life sciences & beyond. He joined Flagship in 2024 as Chief AI Scientist for Ignacio Martinez’s Pioneering Business Unit working in sustainability and health ventures.
Prior to joining Flagship, Matt advanced innovation at leading human genetic diagnostics companies. He served first as Head of AI & Data at Invitae, where he led strategic business development in AI/ML and grew a team to apply machine learning to clinical interpretation, scalable operations, and personalized patient insights. His team’s application of probabilistic machine learning to variant interpretation led to the resolution of tens of thousands of clinical human variants. He later led the technical transformation of Sema4/GeneDx as Chief Product and Technology Officer.
He began his career at IBM working in Linux development and high-performance computing, which led him to academic research in systems and computational biology. He worked with pioneers at UT Austin and UC Berkeley applying machine learning to high throughput morphological phenotyping, x-ray crystallography, and transcriptional regulation.
Matt returned to computer science as a group leader at IBM Research, founding a team to research multimodal AI agents and human-computer interaction. In addition to developing several enterprise software products in this space, Matt continued to author papers and patents in the fields of NLP, AI, HCI, and biology. He holds a Bachelor’s degree from UT Austin and a Ph.D. from UC Berkeley.
David Cooney is the Head of GTM strategy at Sigmatic Sciences and former Strategic Client Partner at Causaly AI and former Associate Partner at McKinsey, focused on AI in life sciences R&D. He has led GTM strategy, value proposition design, and enterprise partnerships across top-20 pharma, building multimillion-dollar pipelines and shaping AI product-packaging and partnership
Keenan Lacey is a Sr. Scientist at Regeneron Pharmaceuticals, where he applies AI-enabled and data-driven approaches to accelerate the discovery and evaluation of novel therapeutic
targets across immunology and infectious disease. His work integrates human biology and translational insights to inform early-stage drug development and strategic decision making. Previously, Keenan led research in host-pathogen biology and vaccine development at NYU Langone Health. He holds a PhD in Immunology and brings deep expertise at the intersection of translational science and innovation in biopharma.
Mitchell spent 3.5 years as a medicinal chemist researching and developing central nervous system drug candidates for neurodegenerative diseases in the Lab for Drug Discovery in Neurodegeneration at Brigham and Women’s Hospital/ Harvard Medical School. Following, Mitchell served as co-founder and Chief Technology Officer for 2.5 years at Modulate Bio, where he helped develop next-gen GABA-A positive allosteric modulators to treat neurological disorders, including essential tremor, epilepsy, and anxiety. Mitchell now works as an Application Scientist at Collaborative Drug Discovery
Jonathan Gilbert leads the growth of the Lilly TuneLab Ecosystem on the east coast of US and Europe. Jonathan received his PhD from MIT in Chemical Engineering and has spent his last decade plus in biotech at multiple companies ranging from the Seed stage to early clinical public companies. Immediately prior to Lilly, Jonathan lead Corporate Development and Strategy at Entact Bio.
In this talk, I’ll explore how to close the gap between data visibility and operational decision-making by understanding how equipment is actually used in the lab. I’ll show how connected intelligence built on real equipment usage can drive clear, prioritized operational decisions. We’ll look at how bringing together disparate data points exposes hidden inefficiencies, equipment risk, and capacity challenges—and I’ll share what the next phase of connected lab operations looks like in practice.
Dan Petkanas is a leader in the digital transformation of laboratories, drawing on years of experience driving impactful change across hundreds of laboratories globally. His expertise spans research and development (R&D), compliance, and manufacturing, where he focuses on optimizing data integrity, maximizing laboratory asset utilization, and ensuring seamless equipment compliance and connectivity. At Elemental Machines, Dan’s strategic vision helps laboratories achieve new levels of operational efficiency, data accuracy, and regulatory excellence.
This will talk will cover the following topics :
• Data Value & AI/ML: Laboratory data is increasingly valuable as AI/ML tools can interpret large datasets and deliver actionable insights.
• Standardized Formats: Trends, alerts, and predictive modeling rely on data being in a standardized format for easy evaluation by these tools.
• OpenLab Advantage: OpenLab enables seamless data sharing with dashboarding tools and converts Agilent and multivendor data types into industry-standard formats for integration into data lakes and AI-driven insights
Alayna is an Associate Director within Biologics CMC Developability at AbbVie. Her team oversees biophysical and structural screening of biotherapeutic candidates in late Discovery timelines. Training in structural biology and mass spectrometry inform her interest in developing mechanistic based understanding of protein structure/function relationships. Additionally, she is interested in maximizing the impact of the complex data sets enabled by recent advances in analytical techniques and data capture
Kate Mingle is a Principal Data Scientist at AbbVie focused on advancing AI and machine learning initiatives to accelerate the development of new therapies. Her work is centered in cultivating innovative and scalable strategies to facilitate broad applications in pharmacokinetics, safety, and biophysical property prediction. Prior to joining AbbVie, she led CMC data science efforts at Moderna, where she supported scale-up and commercialization of the COVID-19 vaccine.
Jon Welsh has been with Agilent for over 30 years. He currently leads the Americas informatics sales team responsible for selling enterprise informatics CDS, LIMS and SDMS and core management software solutions. He has held different positions in software applications, sales, and services marketing management across Agilent.
Raveen Sharma is a Managing Director in Deloitte’s Life Sciences R&D with over 25 years of experience delivering research, clinical, and real-world data informatics solutions for life sciences organizations. He leads teams to develop strategy, business case, roadmaps, solution design, and execution for data-driven programs to transform R&D. Most recently, he launched and co-leads the Lab of the Future practice to help life sciences organizations improve efficiency and increase innovation in the lab environment.
I am a digital and tech senior leader with purpose, presence and agility. I bring a track record of successful digital strategy development and value delivery at scale, with extensive experience in broadening impact, building connections, and developing organizations. I am known as a collaborative partner and engaging communicator with contagious positive energy. My superpower is connecting with people and building a culture where individuals come together and shine. My multi-year global work assignments in China and the UK give me a unique perspective to relate to the international teams I lead. My purpose to positively impact human lives carries through into my work as a foster parent in our community and my seat on the board of a non-profit.
My organization is driving a digital revolution of the next-generation of labs and plants for Sanofi scientists. Our teams deliver digital products and services that enable robust and effective lab and plant operations, while capturing trusted AI-ready data.
Our scope includes instrument connectivity, data automation, experiment and results capture, laboratory workflow solutions, as well as digital manufacturing solutions. We enable all of Sanofi’s R&D labs, across research, pre-clinical and CMC, spanning all pharma modalities and vaccines. We are also driving digital transformation in the manufacturing environment for CMC pilot plants and enable launch excellence in digital technical transfer to commercial scale manufacture.
Gisele Tavares currently serves as the Head of R&D Business Operations at Takeda. In this role, she oversees business operations, the Takeda One Cambridge Campus project, Laboratory Operations in Massachusetts and Austria, and contract management. Gisele acts as the primary point of contact and engagement for functional leaders within Takeda R&D, as well as enterprise business partners including Legal, Takeda Business Services, Real Estate, Facilities, and Procurement.
Gisele began her career in the pharmaceutical industry as a scientist and has held leadership roles in the USA, France, and Switzerland, gaining valuable insights into the benefits of diversity and multicultural environments. Prior to joining Takeda, she held increasingly responsible positions at Hoffmann-La Roche and Novartis Pharma, transitioning from scientific research to clinical operations, procurement, alliance management, and business development.
Gisele holds a Bachelor and Master of Science in Pharmacy and Biochemistry from the University of Parana, Brazil, and a PhD in Science from the University of Sao Paulo, Brazil/Pasteur Institute, France, in Physical Chemistry. She completed her postdoctoral fellowship at the Boston Biomedical Research Institute, Yale University, and Stanford University.