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AI is rapidly moving from experimentation to practical application across the laboratory. Yet as organisations invest in pilots, automation and increasingly intelligent workflows, a more difficult challenge is emerging: how do we move beyond successful proofs of concept and embed AI into the way laboratories actually operate, make decisions and learn? Drawing on lessons from laboratory transformation programmes and emerging industry thinking, this session will explore what we are learning as organisations navigate this transition. It will examine how laboratory operating models need to evolve as AI becomes embedded across familiar Design–Make–Test–Analyse workflows; why change management, new skills and the evolving roles of scientists and operators are becoming as important as the technology itself; and why orchestration and governance must increasingly be designed around the decisions that drive scientific and business outcomes. The session will introduce the concept of the Decision-Ready Laboratory: an environment in which people, AI, automation and trusted data work together through governed, auditable processes to turn evidence into action and outcomes into learning. Data remains foundational, but AI is exposing a challenge beyond data availability and quality: context. For AI to meaningfully support a scientific decision, it needs not only the right data, but an understanding of the objective, evidence, constraints, uncertainty and decision authority surrounding it. Attendees will leave with practical lessons from current transformation efforts, questions to challenge their own AI and automation programmes, and a framework for thinking beyond individual use cases toward laboratories capable of making better decisions, learning faster and adapting as AI capabilities continue to evolve.
Christian Diehl, Chief Data & Digital Officer, Biomedical Research (BR). Christian serves as BR´s Chief Data & Digital Officer and is a member of the BR leadership team. He leads Research Informatics and large data initiatives like Data42 and flagship AI initiatives, driving AI and digital innovation for BR. He also serves on the board of directors of Novartis Germany.
I run the Data & Digital Office for Biomedical Research, enabling delivery of our strategic initiatives, and advancing our digital transformation. I work closely with key stakeholders and our Data Science and Informatics teams across the organization to ensure value delivery, optimal use of data and digital assets, and sound investment decisions into the right priorities.
My role is to maximize the impact of Data Science and Artificial Intelligence on our R&D pipeline’s speed and success rate, bringing better new drugs faster to patient.
Chris leads Accenture’s Lab Reinvention UK practice, helping organisations reinvent their scientific and laboratory environments with the adoption of modern digital technologies. With more than 25 years of software development and technology experience, Chris has worked across start-ups and global organisations, leading teams and delivering solutions that bridge complex technical requirements with business needs. With over 15 years of laboratory informatics experience, Chris takes pride in putting the scientist first to develop and support adoption as part of strategic solutions across the lab to enable acceleration of scientific discoveries to reach the patients.
As the Executive Vice President, Head of R&D at Lundbeck I work together with my talented team to be premiere in neuroscience research and development, translating forefront science into novel medicines to restore brain health and enable people impacted by brain disease to live a better life.
With a focus on applying our leading capabilities in translating neurobiology insights into breakthrough medicines serving neurology, psychiatry, and pain indications where there are particularly high unmet medical needs. Prior to joining Lundbeck I worked with large, mid-sized pharma, and start-up biotech companies. My expertise lies in R&D line-management, project leadership, and program (portfolio) management, from target and drug discovery throughout to late development, for small molecules and biotherapeutics (mAbs and protein ligands) in the neuroscience area (neurology, psychiatry, and pain) and in the immunology & inflammation area (dermatology & rheumatology).
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.
For years, even decades the Lab and technology have been trying to address the same challenges; software implementation, instrument integration, data standardisation and strategy, automation and now Artificial Intelligence. Whilst these have led to progress and some elements of transformation, the reality is that wholesale impact to elicit industry-wide change is yet to be realised. Why is this given so many areas have had vast amounts of time and money invested into them? Could the real path forward be something that we have not focused on throughout much of the traditional Lab of the Future journeys we have taken. Looking at the core building block of the Scientific Process and how to re-imagine this should be where we expend our efforts to help unlock the potential of the modern technology that we now have at our disposal.
Bert is a Senior Fellow Architecture and Engineering at JnJ Innovative Medicine Technology R&D. That means he designs future proof solutions for the Global Sciences department, focusing on cloud-native implementations of systems that require High Performance Compute or require full integration. Bert has a background in Chemistry and Computer Science. During his 28-year career at JnJ he has spent 26 years in various IT departments. In his current position, Bert is predominantly focused on the Discovery (overall process, and In-silico design using Machine Learning) and the lab execution (Scientific Data Management) systems.
Edith Heard, PhD, FRS is a British scientist and previous Director General of the European Molecular Biology Laboratory. She graduated from Cambridge University in 1986, specialising in genetics, and then carried out her PhD at the Imperial Cancer Research Fund, working on gene amplification mechanisms in cancer.
She moved to the Pasteur Institute in Paris in 1990, as a postdoc, which is where she began her studies on the epigenetic process of X-chromosome inactivation. In 2000 she spent a year at Cold Spring Harbor Laboratory in the USA as a visiting scientist, before moving to the Institut Curie in 2001, where she was director of the Genetics and Developmental Biology Department. In 2025, Edith joined the Crick as Chief Executive Officer.
Edith’s laboratory focuses on epigenetic processes in mammals, with a particular interest in chromosome biology and the role of non-coding RNAs, chromatin structure and nuclear organization, in the establishment and maintenance of differential expression patterns during development and in disease. She became an EMBO member in 2005, was awarded the CNRS Gold Medal in 2024, the CNRS Silver Medal in 2008 and elected as a Fellow of the Royal Society in 2013.
Leading UK scientific strategy, creating R&D collaborations, driving external scientific engagement, bridging our diverse portfolio of platforms with partners & investors in the UK, and scaling global innovation and impact for Flagship.
Adam Paton is a principal consultant at Zifo helping scientists transform the way they work through technology but with a lens firmly on the science. As a life sciences informatics veteran, Adam has seen the shift towards digitally driven initiatives that have rapidly accelerated during the last 3 years. Starting out as a biologist, the link between science and computing was an area of initial interest and for the last 24 years he has been on a journey seeing hundreds of organisations start and continue their journey towards the next generation of digital science.
With experience in road mapping, strategy, implementation, customer success with organisations from start-ups to Top 10 Pharma, Adam has seen the vast variety of solutions emerge in the industry and in some cases succeed, in others fail to realise their promise but throughout looking to change the way science is done for the better.
Hans Clevers is world-renowned for his work in the fields of cell biology, molecular signaling and stem
cells. His research groups’ discoveries include the detailed characterization of the molecular effectors
and integrators of the “Wnt” pathway, which play crucial roles in health and disease, including in stem
cells, regeneration and cancer. His group provided important insights into (intestinal) stem cell biology,
exploiting LGR5 as a novel stem cell marker. This eventually led him to pioneer “organoids”, 3
dimensional in vitro structures that behave anatomically and molecularly like the organ from which they
are derived. Organoid biology has revolutionized the way we understand and approach human biology
and medicine.
Hans Clevers obtained his MD and PhD degrees from the University of Utrecht, the Netherlands. He
holds a professorship in Molecular Genetics from the University of Utrecht. He previously held
directorship/President positions at the Hubrecht Institute, the Royal Netherlands Academy of Arts and
Sciences and the Princess Maxima Center for pediatric oncology. He has served as Head of Roche’s
Pharma Research & Early Development (pRED) since March 2022 as member of the company’s Enlarged
Corporate Executive Committee. In 2023, he oversaw the establishment of the Institute of Human
Biology (IHB) in Basel, and currently serves as its ad interim Director. Hans Clevers will remain in charge
of the IHB until a successor is appointed, while supervising his research groups at the Hubrecht Institute
and the Princess Máxima Center.
He is the recipient of multiple international scientific awards, including the Breakthrough Prize in Life
Science. Hans Clevers is a member of the Royal Netherlands Academy of Arts and Sciences (NL), the
National Academy of Sciences (USA), the Royal Society (UK) and the Academie des Sciences (France). He
is also Chevalier de la Légion d’Honneur and Knight in the Order of the Netherlands Lion, among many
other international accolades.
Laboratories will only be able to realize their digital potential if the purpose is clear, the data is relevant, and the organization is ready. In this presentation, I will outline how the Digital Product concept accelerates the impact on the pipeline, working with the tools, processes and skills, and leverage multi-agent frameworks to build trustworthy AI pipelines
Modern laboratory environments are under constant pressure to innovate while continuing to operate at full speed. For many organizations, decades-old systems have evolved into highly complex, tightly coupled platforms that are difficult to scale, integrate, or replace. In this joint keynote, BASF and Astrix share a real-world transformation journey from monolithic, application-centric architectures toward a data-centric lab platform. At the core of this shift is a simple but powerful principle: data, not applications, should be the stable foundation of the enterprise, enabling flexibility, interoperability, and continuous innovation. Rather than pursuing a high-risk “big bang” replacement of legacy capabilities, BASF is applying an incremental modernization strategy that gradually introduces modular services, connected through a data integration layer. This approach allows new digital capabilities to be delivered continuously while existing systems remain operational, effectively “changing the tires while the car is driving.” The session will explore: Why traditional application-centric architectures lead to fragmentation, complexity, and limited scalability in modern labs, How a data-centric architecture enables interchangeable applications and sustainable integration layers, the role of incremental modernization, service decoupling, and domain-driven design in reducing risk and accelerating value delivery Practical lessons learned from BASF’s implementation, including governance, sequencing, and organizational alignment. This keynote provides a pragmatic blueprint for laboratory leaders seeking to modernize complex digital ecosystems without disrupting critical operations, turning transformation from a one-time event into a continuous innovation strategy.
Max has 25+ years of industry experience, focused on digital transformation in chemicals & materials, life sciences, and biotech industries. Throughout his career, Max has held positions in consulting, scientific product development/management, and various other technology leadership positions. Max specializes in data architecture and design with emphasis on the full data lifecycle, including provenance management, active and passive data approaches to quality, dashboarding/modeling/ authoring applications of data, data extraction-transformation architecture and design for data aggregation, ontologies, and cross-industry reference data standards. While at Dotmatics, Max headed up the chemicals & materials division and was also responsible for the formulations data management product strategy. While at Biovia, Max led strategic consulting engagements for top 50 chemicals companies.
Kristof holds 25 years of experience in Plant Science, of which the last 15 years in Digitalization projects. He started his career as Researcher at the Plant Genetics department of the University of Brussels, then later joined Bayer CropScience in multiple roles and is now working with BASF Agricultural Solutions as Program Manager – Molecular Characterization. Throughout his career, he developed a solid mix of bio-technology knowledge with hands-on lab experience, in-depth project management and a broad digital affinity. In his current role, Kristof manages the Digital Product Family that oversees the application landscape for BASF’s Seeds & Traits molecular laboratories. Covering the entire business spectrum from initial discovery to final commercialization, his team takes care of ontologies, repositories, ELN, LIMS, data products & AI solutions. The lab is Kristof’s lifelong passion. It’s the place where magic happens!
AI succeeds in Pharma when data carries enough shared meaning and context to support trustworthy decisions—not simply when more data or advanced models are available. This presentation proposes a flexible semantic backbone, matching semantic investment to each use case’s ambiguity, reasoning, reuse, and risk, while reserving formal ontologies for genuinely auditable, regulator-facing applications.
Biopharma has invested heavily in data platforms, digital architectures, and AI-ready foundations. Yet the scientific knowledge that underpins process understanding, development decisions, and regulatory confidence is created during experimental execution, where processes are refined, evidence is generated, and risks are addressed. This session explores why scientific execution deserves greater recognition as a foundational element of the digital backbone of R&D. By connecting experiments, process knowledge, and development workflows, organizations can establish more defensible development processes, strengthen Digital CMC initiatives, accelerate technology transfer, and reduce the time required to move promising therapies toward commercial readiness. At the same time, they create the trusted scientific foundation needed to support AI-driven innovation.
Chemistry degree educated, accredited Lean Six Sigma Black Belt with a proven history of driving major business & digital transformation projects across global pharmaceutical R&D environments, including successfully leading and coaching multi-functional change project teams in matrix environments to deliver significant business results. Accountable for the creation, development and execution of the late stage pharmaceutical development digital science strategy.
Erik holds a PhD in Molecular Biotechnology from The Royal Institute of Technology (KTH) in Stockholm, Sweden, focusing on intracellular applications of alternative scaffold proteins. After a postdoc at the Novo Nordisk Foundation Center for Protein Research (NNF CPR) in Copenhagen, Denmark, Erik joined Novo Nordisk and has over 15 years with the company (Denmark and US based) collected a broad expertise in Protein Science, Discovery Biology and Research Informatics. He has specialized in difficult-to-produce proteins and multi-specific biologics, been leading therapeutic project initiation, spearheading development of related workflow and registration systems, and contributed to external technology/target evaluation committees. He has also been a program lead for major data science collaborations with tech companies and academic groups. In his current role as VP of Scientific Data Registration, Erik is focused on exploring emerging digital capabilities to fulfil the data and decision support needs of Discovery Research.
Max has 25+ years of industry experience, focused on digital transformation in chemicals & materials, life sciences, and biotech industries. Throughout his career, Max has held positions in consulting, scientific product development/management, and various other technology leadership positions. Max specializes in data architecture and design with emphasis on the full data lifecycle, including provenance management, active and passive data approaches to quality, dashboarding/modeling/ authoring applications of data, data extraction-transformation architecture and design for data aggregation, ontologies, and cross-industry reference data standards. While at Dotmatics, Max headed up the chemicals & materials division and was also responsible for the formulations data management product strategy. While at Biovia, Max led strategic consulting engagements for top 50 chemicals companies.
Kristof holds 25 years of experience in Plant Science, of which the last 15 years in Digitalization projects. He started his career as Researcher at the Plant Genetics department of the University of Brussels, then later joined Bayer CropScience in multiple roles and is now working with BASF Agricultural Solutions as Program Manager – Molecular Characterization. Throughout his career, he developed a solid mix of bio-technology knowledge with hands-on lab experience, in-depth project management and a broad digital affinity. In his current role, Kristof manages the Digital Product Family that oversees the application landscape for BASF’s Seeds & Traits molecular laboratories. Covering the entire business spectrum from initial discovery to final commercialization, his team takes care of ontologies, repositories, ELN, LIMS, data products & AI solutions. The lab is Kristof’s lifelong passion. It’s the place where magic happens!
My mantra to make decisions is this quote by Edwards Demings: “In God we trust and all others must bring data”. I have over 11 years of experience working with data. Recently, I was involved in the development of ontologies and data standardization strategies at Monsanto Research Centre, a subsidiary of Bayer Crop Science. In my previous roles I’ve been involved in bioinformaticis, data mining, data stewardship, data visualisation, the development of tools for querying structured and unstructured data and pipeline analytics.
Nick Fuller is Product Director for the Next-Generation Platform at IDBS, where he leads the vision and evolution of data-centric solutions that address the growing complexity of scientific workflows in drug development. With over a decade of experience at IDBS and Danaher, Nick has worked closely with global biopharma organisations to understand the real-world challenges scientists face – from fragmented data landscapes and legacy systems to the need for faster, more informed decision-making. His career spans training, consultancy, and leadership of strategic delivery teams, giving him deep insight into both the operational and scientific context of modern R&D. Today, Nick focuses on shaping a future where unified data backbones underpin seamless, connected workflows, and where AI plays a central role in augmenting scientific discovery and transforming ways of working. He is passionate about translating complex technical capability into meaningful outcomes for scientists, helping organisations unlock the full value of their data to accelerate innovation. Nick holds a BSc in Biochemistry from the University of Southampton and is trained as an educator, enabling him to communicate complex concepts clearly and drive alignment across diverse stakeholders.
AI agents, predictive models, laboratory automation, and scientific data are advancing rapidly, yet research remains fragmented across wet-lab execution, computational methods, informatics, and business processes. This talk examines multi-agent orchestration as the missing layer that connects these capabilities into coherent scientific workflows. We will show how human and AI scientists can coordinate specialized tools, incorporate scientists and laboratories when needed, evaluate results, and revise research plans. Attendees will see how organizations can progress from embedded AI assistants to increasingly autonomous scientific colleagues, expanding in-silico experimentation while focusing wet-lab resources on the most promising hypotheses.
Darren has recently retired from GSK after a career spanning 33 years and many roles, most recently as Global Head of Cheminformatics. He is now semi-retired, working as a Consultant and is Honorary Professor of Chemistry at University College London where he continues to pursue novel computational methods- based on simulation, cheminformatics and machine learning- which will improve the speed and efficiency of small molecule drug discovery.
The design and deployment of digital platforms are at the heart of my work. I specialize in cloud architecture, driving innovations that enable global expansion and streamline product delivery. My collaborative approach ensures that solutions not only meet but exceed the evolving demands of digital healthcare.
Rob Brown is Global VP, Head of Scientific Office Sapio Sciences. Prior to joining Sapio Sciences, he spent eight years at Dotmatics where he held various positions including Head of Global Presales and Head of Product Marketing & Product Management. Earlier in his career he was responsible for product marketing teams for cheminformatics and bioinformatics at Accelrys, SciTegic and MSI. Rob started his career as a postdoc and later research scientist in the Computer Aided Molecular Design department at Abbott Laboratories (now Abbvie). He received his PhD in Cheminformatics from the University of Sheffield, UK.
An innovative Scientist, Informatician and Technologist with over 25 years of experience in AI/ML, data science and advanced technologies as a Member and Leader of both R&D and IT groups, providing strategic direction and building diverse teams to support the design and development of novel drugs, across modalities and indications. Experienced working and collaborating with start-ups, not-for-profit organisations and large pharma at all levels including executive leadership, internal consulting, and non-executive & advisory board memberships.
Senior Director Lab Capture & Experience for GSK in the R&D Tech division with 20 years’ experience in pharmaceutical R&D at Pfizer and GSK. A PhD biochemist by training, I spent 14 years in early research high throughput screening/compound profiling before transitioning to IT. I have delivered IT solns across CMC functionalities: CG&T supply chain, multi-modality QC LIMS & CMC data access tools, and I am passionate about realising data accessibility in CMC to match the capability in early research. Currently I am accountable for the Tech strategy to digitalise CMC Lab Data Capture from point of generation to availability for re-use, leading the delivery of a multi-modality global CMC ELN deployment and multiple Lab of the Future initiatives.
Jason Boyd is the Head of Regulated Labs Strategy at Benchling. He leads initiatives to expand the company’s impact into the regulated labs through strategic product roadmaps and cross-functional leadership.
The centralized laboratory automation team at AbbVie supports a broad spectrum of R&D laboratories across the global product development landscape. One focus area is the regulated bioanalysis high-throughput laboratory, where step-by-step automation of complex processes has led to substantial productivity gains over the past decade. Segmenting the process into dedicated automation islands or workcells has been pivotal for productivity increase. Furthermore, this approach offered higher programming flexibility, implementation of sophisticated error handling, and enabled modular laboratory setups, while ensuring regulatory compliance. In preparation for a move to a new laboratory facility in 2027 and to challenge the status quo toward full end-to-end automation, we developed a novel order-based strategy for orchestrating of multiple stand-alone islands, aiming to build a future-proof modular laboratory that can quickly adapt to evolving requirements and rapid technological advances. To test this strategy in a real-world scenario, we established the Sandbox Lab. This laboratory acts as a proof-of-concept playground, mimicking the regulatory bioanalysis laboratory, where we integrate multiple vendor systems with custom solutions and test both data transfer and different plate logistics options—such as mobile robots and rovers. This approach enabled seamless connectivity between different systems, independent of traditional orchestration software or scheduler, and remains fully agnostic to system type or vendor.
Martin Winter is founder and CEO of Lab Automation Network since 2008. Martin is passionate about providing outstanding technological solutions to life science companies with his alliance of leading lab automation and digitalization partners. Driving the technological transformation in pharma, biotech and diagnostics industries will significantly improve medical research and individual healthcare.
Martin pursued his chemistry studies in Aachen and Constance before earning his PhD in organic chemistry from the University of Tübingen in 2001. With a professional journey beginning in 1998, he has held various co-founding and managerial positions in biotech and life science technology companies. Martin resides in Tübingen, Germany.
Dr. Gleb Konotop is Head of Automation at AbbVie Development Sciences, where he leads laboratory automation and digital transformation initiatives across global R&D. Over the past seven years, he has established the centralized automation team, promoted global harmonization initiatives, and driven the development of modular laboratory architectures, robotics, orchestration, and scalable automation solutions for regulated and non-regulated research areas. Before joining AbbVie, Gleb worked as an Automation Specialist at Hamilton Robotics, where he implemented automated solutions for a diverse range of customers, including diagnostic laboratories, research institutes, pharmaceutical companies, and startups. Earlier, he was a research scientist at the German Cancer Research Center (DKFZ) and Heidelberg University Hospital, where he developed cell-based and biochemical high-throughput screening applications. Today, his team focuses on building connected, future-ready laboratories that elevate global productivity. By testing and integrating emerging technologies, developing and testing novel automation approaches, the team enables more flexible, scalable, robust, and innovative scientific research in a rapidly evolving environment.
Sven is Director Global Laboratory Automation at BioNTech, bringing more than 10 years of experience in automation development, including 5 years at BioNTech. He holds a PhD in Automation Science. In this role at BioNTech, he leads the company-wide advancement of laboratory automation across diverse laboratory environments and scientific disciplines, fostering harmonized, flexible, and future-ready infrastructures. Together with his team, Sven connects science and technology to enable integrated, connected, and automated laboratories
Tamara graduated with a BSc (Hons) in Chemistry, from the University of Witwatersrand. After graduating, she spent some time working as a process metallurgist for a Mining Research and Technology business before moving into the LIMS industry. She has behind her more than 22+ years’ experience in the laboratory information technology and services industry, where she held positions in Services, Sales & Strategic Accounts Management. Tamara joined Clinisys in May 2023 and is now the Director, Global LIMS Sales.
Ulmas Zhumaev, PhD, is a Lead Scientist in Central Analytics, an analytical chemistry services department supporting R&D at Merck KGaA, Darmstadt, Germany. Since joining the company in 2018, he has supported research projects across multiple business sectors, bringing deep expertise in surface science, spectroscopy, and advanced analytical methods. He is currently managing the implementation and rollout of the Uncountable platform within the department, supporting structured scientific data capture, improved workflow integration, and more data-driven analytical operations.
Matt joined Syngenta in 2019 and is currently a Principal Scientist in the Automation Team within the Bioscience function; developing innovative automation applications and maximising the utilisation of existing automated equipment. His previous roles in Biology and Formulation Chemistry involved high-throughput screening, upgrading existing automation and onboarding new automated systems.
Philippa has a long-standing interest in digital phenotyping and in using analysis of behaviour to understand the mechanism of action of chemicals. She joined Syngenta in 2009 after completing her PhD at the University of Southampton. She is currently a Principal Scientist in the Invertebrate Genetics team within the Bioscience function, where she is responsible for the C. elegans symptomology platform.
After completing his PhD in 2013 from “Sapienza” University of Rome, Claudio held postdoctoral positions at the University of Cambridge, working on innovative flow technologies and collaborating with major pharmaceutical companies.
In 2017, Claudio joined Syngenta as a Team Leader in Process Research, where he established flow chemistry as an enabling technology and led the creation of a global flow chemistry platform. In 2021 he was appointed Chemistry Automation Lead, focusing on operational leadership and automation initiatives.
In 2023 he took up the role of Transformation Lead Digital & Automation Prototype for Crop Protection Research, at Syngenta. Most recently, as of January 2024, Claudio has taken on the role of Digital Automation & IoT Lead for R&D, where he is responsible for driving the strategy across functions and leading change in the R&D organization. In this capacity, he also leads the cross-functional Microfluidics strategy in R&D.
Ulmas Zhumaev, PhD, is a Lead Scientist in Central Analytics, an analytical chemistry services department supporting R&D at Merck KGaA, Darmstadt, Germany. Since joining the company in 2018, he has supported research projects across multiple business sectors, bringing deep expertise in surface science, spectroscopy, and advanced analytical methods. He is currently managing the implementation and rollout of the Uncountable platform within the department, supporting structured scientific data capture, improved workflow integration, and more data-driven analytical operations.
Matt joined Syngenta in 2019 and is currently a Principal Scientist in the Automation Team within the Bioscience function; developing innovative automation applications and maximising the utilisation of existing automated equipment. His previous roles in Biology and Formulation Chemistry involved high-throughput screening, upgrading existing automation and onboarding new automated systems.
Philippa has a long-standing interest in digital phenotyping and in using analysis of behaviour to understand the mechanism of action of chemicals. She joined Syngenta in 2009 after completing her PhD at the University of Southampton. She is currently a Principal Scientist in the Invertebrate Genetics team within the Bioscience function, where she is responsible for the C. elegans symptomology platform.
Artificial intelligence has the potential to transform CMC. But, in order to realize this potential, we have to rethink how scientific knowledge is managed. Documents remain the industry’s primary way of communicating and exchanging CMC knowledge. But products, processes, materials, methods, and decisions don’t exist in documents. They exist as complex, interconnected relationships that evolve during the lifecycle of development. Documents are static snapshots of that knowledge represented as disconnected, narrative text. In this discussion, we advocate that network models are the preferred construct to represent the complexity of CMC knowledge. Network models are extensible and scalable, making them well-suited to manage the evolution of CMC knowledge and make this knowledge reusable for future programs. The digital transformation of CMC using network models requires a fit-for-purpose CMC data model exposed by an application layer that includes cross-functional workflow automation to support key activities such as digital product and process management, digital analytical procedure management, digital tech transfer, integrated quality risk management, and digital control strategies. We will discuss what this looks like in practice and how this approach drives operational efficiency across the lifecycle with real-world examples. Looking ahead, structured CMC knowledge is critical for the scalable deployment of AI to augment these complex workflows. With structured knowledge foundations, it is easier to build AI trust frameworks and credibility assessment plans and support the development of robust AI agents and prediction models that will accelerate the meaningful reduction in cycle times of development to get therapies to patients faster.
Bert is a Senior Fellow Architecture and Engineering at JnJ Innovative Medicine Technology R&D. That means he designs future proof solutions for the Global Sciences department, focusing on cloud-native implementations of systems that require High Performance Compute or require full integration. Bert has a background in Chemistry and Computer Science. During his 28-year career at JnJ he has spent 26 years in various IT departments. In his current position, Bert is predominantly focused on the Discovery (overall process, and In-silico design using Machine Learning) and the lab execution (Scientific Data Management) systems.
Yash Sabharwal, co-founder and CEO of QbDVision, brings over 25 years of experience solving complex problems within the life sciences industry. His journey includes co-founding Xeris Pharmaceuticals, a public company with approved treatments for severe hypoglycaemia and Cushing’s disease, and his first venture, Optical Insights, established in 1997 to develop sophisticated digital imaging solutions for biomedical applications. Before founding QbDVision, Yash served as the COO and CFO for Xeris Pharmaceuticals in its early years. During his later years at Xeris, when its lead program was being scaled for manufacturing, he identified a critical industry need for software tools to consolidate and standardize all CMC data and information generated throughout the product and process development lifecycle. In response, he launched the QbDVision project in 2017 to create a new category of software called Digital CMC. Today, QbDVision offers a comprehensive Digital CMC software platform to tackle operational hurdles across the drug development lifecycle from early-stage process development through commercial translation for pharmaceutical and biotech companies. The platform is currently being used by seven of the top 50 global therapeutics companies in the world as well as emerging biotech companies. Yash is widely recognized as a thought leader in digitally structured data management for CMC workstreams based on ICH guidelines and quality-by-design principles. He has contributed whitepapers, presentations, and recorded webinars on data governance and data integrity for prominent industry organizations, including Biophorum, PDA, the American Association of Pharmaceutical Scientists, and IFPAC. Yash holds a B.S. in Optics from the University of Rochester and M.S. and Ph.D. degrees in Optical Sciences from the University of Arizona.
Operationalizing AI in scientific research requires more than predictive models — it requires directly connecting in-silico design to experimental execution, both internally and with external partners. A continuous lab-in-the-loop cycle embeds AI into the discovery environment, where predictions inform experiments and results refine subsequent decisions
The loop extends beyond the internal lab, connecting in-silico designs with CROs, suppliers, and partners — with results returning in the context needed to support the next design cycle. Drawing on experience with Revvity’s Signals Xynthetica™ and Lilly TuneLab™ models, this talk will examine how this connected approach can impact discovery timelines and cross-lab coordination.
Robbert van Putten joined J&J in 2021 and currently employed as a Senior Scientist in High-Throughput Experimentation. In this role, he acts as the department’s Automation Lead and is responsible for lab automation and workflow optimization for J&J’s chemical process R&D teams.
With nearly three decades of experience in scientific software, David Gosalvez brings a rare combination of technical and domain expertise with broad knowledge across scientific use cases. He is a passionate advocate for improving the efficiency and quality of science via innovative software solutions. David works with scientists and IT across pharma and chemical industry to set the direction of the Signals Software portfolio. He also works with other scientific software vendors to integrate complimentary capabilities into our solutions. As Director of Cheminformatics, he was responsible for the sustained growth of ChemDraw and Spotfire® Lead Discovery. Previously, David headed the interdisciplinary Science & Technology team chartered with creating the novel data management technologies that currently underpin Signals Software’s Signals platform. David also served as Executive Director of Application Development at CambridgeSoft where he brought to market the Oracle Chemistry Cartridge and ChemBioOffice Enterprise Suite.
An innovative Scientist, Informatician and Technologist with over 25 years of experience in AI/ML, data science and advanced technologies as a Member and Leader of both R&D and IT groups, providing strategic direction and building diverse teams to support the design and development of novel drugs, across modalities and indications. Experienced working and collaborating with start-ups, not-for-profit organisations and large pharma at all levels including executive leadership, internal consulting, and non-executive & advisory board memberships.
I am a Business integrator and I am able to translate business needs into IT specifications coordinating multidisciplinary teams (business, lean sigma and IT/analytics), proposing solutions with TCO and ROI. With 20 years of experience spanning from basic research, Manufacturing, advanced Data Analytics and, more recently Digitalization and Business Consulting. I have developed advanced analytics solutions for top products like Keytruda, Gardasil, Bridion (on which he has co-authored 2 patents). I have Developed an investment roadmap for data monetization in manufacturing based on both compliance to ICH Regulations and practical business reporting and progressive analytics needs.
Jelrik Masson is a Senior Director, Europe LIMS Strategy at Veeva, educating and engaging companies on modernising quality control with Veeva LIMS. Veeva LIMS is a cloud-based SaaS LIMS solution built specifically for quality control environments in the life sciences industry. As a 25-year veteran of the Life Sciences industry, his career has spanned leadership roles in both sales and services at companies including PerkinElmer, Waters, and LabWare, where he managed the French branch. Before joining Veeva, he was a sales leader at SaaS firms L7 Informatics and Tetrascience. Jelrik possesses deep expertise in laboratory technologies such as LIMS, ELN, SDMS, LES, and data platforms
Holly’s career as an analytical chemist has spanned jobs at Novartis, GSK and the Francis Crick Institute, covering a range of environments from drug discovery to final product testing to metabolomics. Since joining AstraZeneca four years ago, Holly’s focus has been on improving analytical workflows and data quality using both software and hardware automation and integrating these analytical workflows into the Global AstraZeneca scientific ecosystem to enable acceleration of the DMTA cycle.
Holly’s career as an analytical chemist has spanned jobs at Novartis, GSK and the Francis Crick Institute, covering a range of environments from drug discovery to final product testing to metabolomics. Since joining AstraZeneca four years ago, Holly’s focus has been on improving analytical workflows and data quality using both software and hardware automation and integrating these analytical workflows into the Global AstraZeneca scientific ecosystem to enable acceleration of the DMTA cycle.
Kevin is a Senior Director for Technical Product Management at MSD Manufacturing Division, responsible for GxP lab instrumentation, connectivity & data availability for downstream consumption. During his 29 year career at MSD, he has led & managed varying at site & above site groups, working thru various QC, QA & technology adoption roles. He has current responsibility within the division’s human health supply labs for digital enablement of testing technologies.
Robbert van Putten joined J&J in 2021 and currently employed as a Senior Scientist in High-Throughput Experimentation. In this role, he acts as the department’s Automation Lead and is responsible for lab automation and workflow optimization for J&J’s chemical process R&D teams.
Agentic AI is transforming lab productivity – but what does that look like in practice? Join us for an engaging session with concrete use cases leveraging Agentic AI to move from reactive troubleshooting to proactive actions that can help prevent errors. See how autonomous AI agents can be used responsibly to automate key steps in life science research, uncover hidden patterns limiting lab throughput and enable scalability. The presented use cases will cover the scientific and operational impact, as well as the software and hardware foundations required to make them work. Whether you’re in pharma, biotech, or clinical labs, you’ll leave with concrete examples and insights to help you navigate your own AI journey.
Becky was appointed as the Pistoia Alliance’s first female President in June 2022. She is a long-time supporter of pre-competitive collaboration in life sciences and healthcare R&D and the critical role it plays in advancing science and is passionate about diversity in STEM. Becky is responsible for leading the Pistoia Alliance’s strategy and defining its future within areas of increasing importance to the industry, such as data standards, emerging technologies, diversity and inclusion, sustainability, and precision medicine. Becky first engaged with the Pistoia Alliance on its Lab of the Future project whilst at VWR (now part Avantor) where she worked for over a decade in sales, business development, and scientific services. From here, she joined the scientific instrumentation and analytical services company, Pion, as Managing Director, before moving to the Alliance as a project manager. She later became Chief Portfolio Officer and within this role established the Alliance’s first and thriving Diversity and Inclusion in STEM Leadership program. Becky re-joined the Alliance as President after a return to the commercial world as a Director at Impellam Group where she led the company’s STEM services strategy. Becky has a PhD in Biochemistry from Imperial College and an MBA from Cranfield University
With a background in Computer Science and Biomedical Engineering complemented by a successful track record of 10+ years in driving the development and implementation of Digital Strategies in the Life Sciences sector, Marco Ravot-Licheri brings a unique perspective on how to turn the promise of the Lab-of-the-Future into the reality of the Lab-of-Today. In his role as Head of Digital for Tecan’s Life Sciences Business, Marco is responsible for driving globally the Digital Strategy and Program and was deeply involved in defining & implementing Tecan’s Digital strategy, including spearheading the launch of the newest AI-native solutions bridging Agentic AI and Physical AI. Marco’s main areas of work include AI, ML, Data Science and UX applied to regulated environments.
Pharmaceutical R&D and manufacturing produce enormous amounts of scientific data, yet much of it is still underused: manually transcribed, trapped in proprietary formats, or never captured at all. The next generation of labs and factories will not be defined by adding another robot or another AI model, but by connecting the science that already happens: the measurement, the interpretation, the decision and the control. In this session, we will share real cases of workflow automation across discovery, development and advanced manufacturing, including closed-loop experimentation and LLM-assisted analytical workflows. We will explain a critical enabler that makes them scalable: a parser and connector approach that removes the ceiling on how much data we can ingest, leaving less and less dark data behind. Finally, we will use PIPAc, a project to build a compact, AI-piloted production unit, to illustrate workflow automation during the manufacture of a high-potency API, with the process controlled in real time through PAT and AI. Our argument is simple: great science does not come from any single machine. It comes from the right people, instruments, data and controls working together, with data integrity and governance built in from the start. When those elements connect, the result is not theory. It is faster discovery, better decisions and a more resilient path to new medicines.
Anna Codina is a seasoned scientific strategist with a career spanning academia, pharma, and industry. She has held key roles at Pfizer and Bruker, where she led initiatives in analytical science and biopharmaceuticals. Now at SciY, Anna focuses on driving digital transformation in life sciences, leveraging her deep technical expertise to accelerate innovation and operational excellence. She brings a unique perspective on how data-driven technologies are reshaping the future of drug discovery and development.
Experienced professional in biopharmaceutical industry with a strong background in analytical, formulation and process development for biologics. Experience includes successful global product, approval, launch and support of commercial supply chains in the areas of (immuno-)oncology (Keytruda, Adakveo), infectious disease (Zinplava), ophthalmology (Beovu), auto-immune disease (Ilumya, Cosentyx), allergy immunotherapy (Grastek/Ragwitek), multiple sclerosis (Ofatumumab) and fertility (Elonva, Puregon).
16+ years of experience in pharma industry, including 12+ year experience in leading a growing team of machine learning and data scientists and computational biologists and chemists who harness established and emerging high-dimensional data sources technologies by internalizing, developing and integrating advanced analysis and interpretation approaches in support of drug discovery.
With over five years of experience in pharmaceutical R&D and computational science, I currently serve as the Therapeutic Projects Data & AI Lead at Servier, where I focus on leveraging data analytics and artificial intelligence to drive innovation in oncology, neurology, and immuno-inflammation therapeutic areas. My role emphasizes creating advanced tools and methodologies in collaboration with internal and external stakeholders to support the concept phase in drug development.
Anna Codina is a seasoned scientific strategist with a career spanning academia, pharma, and industry. She has held key roles at Pfizer and Bruker, where she led initiatives in analytical science and biopharmaceuticals. Now at SciY, Anna focuses on driving digital transformation in life sciences, leveraging her deep technical expertise to accelerate innovation and operational excellence. She brings a unique perspective on how data-driven technologies are reshaping the future of drug discovery and development.
At J&J, I am responsible for the overall technology strategy, capability delivery, product development, and application life cycle management of the Laboratory Informatics landscape. My mission requires to partner across scientific functions that operate laboratories including the Discovery Product Development and Clinical Supply (DPDS) and the Therapeutic Area Research. My role involves collaborating closely with other Research & Lab platform leaders, JRD Business Technology Leaders, and business partners to attain the revolution of the end-to-end experimental execution platforms and increase the effectiveness and efficiency of laboratory science.
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.
Pavel Senin builds the agentic lab orchestration layer at Sanofi — the technical pipeline between scientific intent and robotic instruments in R&D. His work connects AI-driven experiment dispatch, instrument control, and operator governance into a single, traceable workflow, addressing the core challenge of moving from isolated automation to orchestrated lab operations. He chairs Sanofi’s relaunched Data Science Community of Practice, a practitioner network of over a hundred contributors spanning six organizations and ten countries. Pavel holds a PhD in Computer Science from the University of Hawai at Mānoa.
Nandini is a Practice Leader at Cognizant, where she works with global pharma organizations on R&D. A Biochemist with a PhD and 20+ years in pharmaceutical R&D, she built Cognizant’s CMC and Lab Informatics practice and advises clients on moving from brownfield labs to agentic AI. She writes on knowledge graph architectures on scientific AI.
AI is delivering validated drugs, not just predictions. This talk showcases how Insilico Medicine’s Pharma.AI platform moves from in silico design to experimental validation. First, TNIK / Rentosertib: the first drug where AI both discovered a novel target and designed the molecule. It reached a preclinical candidate for idiopathic pulmonary fibrosis in about 18 months and is now in Phase 3 clinical trials. Second, Generative Biologics: de novo peptide, VHH, and antibody designs validated in the wet lab, achieving hit rates of 15 to 30%. Together, these case studies show how AI and experimental feedback are compressing drug discovery timelines and turning predictions into therapeutics.
Mark Hahnel is the VP Open Research at Digital Science. He is the founder of Figshare, which he created whilst completing his PhD in stem cell biology at Imperial College London. Figshare currently provides research data infrastructure for institutions, publishers and funders globally. Mark sits on the board of DataCite and the advisory board for Directory of Open Access Journals (DOAJ) re3data and the Journal of Open Research Software (JORS).”
Andrew Aiginin is a product leader and AI drug discovery expert currently driving the research, development, and commercialization of a cutting-edge generative AI platform at Insilico Medicine in Abu Dhabi. As Product Manager, he successfully launched the Generative Biologics platform, from customer discovery through product development to market entry. Prior to joining Insilico’s product team, he served as a medicinal chemist, where he pioneered novel approaches using protein language models, graph neural networks, and advanced computational methods for biological drug design. As a former co-founder of a health-tech startup, he secured venture capital funding and built evidence-based drug intelligence systems and patient-facing digital health solutions. His technical expertise spans bioinformatics, computational drug design, and machine learning. With over a decade of experience across startups and research institutions, Andrew brings a unique combination of deep technical knowledge in drug discovery and proven product leadership skills. His interdisciplinary background and track record in both R&D and commercialization position him at the forefront of AI-driven therapeutic innovation.
Mark Hahnel is the VP Open Research at Digital Science. He is the founder of Figshare, which he created whilst completing his PhD in stem cell biology at Imperial College London. Figshare currently provides research data infrastructure for institutions, publishers and funders globally. Mark sits on the board of DataCite and the advisory board for Directory of Open Access Journals (DOAJ) re3data and the Journal of Open Research Software (JORS).”
AI is rapidly changing how scientists interact with data, knowledge, and each other. This talk shares a forward-looking vision for a digital intelligence companion in drug discovery that continuously integrates scientific work and organisational context, and discusses the journey towards making this concept a reality in modern R&D organisations.
Why realizing value from AI depends on a data strategy, fit for purpose governance, and new operating models.
How leading pharmaceutical organizations are using connected, AI-ready data ecosystems to improve scientific and business decisions across the R&D lifecycle.
An approach to increasing decision velocity that accelerates innovation, improves patient outcomes, and creates measurable business value.
Experienced professional in biopharmaceutical industry with a strong background in analytical, formulation and process development for biologics. Experience includes successful global product, approval, launch and support of commercial supply chains in the areas of (immuno-)oncology (Keytruda, Adakveo), infectious disease (Zinplava), ophthalmology (Beovu), auto-immune disease (Ilumya, Cosentyx), allergy immunotherapy (Grastek/Ragwitek), multiple sclerosis (Ofatumumab) and fertility (Elonva, Puregon).
Melanie Leveridge joined AstraZeneca in 2024 as Vice President of Assays, Profiling and Cell Sciences. In this role she leads a global team accountable for generation of cellular reagents, assay development, compound profiling and mechanism of action studies, partnering with the therapy areas to progress AstraZeneca’s discovery portfolio. Prior to her time at AstraZeneca Mel spent 19 years at GSK, in roles including Senior Director of Screening, Profiling and Mechanistic Biology and head of Global Sample Management. Mel serves as a board member for non-profit organisations supporting education and collaboration in the life sciences sector, including the Society for Lab Automation and Screening (SLAS), OneNucleus, and previously as chair of the board for ELRIG.
Dylan Maixner is Vice President of Consulting at Rancho BioSciences, where he helps life sciences organizations define, operationalize, and scale their R&D data strategies. He partners with R&D companies on enabling enterprise data strategies, operationalizing new governance structures, and preparing organizations for future process, technology, and skillset changes. Before joining Rancho, Dylan was part of Accenture’s Global Life Sciences practice, advising biopharma companies on data and digital transformation programs. His scientific experience includes research at the National Institutes of Health in the Laboratory for Human Neurogenetics and industry work developing a personalized genetic pain panel. Dylan holds a PhD in Pharmaceutical and Biomedical Sciences and an MBA from the University of Georgia, and a BS in Biology from the University of North Carolina at Chapel Hill.
James M. Vergis, Ph.D. is a Principal with Faegre Drinker Consulting and a member of the firm’s Life Sciences Consortium Management Team. He provides scientific and strategic consulting services to pharmaceutical and biotechnology organizations and leads collaborative initiatives across industry consortia, including the Enabling Technologies Consortium (ETC), Allotrope Foundation, ELSIE, and the IQ Consortium. Through his work with ETC, Jamie helps pharmaceutical companies identify shared technology gaps, develop consensus-based requirements, and establish partnerships with technology providers to accelerate the development and commercialization of innovative laboratory solutions. His work spans emerging analytical technologies, data standardization, artificial intelligence and machine learning applications, and collaborative technology evaluation programs designed to ensure new tools are fit for purpose for regulated pharmaceutical environments. This includes initiatives focused on advanced measurement technologies, data interoperability, and federated approaches to AI-enabled drug development. Prior to joining Faegre Drinker, James held scientific research positions in academia and government. He earned a B.S. in Biochemistry with a minor in Computer Science from SUNY Geneseo and a Ph.D. in Molecular Biophysics and Biochemistry from Yale University.
Jonathan is the Principal AI Product Manager at Apheris, where he works at the intersection of science, engineering, and drug discovery users to build AI applications that accelerate drug discovery. He holds a PhD in Organic Chemistry from the University of Oxford and transitioned into product management, combining his scientific background with a passion for developing impactful technology. Over the past seven years, Jonathan has led product development at BenevolentAI, Exscientia, and Recursion, focusing on the platforms and tools that empower drug discovery teams. His work centers on translating cutting-edge AI and computational methods into products that help researchers make better decisions and bring new medicines to patients faster.
I work at the intersection of computational chemistry, structural biology and machine learning, where I aim to bring co-folding models into practical use for structure-based drug discovery. With more than five years of experience supporting discovery portfolios and developing new technologies, I help translate structural and bioactivity data into actionable insights, enabling projects to progress from hit identification to lead optimization. This includes contributions to more than 10 projects across multiple therapeutic areas. My work is centered on co-folding, with a focus on pocket and binding mode elucidation, scalable virtual screening, fine-tuning and architectural improvements. I focus on making these models reliable and directly useful for decision-making in the drug discovery pipeline. I actively collaborate with the broader scientific community through initiatives such as OpenFold and AISB, contributing to the development and adoption of next-generation modelling approaches in drug discovery
What if designing a drug looked less like a solitary act of genius and more like building software as a team, with molecules proposed, tested, reviewed, and merged to a synthesis queue by humans and AI in the same loop? Agentic software development has become the reference case for human-AI collaboration: agents take on the tedious work while engineers focus on architecture and intent. Drug discovery shares this shape: an iterative, reviewable, in-silico design loop. Therefore, the same collaboration should be possible. At DeepCure, we built our AI-physics-based modeling to provide a fast and trustworthy in-silico testing framework, such that a molecule can be scored, filtered, and reviewed in timeframes relevant for agentic workflows. Around that oracle we also designed a shared workbench: our scientists and our AI agents work on one platform, with the same tools and data, and both can propose molecules, comment on designs, and review each other’s hypotheses. Left alone, each falls back on the familiar; together they push toward molecules neither would have drawn. We think this setup, not any single model, is where the real leverage lies.
Jonathan is the Principal AI Product Manager at Apheris, where he works at the intersection of science, engineering, and drug discovery users to build AI applications that accelerate drug discovery. He holds a PhD in Organic Chemistry from the University of Oxford and transitioned into product management, combining his scientific background with a passion for developing impactful technology. Over the past seven years, Jonathan has led product development at BenevolentAI, Exscientia, and Recursion, focusing on the platforms and tools that empower drug discovery teams. His work centers on translating cutting-edge AI and computational methods into products that help researchers make better decisions and bring new medicines to patients faster.
I work at the intersection of computational chemistry, structural biology and machine learning, where I aim to bring co-folding models into practical use for structure-based drug discovery. With more than five years of experience supporting discovery portfolios and developing new technologies, I help translate structural and bioactivity data into actionable insights, enabling projects to progress from hit identification to lead optimization. This includes contributions to more than 10 projects across multiple therapeutic areas. My work is centered on co-folding, with a focus on pocket and binding mode elucidation, scalable virtual screening, fine-tuning and architectural improvements. I focus on making these models reliable and directly useful for decision-making in the drug discovery pipeline. I actively collaborate with the broader scientific community through initiatives such as OpenFold and AISB, contributing to the development and adoption of next-generation modelling approaches in drug discovery
Trish joined Waters in 2022 and has been in laboratory informatics for over 25 years including CDS, LIMS, SDMS and ELN. Trish has led Waters cloud portfolio for the past three years and now is responsible for Waters current and next generation of NuGenesisTM SaaS solutions.
Danai Bili is the Lab Systems and Data Lead of Chemical Process R&D at Johnson & Johnson Innovative Medicine. She leads the implementation of digital transformation projects with the goal of creating an integrated, AI-powered ecosystem. In addition to this, Danai works closely with scientists, engineers, and technology teams to translate laboratory needs into robust, high trust data systems that support decision making. Her experience includes leading global and cross-functional technical projects, building AI solutions, and research at the intersection of machine learning and medical physics.
An innovative Scientist, Informatician and Technologist with over 25 years of experience in AI/ML, data science and advanced technologies as a Member and Leader of both R&D and IT groups, providing strategic direction and building diverse teams to support the design and development of novel drugs, across modalities and indications. Experienced working and collaborating with start-ups, not-for-profit organisations and large pharma at all levels including executive leadership, internal consulting, and non-executive & advisory board memberships.
Assia Ouanaya is an Associate Scientist in the Global Analytical Development Team at Merck KGaA, Darmstadt, Germany, based at the Biotech Development Center in Vevey, Switzerland. With a life sciences engineering background from EPFL, she has more than two years of experience working with robotic platforms in CMC development, supporting analytical methods activities. Her work focuses on enabling automation-driven approaches to improve efficiency, consistency, and throughput across biotech CMC development activities.
Thomas Xie is an Associate Scientist in the Global Drug Product Development Team at Merck KGaA, Darmstadt, Germany, based at the Biotech Development Center in Vevey, Switzerland. With a general engineering background with a focus on healthcare, he has two years of experience working with robotic platforms in CMC development, supporting formulation screening activities. His work focuses on enabling automation-driven approaches to improve efficiency, consistency, and throughput across biotech CMC development activities.
Sathya leads scientific data engineering and applied AI delivery at Zifo across the pharma development and manufacturing lifecycle. His work spans building and delivering solutions that turn raw scientific output into AI-ready data, through to delivering applied AI solutions on top of it. Over the last 20 months he has focused on using AI to accelerate delivery itself, compressing the time it takes to stand up the scientific data foundations that AI value depends on.
Arielle Rolland is a data strategist with deep expertise in data products and data mesh, and the founder of Arielle Rolland Advisory. She has global experience helping large enterprises unlock value through data product strategies, modern data stack implementation and governance frameworks. Her current engagement is with argenx as DT Data & AI Lead for TechOps and Quality, where she owns the data and AI strategy, operating model and roadmap across CMC, Quality and Supply Chain. She is currently completing an Executive MBA at London Business School.
Assia Ouanaya is an Associate Scientist in the Global Analytical Development Team at Merck KGaA, Darmstadt, Germany, based at the Biotech Development Center in Vevey, Switzerland. With a life sciences engineering background from EPFL, she has more than two years of experience working with robotic platforms in CMC development, supporting analytical methods activities. Her work focuses on enabling automation-driven approaches to improve efficiency, consistency, and throughput across biotech CMC development activities.
Thomas Xie is an Associate Scientist in the Global Drug Product Development Team at Merck KGaA, Darmstadt, Germany, based at the Biotech Development Center in Vevey, Switzerland. With a general engineering background with a focus on healthcare, he has two years of experience working with robotic platforms in CMC development, supporting formulation screening activities. His work focuses on enabling automation-driven approaches to improve efficiency, consistency, and throughput across biotech CMC development activities.
Sathya leads scientific data engineering and applied AI delivery at Zifo across the pharma development and manufacturing lifecycle. His work spans building and delivering solutions that turn raw scientific output into AI-ready data, through to delivering applied AI solutions on top of it. Over the last 20 months he has focused on using AI to accelerate delivery itself, compressing the time it takes to stand up the scientific data foundations that AI value depends on.
Arielle Rolland is a data strategist with deep expertise in data products and data mesh, and the founder of Arielle Rolland Advisory. She has global experience helping large enterprises unlock value through data product strategies, modern data stack implementation and governance frameworks. Her current engagement is with argenx as DT Data & AI Lead for TechOps and Quality, where she owns the data and AI strategy, operating model and roadmap across CMC, Quality and Supply Chain. She is currently completing an Executive MBA at London Business School.
What makes research rigorous and cumulative — so results hold up and each one builds on the last? As AI agents take on more of the scientific process, we are learning that what agents can do depends on what they stand on: curated, governed, machine-readable data they can reason over and act on across institutions and across years. A few principles do most of the work — computation captured in the data schema, not bolted on beside it; an executable context that can be branched and rolled back, so experimentation stays safe and reversible; and context complete enough that every result carries its own origin. These principles are already taking hold across neuroscience, precision medicine, and biotech, biopharma, and clinical research. The next decade will be remembered not for the agents but for the substrate underneath them. What are our agents standing on?
Gemma is a cheminformatician specialising in the computational representation of complex scientific data, with expertise spanning cheminformatics, knowledge graphs, and AI-driven scientific workflows. Following an early career in academia, she has led interdisciplinary teams across academia and industry to develop novel methods and open scientific databases, including widely used resources for representing enzyme reaction mechanisms and structure-function relationships, resulting in numerous publications. She later moved into early-phase drug discovery before joining pharmaceutical development, where her current focus is the Early Phase Stability Assistant (EPSA), an agentic AI platform for early-phase stability data.
As a Principal Engineer, I specialize in implementing Agentic AI and production-grade platform engineering for pharmaceutical R&D. My current focus is on embedding AI agents and LLM-assisted workflows into drug discovery pipelines, compressing development cycles and unlocking capabilities that were previously out of reach for science teams. I work closely with scientists, biologists, data engineers, and R&D leadership, bridging the gap between infrastructure and scientific outcomes.
Dr. Dimitri Yatsenko is the Founder and Chief Science & Technology Officer of DataJoint, where he leads the company’s scientific and technical vision. He holds a Ph.D. in Computational Neuroscience, with formal training in computer science and a background in systems engineering. Dimitri co-created the DataJoint framework while supporting computational neuroscience research at Baylor College of Medicine. Today, he works with pharmaceutical companies and research organizations to build reproducible, AI-ready scientific workflows that preserve the provenance, context, and integrity of scientific data and computational decisions. Dimitri’s work sits at the intersection of scientific computing, reproducible research, and AI infrastructure for the life sciences. He is helping leading research organizations establish the trusted scientific foundations that enable AI to accelerate discovery while ensuring scientific results remain reproducible, explainable, and defensible.
1. Why a successful AI pilot is only the beginning and what must be proven before deployment in a regulated laboratory. 2. How to benchmark AI performance beyond accuracy: reliability, consistency, traceability, exception handling, and scientist trust. 3. The change-management work that makes production adoption stick, across scientists, quality teams, processes, and governance.
Meriem Toudjine is a Digital & AI Transformation Strategy Leader at Sanofi, with 14 years of experience spanning pharmaceutical R&D, Manufacturing & Supply, Engineering and Digital Product Leadership.
Her career has evolved from engineering and technology delivery to enterprise-level strategy, giving her a distinctive perspective that combines a strong technical foundation with business, organizational and strategic thinking.
Today, Meriem focuses on how organizations can scale digital and AI transformation across complex and diverse enterprises, connecting strategy, operating model design, AI enablement, product thinking and measurable value creation.
At Sanofi, she contributes to shaping and scaling transformation strategies that help teams move from experimentation to adoption and, ultimately, enterprise-wide scale. Her approach connects technology, AI, people, ways of working and operating models to create sustainable impact. Her perspective is shaped by a career spent bridging technology, business and execution, and by a constant focus on how organizations can evolve to capture the full value of new technologies.
Her focus today is simple: turning vision into strategy, strategy into transformation, and transformation into sustainable impact at scale.
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.
My mantra to make decisions is this quote by Edwards Demings: “In God we trust and all others must bring data”. I have over 11 years of experience working with data. Recently, I was involved in the development of ontologies and data standardization strategies at Monsanto Research Centre, a subsidiary of Bayer Crop Science. In my previous roles I’ve been involved in bioinformaticis, data mining, data stewardship, data visualisation, the development of tools for querying structured and unstructured data and pipeline analytics.
