Zephyr AI
Website: https://www.zephyrai.bio/
Zephyr AI is a precision-medicine company unifying enterprise-scale real-world data with multi-modal AI to deliver actionable, biologically interpretable insights across the therapeutic lifecycle—from discovery to clinical deployment. Our software-native, AI-enabled modules predict drug response and reconstruct gene-expression signatures from clinically available DNA-based inputs and drug metadata, and can be fine-tuned to novel therapeutics or diagnostics. Pilots stand up in weeks, informing patient stratification, trial optimization, label expansion, and indication discovery.
Nexus, our SOC 2/HIPAA-aligned data and compute infrastructure, powers rapid cohort construction, synthetic control arms, and real-world validation with intervention-specific risk modeling. Through Aster Insights™ and the ORIEN Total Cancer Care® study, Zephyr provides access to deeply annotated oncology assets—lifetime-consented patients with linked clinical, exome, transcriptome, and whole-slide imaging—to enable fit-for-purpose data generation. We partner with biopharma, diagnostics, and digital-pathology leaders, integrating seamlessly into existing workflows with no new assays required. Together with a rigorous validation engine grounded in real-world outcomes, Zephyr bridges experimental and clinical domains to extract signal from heterogeneous data, de-risk development, and bring effective therapies to patients sooner. Our mission is to make precision medicine accessible and immediate—turning fragmented data into confident, patient-impacting decisions at scale.
Data powers the engine of artificial intelligence (AI), but not all data is created equal. While software capabilities are rapidly accelerating, the biopharma industry still largely lacks the intelligent hardware needed to generate clean, contextualized, and high-quality data that AI and machine learning (ML) models require to deliver on their promise.
Explore how today’s in silico process development tools for bioreactor scaling and mechanistic modeling of chromatography can help you get it right the first time now, and why the next generation of intelligent hardware will be critical to unlocking the full potential of AI/ML in biopharma.
Tobias Hahn, PhD
R&D Director
GoSilico
Tobias Hahn is R&D Director of chromatography mechanistic modeling activities at Cytiva. As former co-founder and CEO of GoSilico, now part of Cytiva, Tobias is responsible for delivering simulation software and workflows for in silico process development. He received his undergraduate education in computational mathematics and technical physics in Karlsruhe and Stockholm, earning his PhD in chemical engineering from Karlsruhe Institute of Technology (KIT). During his doctoral studies, he utilized his background in mathematics and software engineering to create the simulation software now known as GoSilico™ chromatography modeling software.
Cilon Li
Sr. Director of Engineering, Digital Products Development
Cytiva
Cilon Li is a digital and IT executive with over 15 years of experience in healthcare and biopharma. He is a strategic leader with a proven track record in driving digital transformation across supply chain management, product management, and R&D. At Cytiva, Cilon drives the company’s digital strategy and expanding product portfolio, encompassing Internet of Things (IoT), data analytics, AI/ML, software as a service (SaaS) and enterprise applications to help customers progress their digital biomanufacturing journeys.
Cytiva
Website: https://www.cytivalifesciences.com/about-us
Cytiva is a global life sciences leader dedicated to helping customers discover and commercialize the next generation of therapeutics. Together, we bring dedicated technical expertise and a broad portfolio of tools and technologies that enable the development, manufacture, and delivery of transformative medicines to patients. Visit cytiva.com to learn more.
Faculty AI
Website: https://faculty.ai/
Founded in 2014, Faculty is one of Europe’s leading applied AI companies. Our suite of AI services and products helps organisations design, build, and deploy high-performing AI solutions that deliver measurable impact for their frontline teams. Faculty is also the developer of Faculty Frontier™, a Decision Intelligence platform used by leading pharmaceutical companies to transform decision-making at scale.
Widely recognised as a leader in AI safety, we work closely with the world’s top AI labs, such as OpenAI and Anthropic, to ensure their latest models are safe, human-led, and explainable. Our expertise spans advising Boards, leadership teams, and governments on AI strategy; delivering AI systems that improve critical public services and business outcomes; and equipping organisations with the knowledge and skills they need to thrive in the AI era.
Our PhD-heavy team has delivered hundreds of real-world AI projects across every sector of the economy. Headquartered in London, Faculty remains founder-led and has raised over £40m from investors including The Apax Digital Fund, LocalGlobe, and GMG Ventures.
Advanced computing is a strategic imperative for pharmaceutical innovation. The industry is at a point where traditional computational methods are no longer sufficient to solve the increasingly complex problems in R&D and operations. Embracing technologies like quantum computing and HPC is critical for maintaining a competitive edge and driving breakthroughs.
A hybrid approach is essential for a complete solution. No single technology is the silver bullet. The most effective solutions come from using the right tools—be it classical, quantum, or quantum-inspired—and combining them into a single, powerful workflow to maximize efficiency and impact. This approach allows companies to apply the best technology to a wide range of problems across the business, not just in drug discovery.
Strategic partnerships are key to capability building. For a large enterprise like J&J, the path to adopting these advanced technologies is best navigated through collaboration. Working with a specialist like Strangeworks bridges the knowledge gap, provides access to powerful platforms, and helps overcome organizational hurdles. The ultimate goal of this collaborations like these is to be able to empower J&J's internal teams to become self-sufficient pioneers of innovation.
Steve Gibson
Chief Commercial Officer
Strangeworks
Steve has held a range of C-Suite positions in technology companies ranging from financial technology services, to data science consulting. Currently he serves as Chief Commercial Officer at Strangeworks; an advanced compute platform as a service (PaaS) company based in Austin, Texas. Prior to Strangeworks, Steve helped build several startups from the ground up, the most successful being Honest Dollar which was the first startup acquired by Goldman Sachs in their 147 year history. Prior to Honest Dollar, Steve worked for a number of large multinational corporations in the European aerospace sector delivering platforms for military, civil and space applications. Steve holds a Bachelor’s degree in Aerospace Systems Engineering from the University of Coventry in the UK.
Strangeworks
Website: https://strangeworks.com/
Strangeworks is on a mission to turn computational complexity into real world solutions. With the largest catalog of quantum and quantum-inspired computing resources on an innovative cloud platform backed by computational experts, we make the transformative potential of quantum computing accessible to all. Our AI powered workflows make it easier for enterprises to solve today’s toughest challenges, accelerate breakthroughs, and future-proof their operations. Partnering with customers worldwide, Strangeworks delivers immediate ROI while shaping a smarter, quantum-enabled future.
Helix AI
Website: https://helixai.com/
HelixAI is a specialist scientific technology company focused on accelerating research and development for biopharmaceutical organizations. Its platform, JarvisAI, enables scientific teams to design and execute in silico R&D workflows that support a wide range of operations from early-stage drug discovery to scale-up and bioproduction. By integrating scientific data from public, private and client domains along with computational models and AI-driven orchestration, JarvisAI helps researchers explore hypotheses more efficiently and prioritize the most promising drug candidates for further development. This approach supports better, faster decision-making combined with optimization of scientific and wet-lab resources.