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1. Transforming Real-World Data into Structured, Usable Intelligence: Using our enterprise-level RWD ecosystem, Zephyr built PRISM—an AI-enabled clinical inference engine that converts messy, multi-modal patient data into structured, inference-ready patient journeys. PRISM unlocks the full potential of RWD for scalable clinical insights, machine learning development, and validation.


2. Multi-Modal AI for Predictive Modeling and Expression Reconstruction: Zephyr’s AI models predict drug response and reconstruct gene expression from clinically available inputs such as NGS data from commercial LDTs and whole-slide images (WSI). These capabilities enable retrospective validation of treatment predictions across oncology, linking molecular and clinical outcomes in real-world settings.

3. Partner-Ready Software for Rapid Co-Development and Clinical Integration: Zephyr’s foundation models can be fine-tuned for new assets, diagnostics, or therapeutic areas using partner data—delivering bespoke, AI solutions that integrate as software directly into existing R&D and clinical workflows. Our infrastructure also supports rapid clinical intelligence queries and cohorting, empowering data-driven decision-making from discovery through commercialization.

Author:

Anshu Jain, MD

Chief Business and Clinical Officer
Zephyr AI

Dr. Anshu Jain is Zephyr AI’s Chief Business and Clinical Officer. A double board-certified radiation oncologist and clinical informatician, he leads business development, clinical strategy, medical affairs, and partner collaborations—translating Zephyr’s AI and large-scale real-world data into solutions that help biopharma and diagnostic partners advance precision medicine for patients. Prior to Zephyr, Dr. Jain served as Chief Medical Officer at Aster Insights.

Dr. Jain has authored peer-reviewed publications in Nature Communications, Journal of Clinical Oncology (JCO), and JCO Clinical Cancer Informatics, and has served as a principal investigator for early- and late-phase oncology trials. He has advised the FDA Office of the Commissioner and the Oncology Center of Excellence, and provided clinical leadership to large-scale data initiatives including the NCI SEER program.

He serves on the Board of Directors of the Community Oncology Alliance, the Board of Advisors for the Duke Cancer Institute, and is an Assistant Professor at the Yale School of Medicine.

Dr. Jain trained in internal medicine and radiation oncology at the Massachusetts General Hospital and Columbia New York Presbyterian Hospital. He earned his M.D. with Highest Distinction from the University of Kentucky College of Medicine and a degree in Economics from Duke University.

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Anshu Jain, MD

Chief Business and Clinical Officer
Zephyr AI

Dr. Anshu Jain is Zephyr AI’s Chief Business and Clinical Officer. A double board-certified radiation oncologist and clinical informatician, he leads business development, clinical strategy, medical affairs, and partner collaborations—translating Zephyr’s AI and large-scale real-world data into solutions that help biopharma and diagnostic partners advance precision medicine for patients. Prior to Zephyr, Dr. Jain served as Chief Medical Officer at Aster Insights.

Dr. Jain has authored peer-reviewed publications in Nature Communications, Journal of Clinical Oncology (JCO), and JCO Clinical Cancer Informatics, and has served as a principal investigator for early- and late-phase oncology trials. He has advised the FDA Office of the Commissioner and the Oncology Center of Excellence, and provided clinical leadership to large-scale data initiatives including the NCI SEER program.

He serves on the Board of Directors of the Community Oncology Alliance, the Board of Advisors for the Duke Cancer Institute, and is an Assistant Professor at the Yale School of Medicine.

Dr. Jain trained in internal medicine and radiation oncology at the Massachusetts General Hospital and Columbia New York Presbyterian Hospital. He earned his M.D. with Highest Distinction from the University of Kentucky College of Medicine and a degree in Economics from Duke University.

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.

Author:

Tobias Hahn, PhD

R&D Director, GoSilico
Cytiva

Tobias Hahn is R&D Director of chromatography mechanistic modeling activities at Cytiva. As former co-founder and CEO of GoSilico, now part of Cytiva, Tobias is responsible for delivering simulation software and workflows for in silico process development. He received his undergraduate education in computational mathematics and technical physics in Karlsruhe and Stockholm, earning his PhD in chemical engineering from Karlsruhe Institute of Technology (KIT). During his doctoral studies, he utilized his background in mathematics and software engineering to create the simulation software now known as GoSilico™ chromatography modeling software.

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Tobias Hahn, PhD

R&D Director, GoSilico
Cytiva

Tobias Hahn is R&D Director of chromatography mechanistic modeling activities at Cytiva. As former co-founder and CEO of GoSilico, now part of Cytiva, Tobias is responsible for delivering simulation software and workflows for in silico process development. He received his undergraduate education in computational mathematics and technical physics in Karlsruhe and Stockholm, earning his PhD in chemical engineering from Karlsruhe Institute of Technology (KIT). During his doctoral studies, he utilized his background in mathematics and software engineering to create the simulation software now known as GoSilico™ chromatography modeling software.

Author:

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. 

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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. 

Author:

Andrew Brooked

Chief Technical Officer & Co-Founder
Faculty

Andrew leads Faculty’s technical teams and developed the backbone of Faculty’s AI operating system, Frontier. His accomplishments span building the NHS Covid Early Warning System and mission critical projects for the UK Ministry of Defence. Before Faculty, Andrew led an engineering team at investment management firm BlackRock. He holds a Master’s degree in Computer Science from the University of Warwick.

 

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Andrew Brooked

Chief Technical Officer & Co-Founder
Faculty

Andrew leads Faculty’s technical teams and developed the backbone of Faculty’s AI operating system, Frontier. His accomplishments span building the NHS Covid Early Warning System and mission critical projects for the UK Ministry of Defence. Before Faculty, Andrew led an engineering team at investment management firm BlackRock. He holds a Master’s degree in Computer Science from the University of Warwick.

 

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.

Author:

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.

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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.

Author:

Selene Sass

Technology Product Manager
Johnson and Johnson

Selene is a technology product manager at Johnson & Johnson with nearly five years supporting the Advanced Computing and Analytics team. Her primary focus is to empower R&D scientists with emerging and innovative technologies in the advanced computing space, including the integration of quantum computing within J&J. Currently, she supports groups working in AI/ML and is exploring how quantum computing techniques can further enhance these capabilities. 

... read more

Selene Sass

Technology Product Manager
Johnson and Johnson

Selene is a technology product manager at Johnson & Johnson with nearly five years supporting the Advanced Computing and Analytics team. Her primary focus is to empower R&D scientists with emerging and innovative technologies in the advanced computing space, including the integration of quantum computing within J&J. Currently, she supports groups working in AI/ML and is exploring how quantum computing techniques can further enhance these capabilities. 

  • Learn how AI analyzes patent and R&D data to identify chemical trends, aiding in compound optimization.
  • Discover how integrating diverse data sources streamlines the optimization of drug candidates, enhancing decision-making.