11 June, 2025

New Research Publication: Building Reproducible RWD Pipelines for Clinical Decision Support

Published in PLOS ONE – Supported by ChemAI

We’re excited to share that work supported by ChemAI has been published in PLOS ONE, highlighting a significant advancement in the field of real-world health data (RWD) infrastructure for clinical decision support systems.

Read the full article here: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0324205

Collaborative Innovation in Action
The study, led by researchers at Sanofi, presents a modular, transparent framework designed to enhance the reproducibility, traceability, and auditability of clinical data pipelines. As healthcare increasingly relies on data-driven systems, the need for reliable, version-controlled workflows has become essential – particularly in regulated environments where decisions impact patient care.

A central component of this work is the use of SmartChemistry® Optimiser, a decision support engine licensed from ChemAI, which enabled rigorous data processing and transformation throughout the pipeline. Our CTO, Thomas, contributed to the project by supporting the design and implementation of technical components that ensure end-to-end reproducibility and real-world applicability.

Why This Matters
Ensuring reproducibility in health data science isn’t just an academic concern – it’s foundational for building trustworthy AI tools that can be used safely and effectively in clinical settings. This framework lays the groundwork for:

Transparent lineage of data transformations
Modular, maintainable pipeline architectures
Scalable deployment in both research and production environments
Alignment with compliance and regulatory standards

The publication also includes a case study using simulated hospital data to demonstrate how the framework operates in a realistic clinical context.

Looking Ahead
This work exemplifies how collaboration between industry partners, combining domain expertise, technical tooling, and shared commitment to scientific rigor, can help push the boundaries of what’s possible in digital health and AI.

We’re proud to see ChemAI technology playing a role in shaping the future of reproducible, data-driven healthcare.

27 November 2024

AI-Driven Digital Chemistry Pioneer announces Strategic Rebrand and Key Board Appointments

Deepmatter, a leading innovator in digital chemistry, today unveils its rebrand to ChemAI, as part of a strategic growth plan to revolutionize the future of chemistry with artificial intelligence (AI). The rebrand reflects the company’s vision to empower scientists with advanced AI tools that redefine chemical discovery and manufacturing.

Over recent years, ChemAI has developed and commercialised a suite of AI-driven tools that enable chemists to dramatically improve the efficiency and cost-effectiveness of synthetic routes and formulations. These tools also uncover novel and innovative synthetic pathways. The AI is underpinned by access to proprietary data: a comprehensive and growing chemical database of over 23 million chemical reactions.

Already collaborating with leading pharmaceutical, biotech, and cosmetic firms, ChemAI’s rebranding underscores its mission to harness AI and data-driven innovation to transform the discovery, development, and production of chemical products.

In conjunction with its rebrand, ChemAI announces significant additions to its Board of Directors to support the company’s next growth phase:
Dave Norwood has been appointed Chairman. A seasoned leader in deep-tech and life sciences, Dave is the founder of IP Group PLC and Oxford Science Enterprises, which has driven over £1.5 billion in investments into Oxford since 2015. He also co-founded Oxford Nanopore, a global leader in DNA sequencing, among other notable UK tech companies.

Tony de Fougerolles, PhD has joined as a Non-Executive Director, bringing over 25 years of experience in biotechnology R&D, most recently CEO of Evox Therapeutics. Tony previously served as CSO at Ablynx, where he contributed to the approval of caplacizumab, the first single-domain antibody drug, and advanced immunology and oncology pipelines. As founding CSO at Moderna, he pioneered the foundational mRNA science that underpins the entire sector including the approved mRNA vaccines. He also held leadership roles at Tolerx and Alnylam. Tony serves on the boards of Etherna, Chimeron Bio, Helfie AI and Lift Biosciences. He earned a PhD in Immunology from Harvard and a BSc from McGill.

Commenting on these developments, Dave Norwood, Chairman, said:

“The rebrand to ChemAI reflects our bold ambition to redefine the role of data and AI in chemistry. By combining a visionary approach with a strengthened leadership team, ChemAI is well-positioned to drive transformative change and unlock unprecedented opportunities in the chemical and pharmaceutical industries.”

Tony de Fougerolles, Non-Executive Director, added:

“I’m thrilled to join ChemAI at such an exciting juncture. The company’s AI-powered platform has immense potential to accelerate innovation and improve efficiencies across the chemical ecosystem. Our approach to AI won’t replace chemists entirely, but chemists using our tools will be immeasurably more productive and creative than those that don’t”

ChemAI’s rebrand and new Board appointments underscore its commitment to empowering researchers, manufacturers, and innovators with tools that enhance productivity, sustainability, and innovation. As ChemAI, the company remains steadfast in its mission to create a world where data and AI-driven chemistry fuel solutions for global challenges.

About ChemAI
ChemAI (formerly Deepmatter) is a UK-based privately held technology company leading innovation in digital chemistry. Leveraging AI, machine learning, , ChemAI optimizes chemical research and manufacturing, driving breakthroughs across the chemical, pharmaceutical, and material science industries. Its proprietary platform combines proprietary chemical reaction data, large language model (LLM)-enabled data extraction tools, and domain-specific AI for route prediction, reaction optimization, and automation control.

For more information, visit chemai.io or contact jenny.hand@chemai.io