Manchester-based Imperagen has secured £5 million in seed funding to expand its AI-driven enzyme engineering platform. The company aims to accelerate R&D and scale operations, targeting applications across pharmaceuticals, life sciences, and sustainable chemicals.
Imperagen has secured £5 million to advance the use of quantum physics and artificial intelligence in enzyme engineering. The funding aims to accelerate the development of custom enzymes with potential applications in biotechnology and life sciences.
The BioInnovation Institute (BII) has launched the AI Lab, an initiative to support and accelerate early-stage AI startups in Denmark, with €7 million in funding from the Danish Industry Foundation. The programme offers funding, infrastructure, and industry connections to help turn AI research into market-ready solutions.
OpenAI has introduced GPT-Rosalind, a specialized AI model designed for the challenges of life sciences research. The model aims to assist researchers in integrating fragmented biological data and generating refined scientific hypotheses, with early performance benchmarks indicating better results than previous models for complex research workflows.
OpenAI has introduced GPT-Rosalind, a large language model tailored for biology research workflows. The model is trained on key biological processes and integrates access to major biological databases, supporting researchers in data analysis and hypothesis generation.
OpenAI has introduced GPT-Rosalind, a large language model specifically trained for biological research and workflows. The model aims to assist researchers in managing vast biological datasets and understanding complex, specialized subfields. GPT-Rosalind is designed to streamline tasks such as exploring biological pathways and prioritizing drug targets.
Life sciences organizations face mounting pressure to support advanced AI systems amid lagging digital infrastructure. Experts highlight critical strategies for aligning AI workloads, data storage, and adaptive architectures to realize the potential of automation and generative AI. Robert Wenier of AstraZeneca outlines practical steps for overcoming operational bottlenecks.
AI-enabled predictive cost forecasting is transforming the life sciences and pharmaceutical industries. By leveraging data-driven models, companies can manage demand gaps and optimize spending. This shift is helping organizations address rising costs and supply chain complexities.
Life sciences companies face significant challenges in scaling generative AI due to insufficient data maturity and fragmented data sources. Experts highlight the need for robust data infrastructures, standardized evaluation benchmarks, and organizational alignment to unlock the full potential of AI in R&D workflows.
Switzerland's tech ecosystem demonstrated robust performance in 2025, securing €3.3 billion in startup funding with a notable emphasis on deep technology, life sciences, and industrial AI. Investments were highly concentrated among science-driven sectors, strengthening Switzerland's role as a leading European innovation hub. The country's startups showed particular strength in areas such as energy storage, fintech, climate technology, and medtech.
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