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Webinar
During this webinar we explore emerging technologies that hold the potential to accelerate experimentation in life science and biopharma R&D.
Achieving data interoperability is fundamental for successful FAIR data initiatives, and the utilisation of ontology and terminology standards plays a crucial role in this endeavor. In this webinar, we delve into the landscape of ontology mapping, exploring existing mapping sets and innovative approaches to generating and maintaining ontology mappings.
During this webinar we will demonstrate how using a common, machine-readable data format will enable a digital transfer of analytical High Performance Liquid Chromatography (HPLC) instructions between chromatography data systems (CDS).
In this talk, we will discuss the state of digitalisation in in vivo research, explain why this phase of drug discovery is called the “final frontier”, and will examine actual requests from pharmaceutical and biotech companies when tasked with bringing new software into their existing technology stack to meet modernisation initiatives.
In this webinar, will be teaching the inner workings of Kazu, and how you can use and configure it for your own use cases.
The goal of our project is to build an IDMP Ontology that enables deep, semantic interoperability based on FAIR principles to enhance and augment the existing ISO IDMP standards
This webinar aims to explore the application of large language models in life science R&D from different perspectives, providing attendees with a comprehensive understanding of the topic and its potential implications for the industry.
In this talk, we will discuss the opportunities large language models and other medical foundation models offer in terms of providing a better paradigm of doing “AI in healthcare.”
The Swiss Personalized Health Network (SPHN) has created a national framework for standardizing the semantic representation of health data, in alignment with the FAIR principles.
Large scale implementation of FAIR is often hampered by legal, technical, financial or organizational challenges. Creating a FAIR ecosystem requires that the infrastructure for data capture not only enables but also ensures that data is FAIR right at the point of creation (FAIR@source).
The Ersilia Open Source Initiative is a non-profit organization with the mission to equip laboratories and universities in low resource areas with AI tools for infectious disease research.
Superbio.ai provides datasets, pre-trained AI models, benchmarks, visualization and inference tools, all in a no-code cloud environment, empowering scientists to advance their research with community-driven machine learning. In this webinar, company founder and CEO Berke Buyukkucak will describe his work to democratize the Artificial Intelligence.
