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Vibrant healthtech cluster of Ghent – including BioLizard – featured in Labiotech
BioLizard is proud to be part of Ghent’s vibrant healthtech cluster, highlighted in Labiotech. The article showcases the city’s thriving biotech, medtech, and digital health ecosystem, where seamless collaboration drives innovation and supports cutting-edge life sciences research.
BioLizard joins the Pistoia Alliance
BioLizard has joined the Pistoia Alliance, a global life sciences network fostering pre-competitive collaboration to accelerate R&D. By sharing data, standards, and best practices, BioLizard will contribute to innovative, data-driven solutions alongside 200+ member organizations worldwide.
An Interview with BioLizard & Bridge Informatics CEOs Liesbeth Ceelen & Dan Ryder
BioLizard CEO Liesbeth Ceelen and Bridge Informatics CEO Dan Ryder discuss bridging biology and data science. Their teams help life sciences companies manage, integrate, and analyze complex data, accelerating drug discovery, biomarker development, and enabling more data-driven, patient-focused research.
Three best practices for applying machine learning in the life sciences
BioLizard shares best practices for applying AI in life sciences: avoid reinventing the wheel, integrate deep biological knowledge, and ensure high-quality, well-managed data. By following these steps, companies can harness AI effectively, avoid pitfalls, and generate actionable, data-driven insights.
Machine learning for protein engineering and design: Beyond AlphaFold
BioLizard shows how machine learning can go beyond AlphaFold for protein engineering. ML streamlines pipelines, predicts beneficial protein properties, optimises synthetic libraries, and accelerates personalised medicine, helping life sciences companies save time, reduce costs, and boost experimental success.
Three reasons why you should use machine learning for protein engineering and design
BioLizard highlights three reasons to apply machine learning in protein engineering: 1) uncover patterns in large protein datasets, 2) extract hidden insights from existing data, and 3) streamline production pipelines. ML boosts efficiency, reduces costs, and accelerates discovery in life sciences.
BioLizard hosts Bits in Bio Belgium meeting
BioLizard hosted the Bits in Bio Belgium meeting, bringing together 50+ attendees to explore AI and machine learning in life sciences. Talks highlighted data governance, pipeline optimization, and interactive ML tools, fostering networking and collaboration across the scientific community.
Effective use of AI in the life sciences: BioLizard weighs in at Knowledge for Growth
At Knowledge for Growth, BioLizard’s Volodimir Olexiouk joined a panel on AI in life sciences. Discussions focused on AI tools, success stories, pitfalls, and accelerating drug discovery, highlighting the need for both advanced AI and expert human guidance to maximize impact in biotech pipelines.
Creating a user-friendly and informative app that empowers colorectal cancer patients
BioLizard collaborated with Pierre Fabre Group to develop a user-friendly app for colorectal cancer patients, empowering them to manage their health. From concept to launch, the app reflects BioLizard’s vision of leveraging data to improve patient outcomes and quality of life.
BioLizard partners with Scaler8’s explore programme to unlock novel US market opportunities
BioLizard partners with Scaler8’s Explore Programme to expand into the US market. Leveraging Scaler8’s expertise and network, BioLizard aims to unlock new opportunities in biomedical and translational research, bringing advanced computational and predictive biological modeling to US clients.