Explore our

Spatial transcriptomics bridges the gap between gene expression and tissue context by mapping transcripts to their exact location. By revealing cell interactions, microenvironments, and spatial gene patterns, it provides powerful insights, especially when paired with scRNA-seq.

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.

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.

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.

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.

Volodimir Olexiouk leads BioLizard’s Data Analytics & AI team, combining deep biology, bioinformatics, and machine learning expertise. The team collaborates across disciplines to transform complex biological data into actionable insights, accelerating R&D and creating measurable value for clients.

Alexander Koch, BioLizard’s Bioinformatics Team Lead, combines deep expertise in genomics, transcriptomics, and data visualization to deliver tailored bioinformatics solutions. His team tackles diverse omics projects, collaborating across teams to transform complex data into actionable insights for clients.

Yves Muyssen, BioLizard COO and Data Management lead, leverages his expertise to help life sciences clients tackle complex R&D data challenges. By assembling cross-functional teams and implementing FAIR principles, BioLizard ensures data is structured, accessible, and ready for AI-driven insights.

BioLizard’s Software & IT Architecture team, led by Erik Vandeputte, helps life sciences companies boost efficiency and scalability by bridging IT, biology, and data science. They design robust software, cloud infrastructure, and workflows, turning complex biological data into actionable, data-driven insights.

BioLizard helps life sciences organizations maintain effective R&D data management plans, ensuring FAIR, compliant, and scalable data practices. By training internal data stewards and designing systems that handle routine tasks automatically, teams save time, reduce errors, and unlock AI-driven insights.