Hub & Spoken Podcast: How artificial intelligence plays a role in developing life-saving drugs

BioLizard’s Volodimir Olexiouk joins the Hub & Spoken podcast to discuss how AI is revolutionizing drug discovery. Explore how data-driven innovation accelerates life-saving therapies and reshapes the future of healthcare and biotechnology. Listen to the full episode now.

Volodimir Olexiouk, our Director of Scientific Engagement and Data Science Team Lead, was featured on episode 205 of Cynozure‘s Hub & Spoken podcast.

In this episode, Cynozure CEO and podcast host Jason Foster speaks with Volodimir about the revolutionary intersection of artificial intelligence and pharmaceuticals, exploring how AI is transforming the landscape of drug discovery.

Tune in now and gain insights into the innovative ways AI is transforming drug discovery and shaping the future of healthcare and biotechnology.

Want to learn more about how leveraging artificial intelligence can support your research & development activities? Check out our white paper about how you can use machine learning to develop better biomarkers – a powerful tool for de-risking drug discovery projects.

How spatial biology improves clinical trial success in oncology

How spatial biology improves clinical trial success in oncology

In oncology, the drug development path is unique: Phase 0 and Phase I trials are typically conducted in patients rather than healthy volunteers, allowing for early assessment of efficacy and patient selection alongside safety. Yet, even with this early clinical insight, many cancer drugs show promise in the lab but fail to transition effectively into the clinic. This often happens because, while we verify that a drug’s target is present, we frequently overlook its context, specifically its location, the surrounding microenvironment, and its interaction with neighboring cells. By revisiting real-world examples of discontinued trials, this post explains why understanding the “where” is just as critical as the “what”, and how spatial biology is positioning itself as a valuable avenue for validating clinical potential.

Why bioinformatics workflows require experienced software engineers

Bioinformatics pipelines break for the smallest reasons: package updates, shifting dependencies, or “it only works on my machine.” This post explains why experienced software engineers and DevOps practices (Git, CI/CD, IaC) are essential to keep workflows reproducible, stable, and scalable.