It’s time to stop thinking of AI as a standalone innovation and start embedding it into the daily workflows that define biologics discovery. #allinai #drugdiscovery #pharmatransformation

The shift from experimentation to execution is no longer optional, it’s the next frontier for competitive advantage in drug discovery. Organizations that master MLOps will unlock faster iteration cycles, greater scalability, and a smoother path to regulatory approval.

3️⃣ Regulatory readiness: AI solutions must meet strict reproducibility and interpretability standards to gain regulatory trust. 4️⃣ Cross-disciplinary teams: Scaling AI requires biologists, data scientists, and technologists to collaborate effectively.

1️⃣ Seamless integration: AI insights must fit into end-to-end workflows, not sit isolated in silos. 2️⃣ Data infrastructure: Scaling means ensuring robust, high-quality datasets to train and refine models.

Enter MLOps 🤯 A term that’s still almost unknown in our industry but poised to become one of the major enablers of the future. MLOps (Machine Learning Operations) isn’t just about deploying AI models; it’s about creating a robust framework that ensures:

We often celebrate groundbreaking AI models (and rightfully so), but the transformative potential of these technologies will only be realized with the ability to move fast and systematically test, improve, or discard models at scale.

While most in the industry are focusing on building exceptional AI models to accelerate drug discovery, I had the privilege of presenting at PEGS Europe on a topic that’s still overlooked but just as critical: overcoming barriers to AI adoption. A thread 🧵 #MLOps #drugdiscovery

People love working with Excel 💔, yet recently it cost a major company billions due to overlooked hidden tabs. Massive consequences for something so small! Maybe it’s time we consider more robust solutions that enhance accuracy, automate data collection, and reduce human error.

https://t.co/VyMK5jA6Ks

ImmunoInformatics is organizing a special focus on COVID-19 and computational immunology. Please spread the word in your network. Check it out here: https://t.co/5HlWCHP1NU

With ENPICOM’s new Antibody Discovery Module, candidate selection just got easier, better, and faster. Want to learn how and why? Then watch our live webinar and see this intuitive end-to-end solution in action. https://t.co/L96f7K2QKm #antibodies #drugdiscovery #drugdevelopment

The Princess Margaret Cancer Centre of the University Health Network has selected the IGX Platform to streamline the analysis and management of the vast amounts of immune repertoire sequencing data generated in their research and clinical studies.

If you haven't read yet our review on the progress and challenges in immune receptor sequencing and engineering in the recently published collection of papers on quantitative immunity in @RSC_MolEng, why not have a look now? https://t.co/FEutg3sFkK

The immuneSIM R package, a package for immune receptor repertoire simulation, is now also on CRAN: https://t.co/oyul5NS6fx. Fantastic work by @cedricrweber.

Our paper on repertoire-wide B cell phylogenetic analysis came out in @PNASNews today: https://t.co/RaCYzLv9Wp @EvolveDotZoo @skleinstein

immuneSIM, our immune repertoire simulator for benchmarking immune receptor tools is online: https://t.co/IAf7TKb8q9 We are already using it in several unpublished projects. Extensive documentation is available: https://t.co/u2GUc8JJst 1/3

In collaboration with Donjete Simnica et al. @UniHalle we discovered a lack of physiological T-cell clusters in patients suffering frm Autoimmune Cytopenia using TCR clustering algorithm GLIPH. A potential biomarker of autoimmune conditions. https://t.co/8yAfdylc2L @FrontImmunol

Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion https://t.co/5QsW88GaEy

We profiled the transcriptional landscape of young and older adults over five consecutive #influenza #vaccination seasons to identify signatures of vaccine response.

Our extensive review on computational and experimental analysis and engineering of adaptive immune receptor repertoires is out in @msde https://t.co/FEutg3sFkK. Amazing teamwork with @_Alex_J_Brown_ @isnapkov @pandaisikit @milenapavl @EnkelejdaMiho @SandveGeir