A reproducible, cloud-scale reanalysis of five peer-reviewed studies on cellular aging, reprogramming, and rejuvenation, and an honest account of what survived contact with a shared pipeline.
The headlines led with a 22,000-litre tank and a 99% cost drop. Here is a bioreactor engineer’s read on what Parima and Vow actually proved, why the media breakthrough matters more than the vessel, and the quiet shift that turned cultivated meat into a fermentation problem.
What happens when a bioreactor engineer points his state-estimation toolkit at football. Model90 is a statistical forecasting engine for the 2026 World Cup and the major leagues, built on Dixon-Coles Poisson, Elo, xG and a calibrated meta-model. An honest look at how it works and what its Brier score really means.
A Python CLI tool that strips background noise from any video file using ML denoisers — while copying the video stream byte-for-byte. A 6 GB 4K file processes in minutes instead of hours.
I rebuilt two published CHO cell-culture papers — a hybrid ODE + machine-learning growth model, and a genome-scale metabolic reduction pipeline — as an interactive digital twin that runs in the browser. Here’s how it works, what’s under the hood, and an honest take on what it’s good for. No hosted version yet; the code is on GitHub and a live instance is coming soon.
The Gap Between Models and Tools I’ve seen a lot of impressive ML models in biopharma that never get used. Not because the science is wrong, but because the tool doesn’t fit into anyone’s workflow. The model might be published in Nature Methods with beautiful receiver operating characteristic curves, but if a discovery scientist can’t… Read More: Building ML Tools Scientists Will Actually Use »
Why Trastuzumab Is the Perfect Test Case When I built my antibody developability predictor, I knew I needed to validate it against a molecule where we actually know the manufacturing story. Trastuzumab (Herceptin) was the obvious choice. It’s one of the most successful therapeutic antibodies ever made, with decades of manufacturing data behind it. More… Read More: Case Study: Predicting Trastuzumab Developability »
A bioprocess engineer’s journey into machine learning and why the pharmaceutical industry desperately needs this bridge When I tell people I work in bioprocess engineering, I usually get blank stares. When I explain that I help manufacture proteins in giant tanks for therapeutic use, the response is often: “Oh, like brewing beer?” Not quite. But… Read More: How I Built a Machine Learning Tool to Predict Drug… »