Explore every episode of the podcast The New Biology
| Title | Pub. Date | Duration | |
|---|---|---|---|
| Mark Budde - How to speed up wet-lab biology | 08 May 2026 | 00:57:32 | |
Plasmidsaurus took plasmid sequencing from $600 to $15 and turned a "boring" service company idea into a hugely successful company serving 70,000+ scientists. In this episode, CEO Mark Budde and Niko McCarty get into the bigger question: what does it take for companies to automate and scale wet-lab biology methods in the same way that Plasmidsaurus did for sequencing? They cover the early Oxford Nanopore bet, the obsession with speed, and why Mark won’t sell customer data to AI labs. This podcast is made possible by Astera Institute. | |||
| The Bitter Lesson for Biology — Adam Green on Virtual Cells and Scaling Laws | 12 Jun 2026 | 01:29:34 | |
Markov Biosciences, a startup in San Francisco, is betting that biology is about to have its GPT moment. In this episode, founder Adam Green explains the "bitter lesson" for biology, the idea borrowed from Richard Sutton that large unbiased datasets and the right training objective tend to outcompete models with hard-coded rules and human priors. Adam thinks, in particular, that the virtual cell field took a wrong turn by spending hundreds of millions of dollars collecting expensive perturbation data. Green’s counterargument is that the data needed to train useful virtual cells is not limiting, but rather compute (and the loss function) are. By treating single-cell RNA-seq as a ranking problem rather than raw counts (a century-old idea traceable to a 1927 psychophysics paper), they found that virtual cells pre-trained on plain observational data show clean scaling laws, getting monotonically better at predicting unseen perturbations as the models grow, and beating a state-of-the-art model built specifically for that task.
01:58 - The first clinical prediction from a virtual cell 05:38 - What is a "virtual cell," really? 08:01 - Single-cell RNA-seq biases and the urns analogy 23:29 - The bitter lesson for biology 30:55 - Geometric Plackett-Luce: the right loss function 59:26 Trop2 deep dive 1:11:16 - Top-down vs. bottom-up biology, mechinterp, and control as the goal
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| Magnet-Controlled Medicines — Andrew York & Maria Ingaramo | 29 May 2026 | 02:07:36 | |
Nonfiction Laboratories is building a technology called “magnetogenetics” that promises to control proteins inside the body — such as antibodies or enzymes — using small magnets. In this episode, co-founder Maria Ingaramo and scientific advisor Andrew York explain how they engineered a protein, MagLOV, that responds strongly to magnetic fields, why most prior attempts have failed to replicate, and how the mechanism of magnetically-controlled proteins actually works. They also get into the “dream” use cases, like cancer drugs that activate only at the tumor, which might have a lower toxicity inside the body. This podcast is made possible by Astera Institute. Notes from our discussion: https://nikomc.com/essays/protein-magnets.html 00:00 - Opening 00:54 — Introduction 01:35 — The dream 05:38 — Why magnets vs. light or ultrasound 10:05 — The physics 17:48 — On the name "magnetogenetics" 21:25 — Birds and cryptochromes 27:09 — Why is the field filled with so much junk? 29:51 — Adam Cohen's molecule 33:24 — Markus Meister’s debunking 38:06 — The experiment 46:22 — Finding the LOV domain 54:11 — Singlets, triplets, and cysteine 56:54 — What the magnet is actually doing 1:05:13 — The conformational-change red herring 1:12:46 — The Quantum Biology Institute 1:19:31 — Founding Nonfiction Labs 1:24:38 — How to convince skeptical investors 1:29:39 — What a magnetogenetic medicine might look like 1:38:50 — First clinical indications 1:45:12 — The regulatory path 1:48:01 — What the field needs 1:54:30 — Appendix: Whiteboard lecture | |||