The New Biology Transistor (https://transistor.fm) https://feeds.transistor.fm/the-new-biology The New Biology features long-form discussions with historians, technologists, and scientists who are working on some of the biggest ideas in biotechnology, from magnet-controlled medicines to virtual cells. Supported by Astera Institute. © 2026 Niko McCarty 31a0fa18-744b-54ac-bc9e-ecf887d45867 yes en Tue, 04 Aug 2026 12:45:55 -0700 Tue, 04 Aug 2026 12:46:28 -0700 https://img.transistorcdn.com/hAo0G-JjrmcZZfEfQhneJHE44MKbohGaiLjJQ8u6dOc/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9jYTRi/NTg1Yzc3YmRiZjg1/ZjNmYmNkNjAyYjFl/NjllMS5qcGc.jpg The New Biology episodic Niko McCarty The New Biology features long-form discussions with historians, technologists, and scientists who are working on some of the biggest ideas in biotechnology, from magnet-controlled medicines to virtual cells. Supported by Astera Institute. The New Biology features long-form discussions with historians, technologists, and scientists who are working on some of the biggest ideas in biotechnology, from magnet-controlled medicines to virtual cells. Biology, Science, Technology Nicholas McCarty No No Biotech for Chickens — Robert Yaman 5 5 Biotech for Chickens — Robert Yaman full a3edcd8e-d0f5-4f7f-9f24-654ceaf152a4 https://share.transistor.fm/s/f73c9976 A dairy cow is worth $1,000 to $2,000 to a farmer, whereas a broiler chicken, raised for meat, generates just $4 of profit. Quantifying animals this way may feel uncomfortable, but those $4 are all a farmer can spend to keep a chicken healthy. And this places some really interesting constraints on how biotechnology must be scaled (in terms of vaccines and other interventions) in the animal welfare space. 


In this episode, Robert Yaman, CEO of Innovate Animal Ag, argues that the way to improve animal welfare is to make farming more efficient rather than less. We discuss in-ovo sexing (which uses PCR or hyperspectral imaging to identify an egg's sex before it hatches, and which could help end the culling of 300 million male chicks a year); why hyperspectral cameras work on brown eggs but not white ones; and electron-beam vaccines, which shred a bacterium's DNA while leaving its surface proteins intact, thus producing a farm-specific vaccine for less than one penny per dose.


Robert also reveals publicly, for the first time, that Innovate Animal Ag is building an "accelerator farm": a commercial broiler facility that doubles as a testbed where startups can trial new technology in an industry that hasn't changed all that much in the last fifty years.


Chapters

0:00 Why animal welfare needs scalable technologies
6:40 How chickens were bred for meat and eggs
12:43 Does farm efficiency improve animal welfare overall?
23:41 How the poultry supply chain works, from hatchery to farm
32:01 In ovo sexing to prevent chick culling
47:12 Electron beams and vaccines
1:01:04 Ozempic for chickens
1:15:30 Precision farming and the Accelerator Farm

]]> A dairy cow is worth $1,000 to $2,000 to a farmer, whereas a broiler chicken, raised for meat, generates just $4 of profit. Quantifying animals this way may feel uncomfortable, but those $4 are all a farmer can spend to keep a chicken healthy. And this places some really interesting constraints on how biotechnology must be scaled (in terms of vaccines and other interventions) in the animal welfare space. 


In this episode, Robert Yaman, CEO of Innovate Animal Ag, argues that the way to improve animal welfare is to make farming more efficient rather than less. We discuss in-ovo sexing (which uses PCR or hyperspectral imaging to identify an egg's sex before it hatches, and which could help end the culling of 300 million male chicks a year); why hyperspectral cameras work on brown eggs but not white ones; and electron-beam vaccines, which shred a bacterium's DNA while leaving its surface proteins intact, thus producing a farm-specific vaccine for less than one penny per dose.


Robert also reveals publicly, for the first time, that Innovate Animal Ag is building an "accelerator farm": a commercial broiler facility that doubles as a testbed where startups can trial new technology in an industry that hasn't changed all that much in the last fifty years.


Chapters

0:00 Why animal welfare needs scalable technologies
6:40 How chickens were bred for meat and eggs
12:43 Does farm efficiency improve animal welfare overall?
23:41 How the poultry supply chain works, from hatchery to farm
32:01 In ovo sexing to prevent chick culling
47:12 Electron beams and vaccines
1:01:04 Ozempic for chickens
1:15:30 Precision farming and the Accelerator Farm

]]> Tue, 04 Aug 2026 12:45:49 -0700 Niko McCarty Niko McCarty 5086 A dairy cow is worth $1,000 to $2,000 to a farmer, whereas a broiler chicken, raised for meat, generates just $4 of profit. Quantifying animals this way may feel uncomfortable, but those $4 are all a farmer can spend to keep a chicken healthy. And this places some really interesting constraints on how biotechnology must be scaled (in terms of vaccines and other interventions) in the animal welfare space. 


In this episode, Robert Yaman, CEO of Innovate Animal Ag, argues that the way to improve animal welfare is to make farming more efficient rather than less. We discuss in-ovo sexing (which uses PCR or hyperspectral imaging to identify an egg's sex before it hatches, and which could help end the culling of 300 million male chicks a year); why hyperspectral cameras work on brown eggs but not white ones; and electron-beam vaccines, which shred a bacterium's DNA while leaving its surface proteins intact, thus producing a farm-specific vaccine for less than one penny per dose.


Robert also reveals publicly, for the first time, that Innovate Animal Ag is building an "accelerator farm": a commercial broiler facility that doubles as a testbed where startups can trial new technology in an industry that hasn't changed all that much in the last fifty years.


Chapters

0:00 Why animal welfare needs scalable technologies
6:40 How chickens were bred for meat and eggs
12:43 Does farm efficiency improve animal welfare overall?
23:41 How the poultry supply chain works, from hatchery to farm
32:01 In ovo sexing to prevent chick culling
47:12 Electron beams and vaccines
1:01:04 Ozempic for chickens
1:15:30 Precision farming and the Accelerator Farm

]]> Biology, Science, Technology No Engineered Microbes Seen from the Sky — Yonatan Chemla on Hyperspectral Biology 4 4 Engineered Microbes Seen from the Sky — Yonatan Chemla on Hyperspectral Biology full c9229f2b-2b57-4786-bd41-d93acfb179f3 https://share.transistor.fm/s/390349e5 Scientists have studied bacteria under microscopes for 400 years. But Yonatan Chemla, a postdoctoral fellow at MIT, has developed a technology that lets us see microbes from a drone 100 meters in the air.

In this episode, we discuss the emerging field of "hyperspectral biology," which uses hyperspectral cameras (first built by NASA in the 1980s) to detect molecules with unique light-absorption signatures. With this technology, you could engineer a microbe to sense a landmine, for example, and release a pigment in response. A drone could then spot that pigment from hundreds of meters away. By spraying other types of engineered microbes over a field, they could map heavy metals, report on soil health, or find gold deposits.

But almost none of this can happen in the United States. The EPA regulates engineered microbes as chemicals under the Toxic Substances Control Act, a 1976 law that never mentions biology, and the agency seems to have approved just one product through it. As a result, many of biotechnology's most useful ideas — microbes that break down plastic, sense landmines, or remove pollution from water — never leave the laboratory.

Chapters:
[00:00:00] Introduction
[00:04:08] Applications for hyperspectral biology
[00:07:33] How to build a biosensor
[00:13:00] Molecular absorption data
[00:22:12] How hyperspectral cameras work
[00:38:15] Spatial resolution and satellite monitoring
[00:51:04] Regulations around environmental release
[01:08:44] Risk vs progress

Further Reading:
Summary of the Toxic Substances Control Act, EPA: https://www.epa.gov/laws-regulations/summary-toxic-substances-control-act
Design and regulation of engineered bacteria for environmental release, Nature Microbiology: https://www.nature.com/articles/s41564-024-01918-0
Hyperspectral reporters for long-distance and wide-area detection of gene expression in living bacteria, Nature Biotechnology: https://www.nature.com/articles/s41587-025-02622-y
Seeing microbes from the sky, Asimov Press: https://press.asimov.com/articles/hyperspectral

]]> Scientists have studied bacteria under microscopes for 400 years. But Yonatan Chemla, a postdoctoral fellow at MIT, has developed a technology that lets us see microbes from a drone 100 meters in the air.

In this episode, we discuss the emerging field of "hyperspectral biology," which uses hyperspectral cameras (first built by NASA in the 1980s) to detect molecules with unique light-absorption signatures. With this technology, you could engineer a microbe to sense a landmine, for example, and release a pigment in response. A drone could then spot that pigment from hundreds of meters away. By spraying other types of engineered microbes over a field, they could map heavy metals, report on soil health, or find gold deposits.

But almost none of this can happen in the United States. The EPA regulates engineered microbes as chemicals under the Toxic Substances Control Act, a 1976 law that never mentions biology, and the agency seems to have approved just one product through it. As a result, many of biotechnology's most useful ideas — microbes that break down plastic, sense landmines, or remove pollution from water — never leave the laboratory.

Chapters:
[00:00:00] Introduction
[00:04:08] Applications for hyperspectral biology
[00:07:33] How to build a biosensor
[00:13:00] Molecular absorption data
[00:22:12] How hyperspectral cameras work
[00:38:15] Spatial resolution and satellite monitoring
[00:51:04] Regulations around environmental release
[01:08:44] Risk vs progress

Further Reading:
Summary of the Toxic Substances Control Act, EPA: https://www.epa.gov/laws-regulations/summary-toxic-substances-control-act
Design and regulation of engineered bacteria for environmental release, Nature Microbiology: https://www.nature.com/articles/s41564-024-01918-0
Hyperspectral reporters for long-distance and wide-area detection of gene expression in living bacteria, Nature Biotechnology: https://www.nature.com/articles/s41587-025-02622-y
Seeing microbes from the sky, Asimov Press: https://press.asimov.com/articles/hyperspectral

]]> Mon, 20 Jul 2026 18:16:29 -0700 Niko McCarty Niko McCarty 5004 Scientists have studied bacteria under microscopes for 400 years. But Yonatan Chemla, a postdoctoral fellow at MIT, has developed a technology that lets us see microbes from a drone 100 meters in the air.

In this episode, we discuss the emerging field of "hyperspectral biology," which uses hyperspectral cameras (first built by NASA in the 1980s) to detect molecules with unique light-absorption signatures. With this technology, you could engineer a microbe to sense a landmine, for example, and release a pigment in response. A drone could then spot that pigment from hundreds of meters away. By spraying other types of engineered microbes over a field, they could map heavy metals, report on soil health, or find gold deposits.

But almost none of this can happen in the United States. The EPA regulates engineered microbes as chemicals under the Toxic Substances Control Act, a 1976 law that never mentions biology, and the agency seems to have approved just one product through it. As a result, many of biotechnology's most useful ideas — microbes that break down plastic, sense landmines, or remove pollution from water — never leave the laboratory.

Chapters:
[00:00:00] Introduction
[00:04:08] Applications for hyperspectral biology
[00:07:33] How to build a biosensor
[00:13:00] Molecular absorption data
[00:22:12] How hyperspectral cameras work
[00:38:15] Spatial resolution and satellite monitoring
[00:51:04] Regulations around environmental release
[01:08:44] Risk vs progress

Further Reading:
Summary of the Toxic Substances Control Act, EPA: https://www.epa.gov/laws-regulations/summary-toxic-substances-control-act
Design and regulation of engineered bacteria for environmental release, Nature Microbiology: https://www.nature.com/articles/s41564-024-01918-0
Hyperspectral reporters for long-distance and wide-area detection of gene expression in living bacteria, Nature Biotechnology: https://www.nature.com/articles/s41587-025-02622-y
Seeing microbes from the sky, Asimov Press: https://press.asimov.com/articles/hyperspectral

]]> Biology, Science, Technology No The Bitter Lesson for Biology — Adam Green on Virtual Cells and Scaling Laws 3 3 The Bitter Lesson for Biology — Adam Green on Virtual Cells and Scaling Laws full ca63af84-dd68-4863-89ea-a09caa98aa0d https://share.transistor.fm/s/4f75f06c 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.


00:00 - Cold open and introduction 

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 


Readings and mentions: 

]]> 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.


00:00 - Cold open and introduction 

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 


Readings and mentions: 

]]> Fri, 12 Jun 2026 09:30:00 -0700 Niko McCarty Niko McCarty 5374 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.


00:00 - Cold open and introduction 

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 


Readings and mentions: 

]]> Biology, Science, Technology No Magnet-Controlled Medicines — Andrew York & Maria Ingaramo 2 2 Magnet-Controlled Medicines — Andrew York & Maria Ingaramo full a8955dff-de9d-4635-ad3a-49f3564bb3cb https://share.transistor.fm/s/1c6b4041 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

]]> 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

]]> Fri, 29 May 2026 09:06:00 -0700 Niko McCarty Niko McCarty 7656 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

]]> Biology, Science, Technology No Mark Budde - How to speed up wet-lab biology 1 1 Mark Budde - How to speed up wet-lab biology full a1bb326e-8ef1-4338-9789-bea1b1b826a3 https://share.transistor.fm/s/db426e0b 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.

]]> 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.

]]> Fri, 08 May 2026 09:30:00 -0700 Niko McCarty Niko McCarty 3452 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.

]]> Biology, Science, Technology No