More Stories We'd Like to Publish

A third installment of articles that we’d like to publish across medicine, biosecurity, the environment, animal welfare and more.

Forest of Fontainebleau, Jean-Baptiste-Camille Corot, 1834

Our goal at Asimov Press is to share the biggest stories in biotechnology. We do this by publishing original articles, as well as releasing technical and historical podcasts and printing beautiful, physical books.

This work is made possible by you, our readers, who shape our coverage more than you might expect. When we meet you at events, we often hear great ideas for stories but don’t know suitable writers to take them on. In a quest to find them, we are releasing our third list of Stories We’d Like to Publish. If any of these ideas speak to you, please send an email with the word “Pitch” in the subject line to editors@asimov.com.¹

In your email, tell us why you’re the right person to tell this story, and also include examples of prior, non-academic writing (outlines are also welcome, so we can see how you might structure the article). If we accept the pitch, we’ll support you throughout the writing process, from outlining to editing, then copyediting and publishing. When the article is finished, we’ll pay you, host the article online and, perhaps, print your work in a forthcoming, physical book.

We are no longer seeking to publish “pure histories,” or articles that solely look to the past. History is important and might be integral to the article, but we are after arguments and ideas. We generally publish two types of pieces:

1. Reported features are stories that explain a technology’s promise while looking hard at its setbacks and current hurdles. These features should consider the future with an eye to the past, making both the science and the stakes clear. They should investigate the drama of discovery and the people moving a field forward, yet not shy away from prior decisions that might have led it astray. We typically pay $1-$1.50 per word for reported features and seek to work with experienced writers with a strong narrative skillset. We’re open to funding travel for in-person interviews.

2. Essays should make an argument, advance a big idea, or put forth a new way of looking at an idea. Essays, at their core, explain what should exist in the world and why. What problem are you trying to solve? What would it take to solve it? We want ideas that readers and funders can ingest, contemplate, and act on. We typically pay a flat rate of $1,200 for essays.

Here is a (high-level look) at some of the ideas we’d like to publish.

Wolbachia mosquitoes in Singapore

What happens when a city releases mosquitoes to prevent disease? In Singapore, researchers reared male Aedes aegypti mosquitoes carrying Wolbachia, a type of bacteria that prevents eggs from hatching when these males mate with wild females, and released them around the city. In a randomized trial across neighborhoods home to more than 724,000 people, the mosquitoes reduced the risk of symptomatic dengue by about 71–72%.

How did Singapore make this work in a densely populated city? How do you rear, sort, and distribute enough males, and how much does it cost to keep releasing them? How did residents react? A recent Works in Progress article, “Mosquitoes are a choice,” explored the idea of mosquito control and its regulatory barriers; now we’d like writers to build on that article via on-the-ground reporting to figure out what it would take to scale this technology elsewhere.

Freeze-drying any protein

Can we freeze-dry more proteins and other molecules so that drugs and diagnostics could be shipped without refrigeration? Some proteins, when frozen and dried, unfold or clump together, and finding a formulation that prevents this often involves a lot of trial and error. For a recent study, researchers used AI tools to create solid-state mRNA vaccines that retained their full bioactivity for two months at 37°C. The method worked by optimizing the ingredients around the vaccines and then drying them under vacuum.

This is a cool demonstration, but could we refactor more of our supply chain around dried molecules? It might allow for shipping more molecules where they’re needed; pharmacies in remote areas could keep powders ready to go, unrefrigerated. We’d love an idea-driven article examining how to make more proteins and other medicines stable without refrigeration.

DNA screening is a difficult problem

If someone orders a DNA sequence encoding a known pathogen or toxin, a DNA synthesis company can flag it and refuse to make the order. DNA screening algorithms are becoming quite good, but can they keep up with advances in biotechnology?

A recent Nature Biotechnology paper describes a method to assemble more than 1,000 gene fragments from a large oligo pool in a single reaction, with near-zero misalignment between genes. For a separate study, researchers at Arc Institute used Evo, a generative AI model, to design and synthesize nearly 300 bacteriophage genomes; 16 were viable, and several outperformed the natural ΦX174 template, despite having sequences that differed greatly from natural bacteriophages. How do DNA screening algorithms detect pathogenic sequences that do not share high homology with known pathogens? How might we engineer these algorithms to counter manufactured biothreats (not to mention benchtop DNA printers)?

Islet cell transplants for diabetes

It’s possible to treat type 1 diabetes by taking insulin-producing beta cells from a dead person’s pancreas and injecting them through a patient’s skin into their liver. The beta cells stay trapped inside the liver and pump out insulin, relieving some recipients from insulin injections for several years. Still, these patients need ongoing glucose monitoring and long-term immunosuppressive drugs.

There has been some recent progress in combining donor islet transplants with treatments intended to establish immune tolerance, but how close is this to widespread use? Is there a more permanent way to “cure” type 1 diabetes?

Gene delivery to the brain

A gene therapy can only work if it reaches the right cells. The brain makes this especially difficult, in part because its blood vessels restrict what can pass into surrounding tissue, and reaching one region does not mean reaching the various cell types spread throughout the brain. Researchers are trying many options to get genes into the brain; everything from direct injections (through the skull) to engineered viruses that cross the blood-brain barrier. One team redesigned an AAV capsid to bind the human transferrin receptor and showed that this improved brain delivery in mice engineered to express that receptor.

We’d like a reported guide to what works for brain deliveries, for which cells, and in which species. How do delivery through the bloodstream, spinal fluid, and direct brain injections compare? Which neuron types remain hardest to reach, and why do promising results in mice so often fail to translate? One way to focus this article might be to explore how people have tried to deliver gene therapies to the brain for, say, Huntington’s.

Woman Reading in the Studio, Jean-Baptiste-Camille Corot, 1868.

Gryphon Scientific

Gryphon Scientific was a small consultancy that grew into one of the most important biosecurity organizations. Founded in 2005, it worked at the intersection of biology and national security for years before those issues became mainstream. And when the U.S. government paused certain gain-of-function experiments involving influenza, SARS, and MERS, the guidelines were informed by a risk and benefit analysis performed by Gryphon. The company also did some of the early work on DNA synthesis screening, laboratory containment, and risks at the intersection of AI and biology. (And wrote one of our favorite papers of all time, “The accelerating pace of biotech democratization.”)

Deloitte acquired Gryphon in 2024, so now is a good time to revisit their work. How did Gryphon Scientific choose their projects, recruit people, and build credibility in the biosecurity space? We’d love a reported company profile of their work and early years; such a piece might offer useful context for other entrepreneurs working at the intersection of biosecurity and philanthropy.

On the unreasonable pain of engineering trees

North Carolina State University is famous for its engineered trees. It’s home to multiple tree engineers who use gene-editing tools, such as CRISPR, to modify how quickly eucalyptus, poplar, and other varieties grow, resist disease, or make wood. But this task is unreasonably painful. Even within one species, for example, trees can respond so differently to tissue culture and transformation that researchers have to frequently rebuild their protocol, even in the same species. You cannot just make an edit, grow a tree, and see what happens (as the process takes many, many years).

Given that a single experiment in tree biotechnology can take decades, how is it possible to design edits when iterations are so slow? We’d love a piece profiling “tree engineers” that also investigates what might be done to solve these bottlenecks. Trees are arguably the most important class of organisms on Earth, and yet this topic is largely unknown.

Release the sentinel plants

Plants can be engineered to act as a warning system for farmers. Researchers can create a gene circuit that senses a pathogen, toxin, drought or nutrient stress, coax it into plants, and then design an output module that causes a visible change in leaf color, the emission of a gas, or anything else that can be read out using a drone or tractor. Sean Cutler’s group at UC Riverside has engineered plants that turn red in the presence of a banned pesticide, for example, and a company called InnerPlant is developing soybean, corn, and cotton that fluoresce under stress. We’d like to publish a feature about how these sentinel plants work, and how they might be deployed at scale.

Once-weekly insulin

The FDA recently approved Onswik, a once-weekly insulin injection for people with type 2 diabetes. This molecule was engineered in some intriguing ways; for one, it’s attached to part of an antibody, which slows its clearance from the bloodstream. And two, the insulin protein was engineered to bind its receptor less strongly, helping it to act gradually over time. We’d like to publish an article about these once-weekly insulins, how they work at a molecular level, and what difficulties arose before the FDA approval.

Protein logic drugs

Researchers have been making “smart” insulin proteins that dynamically change their binding activities based on how much glucose is in the bloodstream. One of these experimental therapies, called NNC2215, is an insulin protein attached to a glucose-binding ring and a small chemical group that looks a lot like glucose. So when glucose is low in the blood, these chemical attachments hold the insulin in a shape that makes it harder for the protein to bind to its receptor. But when glucose levels rise, the glucose molecules in the bloodstream compete for the binding site and favor the more active shape. We’re curious about whether similar sorts of dynamic therapeutics are being explored for other conditions. How do these “logical proteins” work mechanistically, especially given advances in protein design tools?

Plants that clone themselves

Some plants naturally make seeds without sex; their offspring are genetic clones of the parents. Researchers are trying to take this trait (naturally found in dandelions, for example) and engineer it into rice and other important crops. If they succeed, the major seed companies—which currently cross plants every year, harvest their seeds, and sell them to farmers—could be circumvented. Farmers would be able to plant their crops and reuse their seeds year after year, because the F1 hybrid “vigor” would remain unchanged.

Researchers have already produced hybrid rice that generates more than 95% clonal seed across several generations, but transferring the system reliably to other crops has been difficult, with problems related to seed yield and the stability of clonal reproduction. We’d like to publish a feature explaining synthetic apomixis, why it has taken so long, and what it might enable at scale.

La Liseuse couchée, Paul Ranson, 1895.

Jellyfish sensors for ocean mapping

John Dabiri’s group at Caltech is building electronic devices that can be attached to living jellyfish and used to measure pH, pollution, and other things in the ocean. His plan is to use these animals to map the ocean by taking measurements through waters they naturally travel, while transmitting data along the way. This would provide an alternative to expensive submersibles. Could we similarly attach chemical sensors to birds to measure air pollution? Would that even be ethical? We’d like to publish a profile of Dabiri that considers this emerging approach to animal sensing.

Real-time RNA sequencing

Transcriptomics is a method to measure the abundance of messenger RNA in a cell. The gist is that you grow cells in a culture (or individual cells in a microfluidic chip), slice them open, extract their RNA molecules, and convert the molecules into DNA copies. Then, you use machines to “count” the abundance of each sequence. The approach has a downside, though, in that the readout reflects only the quantity of RNA molecules at the particular moment when the cells were cut open. Cells are constantly dialing RNA abundances up or down (as gene expression is not static), but this dynamism isn’t captured.

We’d like to commission a piece on “real-time RNA-seq,” or the plethora of methods that enable RNAs to be studied across time. Live-seq, for example, is a method to extract RNA molecules from single cells without breaking them open. Felix Horns, a researcher at Arc Institute, has also developed a method to coax cells to export their own RNAs, enabling the molecules to be studied over time. Why aren’t these methods widely used? Are they biased or finicky? What will it take to make them mundane?

Noninvasive biology

In a related question, we think it’s very strange that so many methods used to study biology measure a particular molecule at a particular moment in time. These methods are incredibly one-dimensional, and we could do so much more in biology if we had ways to study molecules across space and time without killing the cell.

Historically, we could fuse fluorescent proteins to a target in a cell and then watch those cells under a microscope to see where and how that protein moves. But there are all kinds of other interesting noninvasive methods coming online. For example, hyperspectral imaging could theoretically be used to quantify molecular abundances without destroying the cell. Raman spectroscopy similarly allows for studying cells by measuring the vibrational frequencies of molecules. And Dan Needleman at Harvard is developing imaging methods to study metabolism in living cells. We’d like articles on “future” technologies that help normalize and encourage people to work on them.

Getting clinical data from inside the body

Let’s say a drug researcher has invented a new therapy for cancer. The drug is given to patients in a clinical trial, and tumors are measured for shrinkage. While symptoms are tracked, it can be difficult to measure exactly how much drug reached the tumor, which cells it entered, or whether the tumor shrank because of direct or secondary effects. Biopsies, scans, and blood tests help answer some of these questions, but not very well.

There has to be a better way to study how drugs behave inside the body with higher spatial resolution. Consider CAR T-cell therapies, where T-cells are taken from a patient’s body, engineered to recognize the patient’s cancer and then re-infused. The T-cells circulate, find cancer cells, and destroy them. Researchers have engineered CAR T-cells to express gas vesicles (little protein shells that exclude water, and thus show up on ultrasound scans) and tracked them in mice for up to five days. Could similar methods enable us to follow these cells inside patients? There are many other things that could be measured in vivo, too, if only we had better methods.

Blood draws are outdated

Hims & Hers acquired YourBio Health, which makes devices that use tiny needles and suction to collect blood from capillaries in the upper arm. Its TAP Micro Select device can draw up to 500 microliters, or half a milliliter, of blood with the push of a button. In one study, participants rated their pain when using several upper-arm devices, including TAP, and ranked this device below a 1 on a 10-point pain scale. So how is it possible to make a blood draw hurt so little?

A piece on this idea should explain how these capillary blood draws were invented and why we don’t yet find them everywhere. Why, when we go to the doctor, do we still give vials of blood? If it’s because certain assays require a large amount of blood, how can we change those assays to test for more things using less blood? This might sound like Theranos, but we’d love a piece examining which assays these devices are compatible with, which they aren’t, and how their use might be extended.

A “universal” nanopore

The holy grail of biosensing is arguably to create a universal solid-state nanopore. We’ve had several conversations with the founder of Demonpore, a company trying to build this technology, but it’s been hard to get people in the field to speak to us about the bottlenecks. Today, nanopore sensors are best known for DNA sequencing, where individual DNA molecules pass through a tiny protein pore and alter the ionic current flowing through it. In principle, the same basic idea could be extended much further; a solid-state nanopore, for example, is simply a tiny hole (not a protein) drilled into a membrane, and different molecules passing through that hole should perturb the electrical current in different ways. If we collected enough data on the electrical signatures produced by amino acids, proteins, RNA molecules, nucleotides, and other compounds, could we train a model to distinguish among them and turn a nanopore into a general purpose sensor for biology?

A Woman Reading, Camille Corot, ca. 1869.

Egg manufacturing

Vaccines for seasonal influenza have been manufactured in chicken eggs since the 1940s. But eggs could make much more than vaccines. Neion Bio is engineering chickens to make therapeutic proteins—including monoclonal antibodies—in their eggs. Eggs are abundant, and each contains roughly six grams of protein. When Ozempic soared in popularity, there were worries over manufacturing constraints. Could eggs help address manufacturing constraints for some drugs?

What are the bottlenecks? Are GMP-grade manufacturing requirements holding it back? Are eggs too variable from one batch to the next to ensure drug consistency? (For example: Not all influenza strains replicate equally well in eggs, and growing them in eggs can select for changes that affect vaccine performance.)

Bottlenecks on microfluidic chips

Microfluidic chips allow for the manipulation of tiny volumes of liquid and make it relatively easy to study single cells, but making the chips can be finicky. Many methods require photolithography, UV light, specialized equipment, and a lot of technical expertise. The dream would be to have a 3D printer that could just print the chip you want. Researchers already print channels only tens of micrometers across, but achieving the resolution needed remains difficult.

What are the issues holding back microfluidic manufacturing? How do we scale this so that more labs can use microfluidic 3D printers instead? Related: Where Is My Mother Machine?

Can we eradicate cervical cancer?

We have vaccines that can prevent most cervical cancers, and yet the disease still kills hundreds of thousands of women. WHO estimated 660,000 new cases and 350,000 deaths in 2022. In one Swedish study, though, HPV vaccinations given before age 17 were associated with an 88% lower risk of cervical cancer.

Is it possible to eliminate cervical cancer? WHO’s goal is fewer than four new cases per 100,000 women each year, but we’d like to publish a feature about how close we are to full eradication. Where are rates already falling, and what combination of vaccination, screening, and treatment would let other countries follow? (h/t Saloni Dattani)

Hepatitis is weird

Hepatitis B and C both infect the liver and can cause cirrhosis and cancer. But our tools against them have a strange asymmetry. We have a highly effective vaccine against hepatitis B, yet treatment merely suppresses a chronic infection instead of curing it. For hepatitis C, antiviral drugs can cure more than 95% of infections, but we still have no effective vaccine. WHO estimates that 240 million people were living with chronic hepatitis B in 2024.

We’d like a mechanistic, reported piece about the missing hepatitis B cure and hepatitis C vaccine. We’re open to treating these as two separate stories, or as one big feature.

Reading the Will, David Wilkie, 1820.

Biotechnology in the Global South

Biotechnology innovation, historically, has mostly come in the northern hemisphere, particularly in the United States, Europe and (more recently), China. The world would benefit from biotechnology flourishing in the Global South, as well. There are deficits in venture capital and research funding in many countries of the Global South, as well as infrastructure issues around cold storage and the electric grid. A lack of biologic materials hinders progress. There are talent issues, as well, with young researchers leaving to train in established and well-funded labs elsewhere, and sometimes staying.

What other issues might be holding back biotech progress in the Global South? What countries are focusing on building a bio-economy, and are their goals achievable? And what do promising young scientists in the global south think about all of this? We’d love a reported feature on this topic.

How $1B remade Boston

The state of Massachusetts made a 10-year, $1 billion investment to make itself into a biotech and pharma hub. The initiative overhauled Cambridge, Massachusetts, and the surrounding universities. It also bore fruit with drug approvals. With a lack of clarity around future federal funding for basic science, perhaps it is time to again use state tax dollars to drive innovation and growth in biotech. California is moving forward with its own plan, but what lessons can be learned from Boston’s earlier initiative, and can they be applied to other states? We’d love a feature investigating this past and applying it to the future.

Editing mice against Lyme disease

Mice Against Ticks is a collaboration between MIT and Tufts University, with the aim of making white-footed mice immune to Lyme disease. Mice are a reservoir for the disease, and the initiative is seen as a possible tool for also fighting hantavirus, arenavirus and leptospirosis. Many ecological issues arise around engineering the genome of an animal in the wild, of course. The initiative has said it prioritizes local input (the project began in and around Nantucket and Martha’s Vineyard in Massachusetts) and responsibility, but how has that worked in reality? What results have been seen so far, and where has data been published? And how would a relatively small scale field trial be scaled to curtail Lyme disease across the country? Meanwhile, Lyme (and alpha-gal syndrome) is on the rise, with the CDC estimating that nearly half a million Americans are treated for the infection each year. Having seen how unpleasant it can be up close, we’d love to see a reported feature on the technology behind Mice Against Ticks, what it might be able to solve, and the problems inherent in genetically modifying a population of wild animals.

Pig genome engineering for organs

How much of a pig’s genome has to change before its organs can work inside a person? For one study, researchers made 69 edits to the pigs, including changes that removed immune-provoking sugars, added human proteins, and inactivated copies of porcine endogenous retroviruses. A kidney from this design was transplanted into a living patient in 2024, though the patient died 52 days later. Other groups are pursuing different combinations of modifications, and it’s not clear which approach is most likely to succeed and why.

We’d like an article that explains the reasoning behind these edits and what the transplant results tell us about them. How far away are we (actually) from pig organs being transplanted into humans and working inside of them for decades? Why do these studies keep failing?

Paper-based sensors

Similarly, one can combine cell extracts with a synthetic gene circuit, freeze-dry the mixtures onto paper, and then reactivate those molecular circuits with water, saliva, or other liquids. These cell-free circuits can be programmed to sense a particular RNA sequence, protein, small molecule, or toxin. By freezing this molecular program in time on a piece of paper, it basically becomes a portable biosensor. Researchers used these paper-based biosensors to detect Ebola and Zika in the laboratory, and even showed they worked on real patient samples for chikungunya.

But progress seems to have stalled. Were these sensors not sensitive enough, or did they get outcompeted by RT-LAMP and other assays? We’d love an article that tells the story behind these paper-based sensors and where they stand today.

Portable vaccines

Many years ago, researchers showed that you can take molecular machinery from engineered bacteria, freeze-dry it, and then “reactivate” those molecules to create a vaccine. These cell-free systems can read DNA sequences dropped into a vial, basically, and then read it to make proteins. Researchers showed it’s even possible to attach bacterial sugars to these proteins, in these vials, to make conjugate vaccines. The reaction takes about an hour, and the freeze-dried mixtures can be stored at room temperature. In one experiment, a vaccine made from these cell-free mixtures protected mice from a normally lethal bacterial infection.

These “portable vaccines” were touted as a way to make custom vaccine manufacturing more feasible in low-income countries. But they have not yet surfaced. Did they fail for economic, geopolitical, or technical reasons?

1. We do not accept AI-generated pitches, or any AI-generated writing for that matter. It’s fine to use AI for research or analysis (and we do the same), but a great pitch should clearly be in your own voice; it should have personality and charm, and be laden with the sort of specificity that would be difficult to replicate with an LLM.