Houston-based space company Intuitive Machines is gearing up for an actual moonshot at the end of this month, when it’ll try to land a spacecraft named Odysseus on the lunar surface — ideally without it breaking in the process. The mission follows Astrobotic’s unsuccessful attempt in January; that company’s lander, Peregrine, never made it to the moon due to a propellant leak that cut its journey short. Peregrine’s failure means Intuitive Machines’ IM-1 mission could be the first ever commercial moon landing if it makes it there intact.

Intuitive Machines is hoping to make its landing attempt on February 22, targeting the Malapert A crater near the moon’s south pole for touchdown. This arrival date is dependent on Odysseus, one of the company’s Nova-C class landers, leaving Earth atop a SpaceX Falcon 9 rocket sometime between February 14 and February 16. The launch window opens at 12:57AM ET on Wednesday.

Odysseus is the first of three Nova-C landers Intuitive Machines plans to send to the moon this year, all of which will have commercial payloads on board and NASA instruments as contracted under the agency’s Commercial Lunar Payload Services (CLPS) program. At 14 feet tall (4.3 meters), the lander is roughly the size of a giraffe and can carry about 280 pounds (130kg) of cargo. Its mission, if it nails a soft landing, will be a short but potentially valuable one for informing future excursions to the region, including NASA’s upcoming crewed Artemis missions. Orbiting probes have found evidence of water ice at the lunar south pole, which could be used for astronaut subsistence and even fuel, making it an area of high interest for human exploration.

NASA

The solar-powered craft and any functional equipment it’s carrying are only expected to be in working condition for about a week before the onset of lunar night, a 14-day period of frigid darkness that the company says will leave the lander inoperable. But while everything’s up and running, the various instruments will gather data at the surface. NASA awarded Intuitive Machines a $77 million contract for the delivery of its payloads back in 2019, and there are six NASA instruments now hitching a ride on Odysseus.

One, the Laser Retroreflector Array (LRA), will “function as a permanent location mark” from its position on the moon after landing to help incoming spacecraft determine their distance from the surface, according to NASA. The lander is also carrying the Navigation Doppler LIDAR for Precise Velocity and Range Sensing (NDL), a sensor that measures velocity and altitude to better guide the descent, and the Lunar Node 1 Navigation Demonstrator (LN-1) to support communication and autonomous navigation in future missions.

NASA is also sending instruments to study surface plumes — everything that gets kicked up when the lander touches down — along with radio waves and the effects of space weather. That includes the Stereo Cameras for Lunar Plume-Surface Studies (SCALPSS), which will capture images of these dust plumes, and the Radio wave Observation at the Lunar Surface of the photoElectron Sheath (ROLSES) instrument.

The rest of the payloads on board Odysseus are commercial. Columbia Sportswear worked with Intuitive Machines to incorporate the brand’s Apollo-inspired Omni-Heat Infinity thermal reflective material, which is being used for this mission to help protect the cryogenic propulsion tank, according to Intuitive Machines. Students at Embry-Riddle Aeronautical University developed a camera system dubbed the EagleCam that will attempt to separate from the lander before it touches down and snap a picture of the moment from a third-person point of view. EagleCam is also equipped with an experimental dust-removal system.

Intuitive Machines

There are even some Jeff Koons sculptures heading to the moon, which will have physical and NFT counterparts back on Earth. In Koons’ Moon Phase piece, 125 small stainless steel sculptures of the moon at different phases are encased in a clear cube made by 4Space, with the names of important historical figures from around the world listed below each sphere. The International Lunar Observatory Association, based in Hawaii, and Canadensys Aerospace are sending a 1.3-pound dual-camera system called ILO-X, with which they’ll attempt to capture wide and narrow field images of the Milky Way from the moon.

Odysseus is also carrying small discs called “Lunagrams” from Galactic Legacy Labs that contain messages from Earth, including text, images, audio and archives from major databases such as the Arch Mission Foundation and the English-language version of Wikipedia. Similar archival materials were sent to space with Peregrine last month. The information technology company Lonestar plans to demonstrate its Disaster Recovery as a Service (DRaaS) by storing data on the lander and transmitting documents ( including the US Declaration of Independence) between Earth and the moon. It’ll follow this up with a prototype mini data center on Intuitive Machines’ next launch.

Now, the pressure is on for the Odysseus Nova-C lander to actually get to the lunar surface safely. This year started off rocky for moon missions, with the failure of Astrobotic’s Peregrine and a descent hiccup that caused JAXA’s SLIM spacecraft to faceplant into the lunar surface (though the latter was miraculously able to resume functions to some degree after a few days). Intuitive Machines will have other chances to get it right if it doesn’t this time — it has multiple missions already booked up — but only one private lander can be “first.”

Even NASA is not immune to layoffs. The agency says it's cutting around 530 employees from its Jet Propulsion Laboratory (JPL) in California amid budget uncertainty. That's eight percent of the facility's workforce. JPL is laying off about 40 contractors too, just weeks after imposing a hiring freeze and canning 100 other contractors. Workers are being informed of their fates today.

"After exhausting all other measures to adjust to a lower budget from NASA, and in the absence of an FY24 appropriation from Congress, we have had to make the difficult decision to reduce the JPL workforce through layoffs," NASA said in a statement spotted by Gizmodo. "The impacts will occur across both technical and support areas of the Lab. These are painful but necessary adjustments that will enable us to adhere to our budget allocation while continuing our important work for NASA and our nation."

Uncertainty over the final budget that Congress will allocate to NASA for 2024 has played a major factor in the cuts. It's expected that the agency will receive around $300 million for Mars Sample Return (MSR), an ambitious mission in which NASA plans to launch a lander and orbiter to the red planet in 2028 and bring back soil. In its 2024 budget proposal, NASA requested just under $950 million for the project.

“While we still do not have an FY24 appropriation or the final word from Congress on our Mars Sample Return (MSR) budget allocation, we are now in a position where we must take further significant action to reduce our spending,” JPL Director Laurie Leshin wrote in a memo. "In the absence of an appropriation, and as much as we wish we didn’t need to take this action, we must now move forward to protect against even deeper cuts later were we to wait."

NASA has yet to provide a full cost estimate for MSR, though an independent report pegged the price at between $8 billion and $11 billion. In its proposed 2024 budget, the Senate Appropriations subcommittee ordered NASA to submit a year-by-year funding plan for MSR. If the agency does not do so, the subcommittee warned that the mission could be canceled.

That's despite MSR having enjoyed success so far. The Perseverance rover has dug up some soil samples that contain evidence of organic matter and would warrant closer analysis were NASA able to bring them back to Earth. The samples could help scientists learn more about Mars, such as whether the planet ever hosted life.

Against all odds, Japan’s SLIM lander managed to turn back on more than a week after it plopped upside down onto the surface of the moon — but now, it’s gone dormant for the duration of the lunar night, and it may not be able to wake up again. The SLIM team from the Japanese space agency, JAXA, on Thursday shared the last image the lander captured at the moon’s Shioli crater before dusk, as night encroached. Lunar night lasts the equivalent of two Earth weeks and can get colder than 200 degrees Fahrenheit.

The team has confirmed that the solar powered lander is in a dormant state that will last at least the duration of the lunar night. Its chances of resuming operations afterward aren’t great, but then again, it’s already surprised us once. “Although SLIM was not designed for the harsh lunar nights, we plan to try to operate again from mid-February, when the Sun will shine again on SLIM’s solar cells,” the team wrote on X. If this truly is SLIM’s last photo, it sure is a spooky one.

The first metal 3D printer that will be used in space is on its way to the International Space Station. The Cygnus NG-20 supply mission, which is carrying the 180kg (397 lbs) printer, launched on Tuesday and is set to arrive at the ISS on Thursday.

Astronaut Andreas Mogensen will install the printer, which Airbus developed for the European Space Agency. The machine will then be controlled and monitored from Earth.

Polymer-based 3D printers have been employed on the ISS in the past, but metal 3D printing in orbit is said to pose a trickier challenge. The machine will use a form of stainless steel that’s often used for water treatment and medical implants because of how well it resists corrosion.

After the stainless steel wire is pushed into the printing area, the printer melts it with a laser said to be a million times more powerful than a typical laser pointer. The printer then adds the melted metal to the print.

The melting point of the metal is around 1,400°C and the printer will run inside a completely sealed box. Before the printer can operate, it needs to vent its oxygen into space and replace its atmosphere with nitrogen. Otherwise, the melted metal would oxidize when it became exposed to oxygen.

Given the higher temperatures that are employed compared with a plastic 3D printer (which heats to around 200°C), "the safety of the crew and the Station itself have to be ensured — while maintenance possibilities are also very limited," ESA technical officer Rob Postema told the agency's website. "If successful though, the strength, conductivity and rigidity of metal would take the potential of in-space 3D printing to new heights.”

Four test prints are scheduled. The printer will replicate reference prints that have been created back on Earth. The two versions will be compared to help scientists understand how printing quality and performance differs in space. Even though each print will weigh less than 250g (8.8 ounces) and be smaller than a soda can, it will take the printer between two and four weeks to create each one. The printer will only be in operation for a maximum of four hours each day, since its fans and motor are fairly loud and the ISS has noise regulations.

If the experiment goes well, it will pave the way for astronauts and space agencies to print required tools or parts without having to send the items on resupply missions. Metal 3D printing could also help with the construction of a lunar base using recycled materials or transformed regolith (moon soil and rock). It may come in useful for missions to Mars too.

An MIT biotech researcher has been able to run the iconic computer game Doom using actual gut bacteria. Lauren Ramlan didn’t get the game going on a digital simulation of bacteria, but turned actual bacteria into pixels to display the 30-year-old FPS, as reported by Rock Paper Shotgun.

Specifically, Ramlan created a display inside of a cell wall made entirely of E. coli bacteria. The 32x48 1-bit display may not win any resolution awards, but who cares, right? It’s Doom running on bacteria. The researcher dosed the bacteria with fluorescent proteins to get them to light up just like digital pixels.

There’s a couple of caveats here. First of all, the bacteria aren’t actually running the game, as we still haven't cracked that whole “inject biological matter with digital code” thing. Instead, the bacteria combine to act as a teensy-tiny monitor that renders gameplay for the beloved shooter.

Also, there’s the subject of frame rate, which is always an important metric when considering FPS games. To be blunt, the frame rate is atrocious, likely due to the fact that bacteria were never intended to display 3D video games. It takes 70 minutes for the bacteria to illuminate one frame of the game and another eight hours to return to its starting state. This translates to nearly nine hours per frame, which means it would take around 600 years to play the game from start to finish. That’s even worse than Cyberpunk 2077 at launch.

So while this won’t present the smoothest gameplay experience, it’s still a pretty nifty idea. Also, it further proves the theory that Doom can run on just about anything. We’ve seen the game running on pregnancy tests, rat brain neurons and even inside of other titles, like the sequel Doom II and Minecraft. Doom is the great equalizer. May it continue to surprise us for the next 30 years.

We may have an adequate understanding of the human body in that, well, we invented aspirin and sequenced the genome, but researchers still find out new things about the humble homo sapien all of the time. Case in point? Scientists just discovered a previously unknown entity hanging out in the human gut and mouth. The researchers are calling these virus-like structures “obelisks”, due to their presumed microscopic shape.

These entities replicate like viruses, but are much smaller and simpler. Due to the minuscule size, they fall into the “viroid” class, which are typically single-stranded RNAs without a protein shell. However, most viroids are infectious agents that cause disease and it doesn’t look like that’s the case with these lil obelisks, as reported by Live Science.

So why are they inside of us and what do they do? That’s the big question. The discoverers at Stanford University, the University of Toronto and the Technical University of Valencia have some theories. They may influence gene activity within the human microbiome, though they also hang out in the mouth. To that end, they have been found using the common mouth-based bacterium Streptococcus sanguinis as a host. It’s been suggested that these viroids infect various bacteria in both the mouth and gut, though we don’t know why.

Some of the obelisks seem to contain instructions for enzymes required for replication, so they look to be more complex than your average viroid, as indicated by Science. In any event, there has been a “chicken and the egg” debate raging for years over whether viruses evolved from viroids or if viroids actually evolved from viruses, so further study could finally end that argument.

While we don’t exactly know what these obelisk sequences do, scientists have discovered just how prevalent they are in our bodies. These sequences are found in roughly seven percent of human gut bacteria and a whopping 50 percent of mouth bacteria. The gut-based structures also feature a distinctive RNA sequence when compared to the mouth-based obelisks. This diversity has led researchers to proclaim that they “comprise a class of diverse RNAs that have colonized, and gone unnoticed in, human, and global microbiomes.”

“I think this is one more clear indication that we are still exploring the frontiers of this viral universe,” computational biologist Simon Roux of the DOE Joint Genome Institute at Lawrence Berkeley National Laboratory told Science.

“It’s insane,” added Mark Peifer, a cell and developmental biologist at the University of North Carolina at Chapel Hill. “The more we look, the more crazy things we see.”

Speaking of frontier medicine, scientists also recently created custom bacteria to detect cancer cells and biometric implants that detect organ rejection after replacement surgery. The human body may be just about as vast and mysterious as the ocean, or even space, but we’re slowly (ever so slowly) unraveling its puzzles.

The first human patient has received a Neuralink brain implant, according to Elon Musk. The procedure was apparently successful, with Musk saying the individual “is recovering well” one day after the surgery.

Neuralink, which aims to create brain-computer interfaces (BCI), began recruiting human patients for its first clinical trial last fall after getting the green light from the FDA. At the time, Neuralink said that people “who have quadriplegia due to cervical spinal cord injury or amyotrophic lateral sclerosis (ALS)” may qualify for the study. “The initial goal of our BCI is to grant people the ability to control a computer cursor or keyboard using their thoughts alone,” the company wrote in a statement.

Musk didn’t share any other details about the procedure or the status of the trial. He said that “initial results show promising neuron spike detection.” Successfully implanting its device into a human patient would be a major milestone for the company, which Musk has claimed could one day enable people to experience alternate realities. The company is also facing a federal investigation for allegedly violating animal welfare laws.

Meta is teaming up with the Center for Open Science (COS) to start a pilot program that studies “topics related to well-being.” It looks like the program will dive into our social media data, but on a voluntary basis, as COS says it will use a “privacy-preserving” dataset provided by Meta for the study. The agency says the study should help people understand “how different factors may or may not impact well-being and inform productive conversations about how to help people thrive.”

The specifics of the study remain opaque, but COS says it’ll use “new types of research processes” like pre-registration and early peer review. That last one is important, as it sends proposed research questions to peer review before being issued to study participants. This should help stave off bias and ensure the questions are actually useful. The agency also says that all results will be published and “not just those that confirm one’s hypothesis or support a prevailing theory.”

As for a totally non-scientific study on the effects of social media, using it for even ten minutes transforms any dopamine in my brain to the swamps of sadness from The Neverending Story. You could be the same. It’s no secret that social media is basically a factory that creates mental unease, and this is particularly true for kids and teens.

So, why announce this partnership today of all days? It could be a coincidence, but the timing sure is funny. Meta is set to testify this week in front of the US Senate Judiciary Committee about its failures to protect kids online, along with other social media bigwigs like TikTok, Snap and X. It is worth noting, however, that Meta CEO Mark Zuckerberg and TikTok CEO Shou Zi Chew are willing participants in this testimony. Snap CEO Evan Spiegel, Discord CEO Jason Citron and X CEO Linda Yaccarino had to be formally subpoenaed.

However, Meta has a particularly bad track record when it comes to this stuff. After all, the company’s being sued by 41 states for allegedly harming the mental health of its youngest users. The suit claims Meta knew its “addictive” features were bad for kids and intentionally misled the public about the safety of its platforms.

Unsealed documents from the suit claim that Meta actually “coveted and pursued” children under 13 and lied about how it handled underage accounts once discovered, often failing to disable these accounts while continuing to harvest data. This would be a brazen violation of the Children’s Online Privacy Protection Act of 1998.

Another lawsuit alleges that Facebook and Instagram's algorithms facilitated child sexual harassment, with the complaint stating that Meta's own internal documents said over 100,000 kids were harassed daily. Facebook's "People You May Know" algorithm was singled out as a primary conduit to connect children to predators. The complaint alleges that Meta did nothing to stop this issue when approached by concerned employees.

With all of this in mind, it doesn’t really take a study to recognize that the “well-being” of users isn’t exactly the most important thing on the minds of social media CEOs. Still, if the program helps these companies move in the right direction, that’s certainly cool. COS says the study will take two years and that it’s still in the early planning stages. We’ll know more in the coming months. In the meantime, you can watch CEO Zuckerberg and all the rest testify before congress on Wednesday at 10 AM ET.

Japan's lunar lander has regained power a full nine days after it landed on the moon's surface nearly upside down and was subsequently switched off, JAXA (Japan Aerospace Exploration Agency) announced. A change in the sun's position allowed the solar panels to receive light and charge the probe's battery, allowing JAXA to re-establish communication. 

Things were looking dire shortly after the SLIM (Smart Lander for Investigating Moon) touched down. The agency immediately noticed a problem with power generation, but was able to launch a pair of probes onto the moon's surface. The Lunar Excursion Vehicle 2 (LEV-2) snapped an incredible photo of SLIM, showing it to be upside down with its panels pointing away from the sun. The cause was found to be a malfunction of the main engine.

JAXA thought there was a chance the probe could recover once the sun's rays pointed more toward the solar panels, and that's exactly what transpired. Shortly after power was regained, it snapped another picture of a previously imaged rock formation called "toy poodle" using a multi-band spectral camera. The team is also targeting several other rocks with canine-themed names, including "St. Bernard," "Bulldog" and "Shibainu."

The upside-down landing may have seemed like an unrecoverable fault, but it looks like the mission can now proceed more or less as planned. While the baseball-sized LEV-2 explores the surface (relaying data via the LEV-1 probe, which also has two cameras), SLIM will grab whatever science it can. 

In any case, the mission was already deemed a success, as the primary goal was a precision landing. It did just that, hitting a spot just 55 meters (180 feet) of its target. It's not known how much longer SLIM can function, as it was never designed to survive a solar night and the next one happens on Thursday. 

If there’s one thing we can all agree upon, it’s that the 21st century’s captains of industry are trying to shoehorn AI into every corner of our world. But for all of the ways in which AI will be shoved into our faces and not prove very successful, it might actually have at least one useful purpose. For instance, by dramatically speeding up the often decades-long process of designing, finding and testing new drugs.

Risk mitigation isn’t a sexy notion but it’s worth understanding how common it is for a new drug project to fail. To set the scene, consider that each drug project takes between three and five years to form a hypothesis strong enough to start tests in a laboratory. A 2022 study from Professor Duxin Sun found that 90 percent of clinical drug development fails, with each project costing more than $2 billion. And that number doesn’t even include compounds found to be unworkable at the preclinical stage. Put simply, every successful drug has to prop up at least $18 billion waste generated by its unsuccessful siblings, which all but guarantees that less lucrative cures for rarer conditions aren’t given as much focus as they may need.

Dr. Nicola Richmond is VP of AI at Benevolent, a biotech company using AI in its drug discovery process. She explained the classical system tasks researchers to find, for example, a misbehaving protein – the cause of disease – and then find a molecule that could make it behave. Once they've found one, they need to get that molecule into a form a patient can take, and then test if it’s both safe and effective. The journey to clinical trials on a living human patient takes years, and it’s often only then researchers find out that what worked in theory does not work in practice.

The current process takes “more than a decade and multiple billions of dollars of research investment for every drug approved,” said Dr. Chris Gibson, co-founder of Recursion, another company in the AI drug discovery space. He says AI’s great skill may be to dodge the misses and help avoid researchers spending too long running down blind alleys. A software platform that can churn through hundreds of options at a time can, in Gibson’s words, “fail faster and earlier so you can move on to other targets.”

CellProfiler / Carpenter-Singh laboratory at the Broad Institute

Dr. Anne E. Carpenter is the founder of the Carpenter-Singh laboratory at the Broad Institute of MIT and Harvard. She has spent more than a decade developing techniques in Cell Painting, a way to highlight elements in cells, with dyes, to make them readable by a computer. She is also the co-developer of Cell Profiler, a platform enabling researchers to use AI to scrub through vast troves of images of those dyed cells. Combined, this work makes it easy for a machine to see how cells change when they are impacted by the presence of disease or a treatment. And by looking at every part of the cell holistically – a discipline known as “omics” – there are greater opportunities for making the sort of connections that AI systems excel at.

Using pictures as a way of identifying potential cures seems a little left-field, since how things look don’t always represent how things actually are, right? Carpenter said humans have always made subconscious assumptions about medical status from sight alone. She explained most people may conclude someone may have a chromosomal issue just by looking at their face. And professional clinicians can identify a number of disorders by sight alone purely as a consequence of their experience. She added that if you took a picture of everyone’s face in a given population, a computer would be able to identify patterns and sort them based on common features.

This logic applies to the pictures of cells, where it’s possible for a digital pathologist to compare images from healthy and diseased samples. If a human can do it, then it should be faster and easier to employ a computer to spot these differences in scale so long as it’s accurate. “You allow this data to self-assemble into groups and now [you’re] starting to see patterns,” she explained, “when we treat [cells] with 100,000 different compounds, one by one, we can say ‘here’s two chemicals that look really similar to each other.’” And this looking really similar to each other isn’t just coincidence, but seems to be indicative of how they behave.

In one example, Carpenter cited that two different compounds could produce similar effects in a cell, and by extension could be used to treat the same condition. If so, then it may be that one of the two – which may not have been intended for this purpose – has fewer harmful side effects. Then there’s the potential benefit of being able to identify something that we didn’t know was affected by disease. “It allows us to say, ‘hey, there’s this cluster of six genes, five of which are really well known to be part of this pathway, but the sixth one, we didn’t know what it did, but now we have a strong clue it’s involved in the same biological process.” “Maybe those other five genes, for whatever reason, aren’t great direct targets themselves, maybe the chemicals don’t bind,” she said, “but the sixth one [could be] really great for that.”

FatCamera via Getty Images

In this context, the startups using AI in their drug discovery processes are hoping that they can find the diamonds hiding in plain sight. Dr. Richmond said that Benevolent’s approach is for the team to pick a disease of interest and then formulate a biological question around it. So, at the start of one project, the team might wonder if there are ways to treat ALS by enhancing, or fixing, the way a cell’s own housekeeping system works. (To be clear, this is a purely hypothetical example supplied by Dr. Richmond.)

That question is then run through Benevolent’s AI models, which pull together data from a wide variety of sources. They then produce a ranked list of potential answers to the question, which can include novel compounds, or existing drugs that could be adapted to suit. The data then goes to a researcher, who can examine what, if any, weight to give to its findings. Dr. Richmond added that the model has to provide evidence from existing literature or sources to support its findings even if its picks are out of left-field. And that, at all times, a human has the final say on what of its results should be pursued and how vigorously.

It’s a similar situation at Recursion, with Dr. Gibson claiming that its model is now capable of predicting “how any drug will interact with any disease without having to physically test it.” The model has now formed around three trillion predictions connecting potential problems to their potential solutions based on the data it has already absorbed and simulated. Gibson said that the process at the company now resembles a web search: Researchers sit down at a terminal, “type in a gene associated with breast cancer and [the system] populates all the other genes and compounds that [it believes are] related.”

“What gets exciting,” said Dr. Gibson, “is when [we] see a gene nobody has ever heard of in the list, which feels like novel biology because the world has no idea it exists.” Once a target has been identified and the findings checked by a human, the data will be passed to Recursion’s in-house scientific laboratory. Here, researchers will run initial experiments to see if what was found in the simulation can be replicated in the real world. Dr. Gibson said that Recursion’s wet lab, which uses large-scale automation, is capable of running more than two million experiments in a working week.

“About six weeks later, with very little human intervention, we’ll get the results,” said Dr. Gibson and, if successful, it’s then the team will “really start investing.” Because, until this point, the short period of validation work has cost the company “very little money and time to get.” The promise is that, rather than a three-year preclinical phase, that whole process can be crunched down to a few database searches, some oversight and then a few weeks of ex vivo testing to confirm if the system’s hunches are worth making a real effort to interrogate. Dr. Gibson said that it believes it has taken a “year’s worth of animal model work and [compressed] it, in many cases, to two months.”

Of course, there is not yet a concrete success story, no wonder cure that any company in this space can point to as a validation of the approach. But Recursion can cite one real-world example of how close its platform came to matching the success of a critical study. In April 2020, Recursion ran the COVID-19 sequence through its system to look at potential treatments. It examined both FDA-approved drugs and candidates in late-stage clinical trials. The system produced a list of nine potential candidates which would need further analysis, eight of which it would later be proved to be correct. It also said that Hydroxychloroquine and Ivermectin, both much-ballyhooed in the earliest days of the pandemic, would flop.

And there are AI-informed drugs that are currently undergoing real-world clinical trials right now. Recursion is pointing to five projects currently finishing their stage one (tests in healthy patients), or entering stage two (trials in people with the rare diseases in question) clinical testing right now. Benevolent has started a stage one trial of BEN-8744, a treatment for ulcerative colitis that may help with other inflammatory bowel disorders. And BEN-8744 is targeting an inhibitor that has no prior associations in the existing research which, if successful, will add weight to the idea that AIs can spot the connections humans have missed. Of course, we can’t make any conclusions until at least early next year when the results of those initial tests will be released.

Yuichiro Chino via Getty Images

There are plenty of unanswered questions, including how much we should rely upon AI as the sole arbiter of the drug discovery pipeline. There are also questions around the quality of the training data and the biases in the wider sources more generally. Dr. Richmond highlighted the issues around biases in genetic data sources both in terms of the homogeneity of cell cultures and how those tests are carried out. Similarly, Dr. Carpenter said the results of her most recent project, the publicly available JUMP-Cell Painting project, were based on cells from a single participant. “We picked it with good reason, but it’s still one human and one cell type from that one human.” In an ideal world, she’d have a far broader range of participants and cell types, but the issues right now center on funding and time, or more appropriately, their absence.

But, for now, all we can do is await the results of these early trials and hope that they bear fruit. Like every other potential application of AI, its value will rest largely in its ability to improve the quality of the work – or, more likely, improve the bottom line for the business in question. If AI can make the savings attractive enough, however, then maybe those diseases which are not likely to make back the investment demands under the current system may stand a chance. It could all collapse in a puff of hype, or it may offer real hope to families struggling for help while dealing with a rare disorder.