New tools could catch disease outbreaks earlier - or predict them
Every year, the villages which lie in the so-called ‘Nipah belt’— which stretches along the western border between Bangladesh and India, brace themselves for the latest outbreak. For since 1998, when Nipah virus—a form of hemorrhagic fever most common in Bangladesh—first spilled over into humans, it has been a grim annual visitor to the people of this region.
With a 70 percent fatality rate, no vaccine, and no known treatments, Nipah virus has been dubbed in the Western world as ‘the worst disease no one has ever heard of.’ Currently, outbreaks tend to be relatively contained because it is not very transmissible. The virus circulates throughout Asia in fruit eating bats, and only tends to be passed on to people who consume contaminated date palm sap, a sweet drink which is harvested across Bangladesh.
But as SARS-CoV-2 has shown the world, this can quickly change.
“Nipah virus is among what virologists call ‘the Big 10,’ along with things like Lassa fever and Crimean Congo hemorrhagic fever,” says Noam Ross, a disease ecologist at New York-based non-profit EcoHealth Alliance. “These are pretty dangerous viruses from a lethality perspective, which don’t currently have the capacity to spread into broader human populations. But that can evolve, and you could very well see a variant emerge that has human-human transmission capability.”
That’s not an overstatement. Surveys suggest that mammals harbour about 40,000 viruses, with roughly a quarter capable of infecting humans. The vast majority never get a chance to do so because we don’t encounter them, but climate change can alter that. Recent studies have found that as animals relocate to new habitats due to shifting environmental conditions, the coming decades will bring around 300,000 first encounters between species which normally don’t interact, especially in tropical Africa and southeast Asia. All these interactions will make it far more likely for hitherto unknown viruses to cross paths with humans.
That’s why for the last 16 years, EcoHealth Alliance has been conducting ongoing viral surveillance projects across Bangladesh. The goal is to understand why Nipah is so much more prevalent in the western part of the country, compared to the east, and keep a watchful eye out for new Nipah strains as well as other dangerous pathogens like Ebola.
"There are a lot of different infectious agents that are sensitive to climate change that don't have these sorts of software tools being developed for them," says Cat Lippi, medical geography researcher at the University of Florida.
Until very recently this kind of work has been hampered by the limitations of viral surveillance technology. The PREDICT project, a $200 million initiative funded by the United States Agency for International Development, which conducted surveillance across the Amazon Basin, Congo Basin and extensive parts of South and Southeast Asia, relied upon so-called nucleic acid assays which enabled scientists to search for the genetic material of viruses in animal samples.
However, the project came under criticism for being highly inefficient. “That approach requires a big sampling effort, because of the rarity of individual infections,” says Ross. “Any particular animal may be infected for a couple of weeks, maybe once or twice in its lifetime. So if you sample thousands and thousands of animals, you'll eventually get one that has an Ebola virus infection right now.”
Ross explains that there is now far more interest in serological sampling—the scientific term for the process of drawing blood for antibody testing. By searching for the presence of antibodies in the blood of humans and animals, scientists have a greater chance of detecting viruses which started circulating recently.
Despite the controversy surrounding EcoHealth Alliance’s involvement in so-called gain of function research—experiments that study whether viruses might mutate into deadlier strains—the organization’s separate efforts to stay one step ahead of pathogen evolution are key to stopping the next pandemic.
“Having really cheap and fast surveillance is really important,” says Ross. “Particularly in a place where there's persistent, low level, moderate infections that potentially have the ability to develop into more epidemic or pandemic situations. It means there’s a pathway that something more dangerous can come through."
Scientists are searching for the presence of antibodies in the blood of humans and animals in hopes to detect viruses that recently started circulating.
EcoHealth Alliance
In Bangladesh, EcoHealth Alliance is attempting to do this using a newer serological technology known as a multiplex Luminex assay, which tests samples against a panel of known antibodies against many different viruses. It collects what Ross describes as a ‘footprint of information,’ which allows scientists to tell whether the sample contains the presence of a known pathogen or something completely different and needs to be investigated further.
By using this technology to sample human and animal populations across the country, they hope to gain an idea of whether there are any novel Nipah virus variants or strains from the same family, as well as other deadly viral families like Ebola.
This is just one of several novel tools being used for viral discovery in surveillance projects around the globe. Multiple research groups are taking PREDICT’s approach of looking for novel viruses in animals in various hotspots. They collect environmental DNA—mucus, faeces or shed skin left behind in soil, sediment or water—which can then be genetically sequenced.
Five years ago, this would have been a painstaking work requiring bringing collected samples back to labs. Today, thanks to the vast amounts of money spent on new technologies during COVID-19, researchers now have portable sequencing tools they can take out into the field.
Christopher Jerde, a researcher at the UC Santa Barbara Marine Science Institute, points to the Oxford Nanopore MinION sequencer as one example. “I tried one of the early versions of it four years ago, and it was miserable,” he says. “But they’ve really improved, and what we’re going to be able to do in the next five to ten years will be amazing. Instead of having to carefully transport samples back to the lab, we're going to have cigar box-shaped sequencers that we take into the field, plug into a laptop, and do the whole sequencing of an organism.”
In the past, viral surveillance has had to be very targeted and focused on known families of viruses, potentially missing new, previously unknown zoonotic pathogens. Jerde says that the rise of portable sequencers will lead to what he describes as “true surveillance.”
“Before, this was just too complex,” he says. “It had to be very focused, for example, looking for SARS-type viruses. Now we’re able to say, ‘Tell us all the viruses that are here?’ And this will give us true surveillance – we’ll be able to see the diversity of all the pathogens which are in these spots and have an understanding of which ones are coming into the population and causing damage.”
But being able to discover more viruses also comes with certain challenges. Some scientists fear that the speed of viral discovery will soon outpace the human capacity to analyze them all and assess the threat that they pose to us.
“I think we're already there,” says Jason Ladner, assistant professor at Northern Arizona University’s Pathogen and Microbiome Institute. “If you look at all the papers on the expanding RNA virus sphere, there are all of these deposited partial or complete viral sequences in groups that we just don't know anything really about yet.” Bats, for example, carry a myriad of viruses, whose ability to infect human cells we understand very poorly.
Cultivating these viruses under laboratory conditions and testing them on organoids— miniature, simplified versions of organs created from stem cells—can help with these assessments, but it is a slow and painstaking work. One hope is that in the future, machine learning could help automate this process. The new SpillOver Viral Risk Ranking platform aims to assess the risk level of a given virus based on 31 different metrics, while other computer models have tried to do the same based on the similarity of a virus’s genomic sequence to known zoonotic threats.
However, Ladner says that these types of comparisons are still overly simplistic. For one thing, scientists are still only aware of a few hundred zoonotic viruses, which is a very limited data sample for accurately assessing a novel pathogen. Instead, he says that there is a need for virologists to develop models which can determine viral compatibility with human cells, based on genomic data.
“One thing which is really useful, but can be challenging to do, is understand the cell surface receptors that a given virus might use,” he says. “Understanding whether a virus is likely to be able to use proteins on the surface of human cells to gain entry can be very informative.”
As the Earth’s climate heats up, scientists also need to better model the so-called vector borne diseases such as dengue, Zika, chikungunya and yellow fever. Transmitted by the Aedes mosquito residing in humid climates, these blights currently disproportionally affect people in low-income nations. But predictions suggest that as the planet warms and the pests find new homes, an estimated one billion people who currently don’t encounter them might be threatened by their bites by 2080. “When it comes to mosquito-borne diseases we have to worry about shifts in suitable habitat,” says Cat Lippi, a medical geography researcher at the University of Florida. “As climate patterns change on these big scales, we expect to see shifts in where people will be at risk for contracting these diseases.”
Public health practitioners and government decision-makers need tools to make climate-informed decisions about the evolving threat of different infectious diseases. Some projects are already underway. An ongoing collaboration between the Catalan Institution for Research and Advanced Studies and researchers in Brazil and Peru is utilizing drones and weather stations to collect data on how mosquitoes change their breeding patterns in response to climate shifts. This information will then be fed into computer algorithms to predict the impact of mosquito-borne illnesses on different regions.
The team at the Catalan Institution for Research and Advanced Studies is using drones and weather stations to collect data on how mosquito breeding patterns change due to climate shifts.
Gabriel Carrasco
Lippi says that similar models are urgently needed to predict how changing climate patterns affect respiratory, foodborne, waterborne and soilborne illnesses. The UK-based Wellcome Trust has allocated significant assets to fund such projects, which should allow scientists to monitor the impact of climate on a much broader range of infections. “There are a lot of different infectious agents that are sensitive to climate change that don't have these sorts of software tools being developed for them,” she says.
COVID-19’s havoc boosted funding for infectious disease research, but as its threats begin to fade from policymakers’ focus, the money may dry up. Meanwhile, scientists warn that another major infectious disease outbreak is inevitable, potentially within the next decade, so combing the planet for pathogens is vital. “Surveillance is ultimately a really boring thing that a lot of people don't want to put money into, until we have a wide scale pandemic,” Jerde says, but that vigilance is key to thwarting the next deadly horror. “It takes a lot of patience and perseverance to keep looking.”
This article originally appeared in One Health/One Planet, a single-issue magazine that explores how climate change and other environmental shifts are increasing vulnerabilities to infectious diseases by land and by sea. The magazine probes how scientists are making progress with leaders in other fields toward solutions that embrace diverse perspectives and the interconnectedness of all lifeforms and the planet.
Story by Big Think
For most of history, artificial intelligence (AI) has been relegated almost entirely to the realm of science fiction. Then, in late 2022, it burst into reality — seemingly out of nowhere — with the popular launch of ChatGPT, the generative AI chatbot that solves tricky problems, designs rockets, has deep conversations with users, and even aces the Bar exam.
But the truth is that before ChatGPT nabbed the public’s attention, AI was already here, and it was doing more important things than writing essays for lazy college students. Case in point: It was key to saving the lives of tens of millions of people.
AI-designed mRNA vaccines
As Dave Johnson, chief data and AI officer at Moderna, told MIT Technology Review‘s In Machines We Trust podcast in 2022, AI was integral to creating the company’s highly effective mRNA vaccine against COVID. Moderna and Pfizer/BioNTech’s mRNA vaccines collectively saved between 15 and 20 million lives, according to one estimate from 2022.
Johnson described how AI was hard at work at Moderna, well before COVID arose to infect billions. The pharmaceutical company focuses on finding mRNA therapies to fight off infectious disease, treat cancer, or thwart genetic illness, among other medical applications. Messenger RNA molecules are essentially molecular instructions for cells that tell them how to create specific proteins, which do everything from fighting infection, to catalyzing reactions, to relaying cellular messages.
Johnson and his team put AI and automated robots to work making lots of different mRNAs for scientists to experiment with. Moderna quickly went from making about 30 per month to more than one thousand. They then created AI algorithms to optimize mRNA to maximize protein production in the body — more bang for the biological buck.
For Johnson and his team’s next trick, they used AI to automate science, itself. Once Moderna’s scientists have an mRNA to experiment with, they do pre-clinical tests in the lab. They then pore over reams of data to see which mRNAs could progress to the next stage: animal trials. This process is long, repetitive, and soul-sucking — ill-suited to a creative scientist but great for a mindless AI algorithm. With scientists’ input, models were made to automate this tedious process.
“We don’t think about AI in the context of replacing humans,” says Dave Johnson, chief data and AI officer at Moderna. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
All these AI systems were in put in place over the past decade. Then COVID showed up. So when the genome sequence of the coronavirus was made public in January 2020, Moderna was off to the races pumping out and testing mRNAs that would tell cells how to manufacture the coronavirus’s spike protein so that the body’s immune system would recognize and destroy it. Within 42 days, the company had an mRNA vaccine ready to be tested in humans. It eventually went into hundreds of millions of arms.
Biotech harnesses the power of AI
Moderna is now turning its attention to other ailments that could be solved with mRNA, and the company is continuing to lean on AI. Scientists are still coming to Johnson with automation requests, which he happily obliges.
“We don’t think about AI in the context of replacing humans,” he told the Me, Myself, and AI podcast. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
Moderna, which was founded as a “digital biotech,” is undoubtedly the poster child of AI use in mRNA vaccines. Moderna recently signed a deal with IBM to use the company’s quantum computers as well as its proprietary generative AI, MoLFormer.
Moderna’s success is encouraging other companies to follow its example. In January, BioNTech, which partnered with Pfizer to make the other highly effective mRNA vaccine against COVID, acquired the company InstaDeep for $440 million to implement its machine learning AI across its mRNA medicine platform. And in May, Chinese technology giant Baidu announced an AI tool that designs super-optimized mRNA sequences in minutes. A nearly countless number of mRNA molecules can code for the same protein, but some are more stable and result in the production of more proteins. Baidu’s AI, called “LinearDesign,” finds these mRNAs. The company licensed the tool to French pharmaceutical company Sanofi.
Writing in the journal Accounts of Chemical Research in late 2021, Sebastian M. Castillo-Hair and Georg Seelig, computer engineers who focus on synthetic biology at the University of Washington, forecast that AI machine learning models will further accelerate the biotechnology research process, putting mRNA medicine into overdrive to the benefit of all.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
Opioid prescription policies may hurt those in chronic pain
Tinu Abayomi-Paul works as a writer and activist, plus one unwanted job: Trying to fill her opioid prescription. She says that some pharmacists laugh and tell her that no one needs the amount of pain medication that she is seeking. Another pharmacist near her home in Venus, Tex., refused to fill more than seven days of a 30-day prescription.
To get a new prescription—partially filled opioid prescriptions can’t be dispensed later—Abayomi-Paul needed to return to her doctor’s office. But without her medication, she was having too much pain to travel there, much less return to the pharmacy. She rationed out the pills over several weeks, an agonizing compromise that left her unable to work, interact with her children, sleep restfully, or leave the house. “Don’t I deserve to do more than survive?” she says.
Abayomi-Paul’s pain results from a degenerative spine disorder, chronic lymphocytic leukemia, and more than a dozen other diagnoses and disabilities. She is part of a growing group of people with chronic pain who have been negatively impacted by the fallout from efforts to prevent opioid overdose deaths.
Guidelines for dispensing these pills are complicated because many opioids, like codeine, oxycodone, and morphine, are prescribed legally for pain. Yet, deaths from opioids have increased rapidly since 1999 and become a national emergency. Many of them, such as heroin, are used illegally. The CDC identified three surges in opioid use: an increase in opioid prescriptions in the ‘90s, a surge of heroin around 2010, and an influx of fentanyl and other powerful synthetic opioids in 2013.
As overdose deaths grew, so did public calls to address them, prompting the CDC to change its prescription guidelines in 2016. The new guidelines suggested limiting medication for acute pain to a seven-day supply, capping daily doses of morphine, and other restrictions. Some statistics suggest that these policies have worked; from 2016 to 2019, prescriptions for opiates fell 44 percent. Physicians also started progressively lowering opioid doses for patients, a practice called tapering. A study tracking nearly 100,000 Medicare subscribers on opioids found that about 13 percent of patients were tapering in 2012, and that number increased to about 23 percent by 2017.
But some physicians may be too aggressive with this tapering strategy. About one in four people had doses reduced by more than 10 percent per week, a rate faster than the CDC recommends. The approach left people like Abayomi-Paul without the medication they needed. Every year, Abayomi-Paul says, her prescriptions are harder to fill. David Brushwood, a pharmacy professor who specializes in policy and outcomes at the University of Florida in Gainesville, says opioid dosing isn’t one-size-fits-all. “Patients need to be taken care of individually, not based on what some government agency says they need,” he says.
‘This is not survivable’
Health policy and disability rights attorney Erin Gilmer advocated for people with pain, using her own experience with chronic pain and a host of medical conditions as a guidepost. She launched an advocacy website, Healthcare as a Human Right, and shared her struggles on Twitter: “This pain is more than anything I've endured before and I've already been through too much. Yet because it's not simply identified no one believes it's as bad as it is. This is not survivable.”
When her pain dramatically worsened midway through 2021, Gilmer’s posts grew ominous: “I keep thinking it can't possibly get worse but somehow every day is worse than the last.”
The CDC revised its guidelines in 2022 after criticisms that people with chronic pain were being undertreated, enduring dangerous withdrawal symptoms, and suffering psychological distress. (Long-term opioid use can cause physical dependency, an adaptive reaction that is different than the compulsive misuse associated with a substance use disorder.) It was too late for Gilmer. On July 7, 2021, the 38-year-old died by suicide.
Last August, an Ohio district court ruling set forth a new requirement for Walgreens, Walmart, and CVS pharmacists in two counties. These pharmacists must now document opioid prescriptions that are turned down, even for customers who have no previous purchases at that pharmacy, and they’re required to share this information with other locations in the same chain. None of the three pharmacies responded to an interview request from Leaps.org.
In a practice called red flagging, pharmacists may label a prescription suspicious for a variety of reasons, such as if a pharmacist observes an unusually high dose, a long distance from the patient’s home to the pharmacy, or cash payment. Pharmacists may question patients or prescribers to resolve red flags but, regardless of the explanation, they’re free to refuse to fill a prescription.
As the risk of litigation has grown, so has finger-pointing, says Seth Whitelaw, a compliance consultant at Whitelaw Compliance Group in West Chester, PA, who advises drug, medical device, and biotech companies. Drugmakers accused in National Prescription Opioid Litigation (NPOL), a complex set of thousands of cases on opioid epidemic deaths, which includes the Ohio district case, have argued that they shouldn’t be responsible for the large supply of opiates and overdose deaths. Yet, prosecutors alleged that these pharmaceutical companies hid addiction and overdose risks when labeling opioids, while distributors and pharmacists failed to identify suspicious orders or scripts.
Patients and pharmacists fear red flags
The requirements that pharmacists document prescriptions they refuse to fill so far only apply to two counties in Ohio. But Brushwood fears they will spread because of this precedent, and because there’s no way for pharmacists to predict what new legislation is on the way. “There is no definition of a red flag, there are no lists of red flags. There is no instruction on what to do when a red flag is detected. There’s no guidance on how to document red flags. It is a standardless responsibility,” Brushwood says. This adds trepidation for pharmacists—and more hoops to jump through for patients.
“I went into the doctor one day here and she said, ‘I'm going to stop prescribing opioids to all my patients effective immediately,” Nicolson says.
“We now have about a dozen studies that show that actually ripping somebody off their medication increases their risk of overdose and suicide by three to five times, destabilizes their health and mental health, often requires some hospitalization or emergency care, and can cause heart attacks,” says Kate Nicolson, founder of the National Pain Advocacy Center based in Boulder, Colorado. “It can kill people.” Nicolson was in pain for decades due to a surgical injury to the nerves leading to her spinal cord before surgeries fixed the problem.
Another issue is that primary care offices may view opioid use as a reason to turn down new patients. In a 2021 study, secret shoppers called primary care clinics in nine states, identifying themselves as long-term opioid users. When callers said their opioids were discontinued because their former physician retired, as opposed to an unspecified reason, they were more likely to be offered an appointment. Even so, more than 40 percent were refused an appointment. The study authors say their findings suggest that some physicians may try to avoid treating people who use opioids.
Abayomi-Paul says red flagging has changed how she fills prescriptions. “Once I go to one place, I try to [continue] going to that same place because of the amount of records that I have and making sure my medications don’t conflict,” Abayomi-Paul says.
Nicolson moved to Colorado from Washington D.C. in 2015, before the CDC issued its 2016 guidelines. When the guidelines came out, she found the change to be shockingly abrupt. “I went into the doctor one day here and she said, ‘I'm going to stop prescribing opioids to all my patients effective immediately.’” Since then, she’s spoken with dozens of patients who have been red-flagged or simply haven’t been able to access pain medication.
Despite her expertise, Nicolson isn’t positive she could successfully fill an opioid prescription today even if she needed one. At this point, she’s not sure exactly what various pharmacies would view as a red flag. And she’s not confident that these red flags even work. “You can have very legitimate reasons for being 50 miles away or having to go to multiple pharmacies, given that there are drug shortages now, as well as someone refusing to fill [a prescription.] It doesn't mean that you’re necessarily ‘drug seeking.’”
While there’s no easy solution. Whitelaw says clarifying the role of pharmacists and physicians in patient access to opioids could help people get the medication they need. He is seeking policy changes that focus on the needs of people in pain more than the number of prescriptions filled. He also advocates standardizing the definition of red flags and procedures for resolving them. Still, there will never be a single policy that can be applied to all people, explains Brushwood, the University of Florida professor. “You have to make a decision about each individual prescription.”