New research focuses on methods that could change medicine-making worldwide. The scientists propose bursting cells open, removing their DNA and using the cellular gears inside to make therapies.
Rao and his team of collaborators, which spans multiple research institutions, believe they have a better approach that may change medicine-making worldwide. They suggest forgoing the concept of using living cells as medicine-producers. Instead, they propose breaking the cells and using the remaining cellular gears for assembling the therapeutic compounds. Instead of inserting the DNA into living cells, the team burst them open, and removed their DNA altogether. Yet, the residual molecular machinery of ribosomes, polymerases and other cogwheels still functioned the way it would in a cell. “Now if you drop your DNA drug-making instructions into that soup, this machinery starts making what you need,” Rao explains. “And because you're no longer worrying about living cells, it becomes much simpler and more efficient.” The collaborators detail their cell-free protein synthesis or CFPS method in their recent paper published in preprint BioAxiv.
While CFPS does not use living cells, it still needs the basic building blocks to assemble proteins from—such as amino acids, nucleotides and certain types of enzymes. These are regularly added into this “soup” to keep the molecular factory chugging. “We just mix everything in as a batch and we let it integrate,” says James Robert Swartz, professor of chemical engineering and bioengineering at Stanford University and co-author of the paper. “And we make sure that we provide enough oxygen.” Rao likens the process to making milk from milk powder.
For a variety of reasons—from the field’s general inertia to regulatory approval hurdles—the method hasn’t become mainstream. The pandemic rekindled interest in medicines that can be made quickly and easily, so it drew more attention to the technology.
The idea of a cell-free protein synthesis is older than one might think. Swartz first experimented with it around 1997, when he was a chemical engineer at Genentech. While working on engineering bacteria to make pharmaceuticals, he discovered that there was a limit to what E. coli cells, the workhorse darling of pharma, could do. For example, it couldn’t grow and properly fold some complex proteins. “We tried many genetic engineering approaches, many fermentation, development, and environmental control approaches,” Swartz recalls—to no avail.
“The organism had its own agenda,” he quips. “And because everything was happening within the organism, we just couldn't really change those conditions very easily. Some of them we couldn’t change at all—we didn’t have control.”
It was out of frustration with the defiant bacteria that a new idea took hold. Could the cells be opened instead, so that the protein-forming reactions could be influenced more easily? “Obviously, we’d lose the ability for them to reproduce,” Swartz says. But that also meant that they no longer needed to keep the cells alive and could focus on making the specific reactions happen. “We could take the catalysts, the enzymes, and the more complex catalysts and activate them, make them work together, much as they would in a living cell, but the way we wanted.”
In 1998, Swartz joined Stanford, and began perfecting the biochemistry of the cell-free method, identifying the reactions he wanted to foster and stopping those he didn’t want. He managed to make the idea work, but for a variety of reasons—from the field’s general inertia to regulatory approval hurdles—the method hasn’t become mainstream. The pandemic rekindled interest in medicines that can be made quickly and easily, so it drew more attention to the technology. For their BioArxiv paper, the team tested the method by growing a specific antiviral protein called griffithsin.
First identified by Barry O’Keefe at National Cancer Institute over a decade ago, griffithsin is an antiviral known to interfere with many viruses’ ability to enter cells—including HIV, SARS, SARS-CoV-2, MERS and others. Originally isolated from the red algae Griffithsia, it works differently from antibodies and antibody cocktails.
Most antiviral medicines tend to target the specific receptors that viruses use to gain entry to the cells they infect. For example, SARS-CoV-2 uses the infamous spike protein to latch onto the ACE2 receptor of mammalian cells. The antibodies or other antiviral molecules stick to the spike protein, shutting off its ability to cling onto the ACE2 receptors. Unfortunately, the spike proteins mutate very often, so the medicines lose their potency. On the contrary, griffithsin has the ability to cling to the different parts of viral shells called capsids—namely to the molecules of mannose, a type of sugar. That extra stuff, glued all around the capsid like dead weight, makes it impossible for the virus to squeeze into the cell.
“Every time we have a vaccine or an antibody against a specific SARS-CoV-2 strain, that strain then mutates and so you lose efficacy,” Rao explains. “But griffithsin molecules glom onto the viral capsid, so the capsid essentially becomes a sticky mess and can’t enter the cell.” Mannose molecules also don’t mutate as easily as viruses’ receptors, so griffithsin-based antivirals do not have to be constantly updated. And because mannose molecules are found on many viruses’ capsids, it makes griffithsin “a universal neutralizer,” Rao explains.
“When griffithsin was discovered, we recognized that it held a lot of promise as a potential antiviral agent,” O’Keefe says. In 2010, he published a paper about griffithsin efficacy in neutralizing viruses of the corona family—after the first SARS outbreak in the early 2000s, the scientific community was interested in such antivirals. Yet, griffithsin is still not available as an off-the-shelf product. So during the Covid pandemic, the team experimented with synthesizing griffithsin using the cell-free production method. They were able to generate potent griffithsin in less than 24 hours without having to grow living cells.
The antiviral protein isn't the only type of medicine that can be made cell-free. The proteins needed for vaccine production could also be made the same way. “Such portable, on-demand drug manufacturing platforms can produce antiviral proteins within hours, making them ideal for combating future pandemics,” Rao says. “We would be able to stop the pandemic before it spreads.”
Top: Describes the process used in the study. Bottom: Describes how the new medicines and vaccines could be made at the site of a future viral outbreak.
Image courtesy of Rao and team, sourced from An approach to rapid distributed manufacturing of broad spectrumanti-viral griffithsin using cell-free systems to mitigate pandemics.
Rao’s idea is to perfect the technology to the point that any hospital or pharmacy can load up the media containing molecular factories, mix up the required amino acids, nucleotides and enzymes, and harvest the meds within hours. That will allow making medicines onsite and on demand. “That would be a self-contained production unit, so that you could just ship the production wherever the pandemic is breaking out,” says Swartz.
These units and the meds they produce, will, of course, have to undergo rigorous testing. “The biggest hurdles will be validating these against conventional technology,” Rao says. The biotech industry is risk-averse and prefers the familiar methods. But if this approach works, it may go beyond emergency situations and revolutionize the medicine-making paradigm even outside hospitals and pharmacies. Rao hopes that someday the method might become so mainstream that people may be able to buy and operate such reactors at home. “You can imagine a diabetic patient making insulin that way, or some other drugs,” Rao says. It would work not unlike making baby formula from the mere white powder. Just add water—and some oxygen, too.
Marielle Gross, a professor at the University of Pittsburgh, shows patients a new app that tracks how their samples are used during biomedical research.
Tissue donors can track what scientists do with their samples while safeguarding privacy, through a pilot program initiated in October by researchers at the Johns Hopkins Berman Institute of Bioethics and the University of Pittsburgh’s Institute for Precision Medicine. The program uses blockchain technology to offer patients this opportunity through the University of Pittsburgh's Breast Disease Research Repository, while assuring that their identities remain anonymous to investigators.
A blockchain is a digital, tamper-proof ledger of transactions duplicated and distributed across a computer system network. Whenever a transaction occurs with a patient’s sample, multiple stakeholders can track it while the owner’s identity remains encrypted. Special certificates called “nonfungible tokens,” or NFTs, represent patients’ unique samples on a trusted and widely used blockchain that reinforces transparency.
Blockchain could be used to notify people if cancer researchers discover that they have certain risk factors.
“Healthcare is very data rich, but control of that data often does not lie with the patient,” said Julius Bogdan, vice president of analytics for North America at the Healthcare Information and Management Systems Society (HIMSS), a Chicago-based global technology nonprofit. “NFTs allow for the encapsulation of a patient’s data in a digital asset controlled by the patient.” He added that this technology enables a more secure and informed method of participating in clinical and research trials.
Without this technology, de-identification of patients’ samples during biomedical research had the unintended consequence of preventing them from discovering what researchers find -- even if that data could benefit their health. A solution was urgently needed, said Marielle Gross, assistant professor of obstetrics, gynecology and reproductive science and bioethics at the University of Pittsburgh School of Medicine.
“A researcher can learn something from your bio samples or medical records that could be life-saving information for you, and they have no way to let you or your doctor know,” said Gross, who is also an affiliate assistant professor at the Berman Institute. “There’s no good reason for that to stay the way that it is.”
For instance, blockchain could be used to notify people if cancer researchers discover that they have certain risk factors. Gross estimated that less than half of breast cancer patients are tested for mutations in BRCA1 and BRCA2 — tumor suppressor genes that are important in combating cancer. With normal function, these genes help prevent breast, ovarian and other cells from proliferating in an uncontrolled manner. If researchers find mutations, it’s relevant for a patient’s and family’s follow-up care — and that’s a prime example of how this newly designed app could play a life-saving role, she said.
Liz Burton was one of the first patients at the University of Pittsburgh to opt for the app -- called de-bi, which is short for decentralized biobank -- before undergoing a mastectomy for early-stage breast cancer in November, after it was diagnosed on a routine mammogram. She often takes part in medical research and looks forward to tracking her tissues.
“Anytime there’s a scientific experiment or study, I’m quick to participate -- to advance my own wellness as well as knowledge in general,” said Burton, 49, a life insurance service representative who lives in Carnegie, Pa. “It’s my way of contributing.”
Liz Burton was one of the first patients at the University of Pittsburgh to opt for the app before undergoing a mastectomy for early-stage breast cancer.
Liz Burton
The pilot program raises the issue of what investigators may owe study participants, especially since certain populations, such as Black and indigenous peoples, historically were not treated in an ethical manner for scientific purposes. “It’s a truly laudable effort,” Tamar Schiff, a postdoctoral fellow in medical ethics at New York University’s Grossman School of Medicine, said of the endeavor. “Research participants are beautifully altruistic.”
Lauren Sankary, a bioethicist and associate director of the neuroethics program at Cleveland Clinic, agrees that the pilot program provides increased transparency for study participants regarding how scientists use their tissues while acknowledging individuals’ contributions to research.
However, she added, “it may require researchers to develop a process for ongoing communication to be responsive to additional input from research participants.”
Peter H. Schwartz, professor of medicine and director of Indiana University’s Center for Bioethics in Indianapolis, said the program is promising, but he wonders what will happen if a patient has concerns about a particular research project involving their tissues.
“I can imagine a situation where a patient objects to their sample being used for some disease they’ve never heard about, or which carries some kind of stigma like a mental illness,” Schwartz said, noting that researchers would have to evaluate how to react. “There’s no simple answer to those questions, but the technology has to be assessed with an eye to the problems it could raise.”
To truly make a difference, blockchain must enable broad consent from patients, not just de-identification.
As a result, researchers may need to factor in how much information to share with patients and how to explain it, Schiff said. There are also concerns that in tracking their samples, patients could tell others what they learned before researchers are ready to publicly release this information. However, Bogdan, the vice president of the HIMSS nonprofit, believes only a minimal study identifier would be stored in an NFT, not patient data, research results or any type of proprietary trial information.
Some patients may be confused by blockchain and reluctant to embrace it. “The complexity of NFTs may prevent the average citizen from capitalizing on their potential or vendors willing to participate in the blockchain network,” Bogdan said. “Blockchain technology is also quite costly in terms of computational power and energy consumption, contributing to greenhouse gas emissions and climate change.”
In addition, this nascent, groundbreaking technology is immature and vulnerable to data security flaws, disputes over intellectual property rights and privacy issues, though it does offer baseline protections to maintain confidentiality. To truly make a difference, blockchain must enable broad consent from patients, not just de-identification, said Robyn Shapiro, a bioethicist and founding attorney at Health Sciences Law Group near Milwaukee.
The Henrietta Lacks story is a prime example, Shapiro noted. During her treatment for cervical cancer at Johns Hopkins, Lacks’s tissue was de-identified (albeit not entirely, because her cell line, HeLa, bore her initials). After her death, those cells were replicated and distributed for important and lucrative research and product development purposes without her knowledge or consent.
Nonetheless, Shapiro thinks that the initiative by the University of Pittsburgh and Johns Hopkins has potential to solve some ethical challenges involved in research use of biospecimens. “Compared to the system that allowed Lacks’s cells to be used without her permission, Shapiro said, “blockchain technology using nonfungible tokens that allow patients to follow their samples may enhance transparency, accountability and respect for persons who contribute their tissue and clinical data for research.”
Read more about laws that have prevented people from the rights to their own cells.
The U.S. has the highest incarceration rate in the world, costing $182 billion per year, partly because its antiquated data systems often fail to identify people who should be released. A tech nonprofit is trying to change that.
Recidiviz has built a platform that connects the different databases, with the goal of identifying people who are already qualified for release but remain behind bars or on supervision. “Think of Recidiviz like Google Maps,” says Jacoby, who worked on Maps when she was at the tech giant. Google Maps takes in data from different sources – satellite images, street maps, local business data — and organizes it into one easy view. “Recidiviz does something similar with criminal justice data,” Jacoby explains, “making it easy to identify people eligible to come home or to move to less intensive levels of supervision.”
People like Jacoby’s uncle. His experience with incarceration is what inspired her passion for criminal justice reform in the first place.
The problems are vast
The U.S. has the highest incarceration rate in the world — 2 million people according to the watchdog group, Prison Policy Initiative — at a cost of $182 billion a year. The numbers could be a lot lower if not for an array of problems including inaccurate sentencing calculations, flawed algorithms and parole violations laws.
Sentencing miscalculations
To determine eligibility for release, the current system requires corrections officers to check 21 different requirements spread across five different databases for each of the 90 to 100 people under their supervision. These manual calculations are time prohibitive, says Jacoby, and fall victim to human error.
In addition, Recidiviz found that policies aimed at helping to reduce the prison population don’t always work correctly. A key example is time off for good behavior laws that allow inmates to earn one day off for every 30 days of good behavior. Some states' data systems are built to calculate time off as one day per month of good behavior, rather than per day. Over the course of a decade-long sentence, Jacoby says these miscalculations can lead to a huge discrepancy in the calculated release data and the actual release date.
Algorithms
Commercial algorithm-based software systems for risk assessment continue to be widely used in the criminal justice system, even though a 2018 study published in Science Advances exposed their limitations. After the study went viral, it took three years for the Justice Department to issue a report on their own flawed algorithms used to reduce the federal prison population as part of the 2018 First Step Act. The program, it was determined, overestimated the risk of putting inmates of color into early-release programs.
Despite its name, Recidiviz does not build these types of algorithms for predicting recidivism, or whether someone will commit another crime after being released from prison. Rather, Jacoby says the company’s "descriptive analytics” approach is specifically intended to weed out incarceration inequalities and avoid algorithmic pitfalls.
Parole violation laws
Research shows that 350,000 people a year — about a quarter of the total prison population — are sent back not because they’ve committed another crime, but because they’ve broken a specific rule of their probation. “Things that wouldn't send you or I to prison, but would send someone on parole,” such as crossing county lines or being in the presence of alcohol when they shouldn’t be, are inflating the prison population, says Jacoby.
It’s personal for the co-founder and CEO
“I grew up with an uncle who went into the prison system,” Jacoby says. At 19, he was sentenced to ten years in prison for a non-violent crime. A few months after being released from jail, he was sent back for a non-violent parole violation.
“For my family, the fact that one in four prison admissions are driven not by a crime but by someone who's broken a rule on probation and parole was really profound because that happened to my uncle,” Jacoby says. The experience led her to begin studying criminal justice in high school, then college. She continued her dive into how the criminal justice system works as part of her Passion Project while at Google, a program that allows employees to spend 20 percent of their time on pro-bono work. Two colleagues whose family members had also been stuck in the system joined her.
As part of the project, Jacoby interviewed hundreds of people involved in the criminal justice system. “Those on the right, those on the left, agreed that bad data was slowing down reform,” she says. Their research brought them to North Dakota where they began to understand the root of the problem. The corrections department is making “huge, consequential decisions every day [without] … the data,” Jacoby says. In a new video by Recidiviz not yet released, Jacoby recounts her exchange with the state’s director of corrections who told her, “‘It’s not that we have the data and we just don’t know how to make it public; we don’t have the information you think we have.'"
A mock-up (with fake data) of the types of dashboards and insights that Recidiviz provides to state governments.
Recidiviz
As a software engineer, Jacoby says the comment made no sense to her — until she witnessed it first-hand. “We spent a lot of time driving around in cars with corrections directors and parole officers watching them use these incredibly taxing, frankly terrible, old data systems,” Jacoby says.
As they weeded through thousands of files — some computerized, some on paper — they unearthed the consequences of bad data: Hundreds of people in prison well past their release date and thousands more whose release from parole was delayed because of minor paperwork issues. They found individuals stuck in parole because they hadn’t checked one last item off their eligibility list — like simply failing to provide their parole officer with a paystub. And, even when parolees advocated for themselves, the archaic system made it difficult for their parole officers to confirm their eligibility, so they remained in the system. Jacoby and her team also unpacked specific policies that drive racial disparities — such as fines and fees.
The Solution
It’s more than a trivial technical challenge to bring the incomplete, fragmented data onto a 21st century data platform. It takes months for Recidiviz to sift through a state’s information systems to connect databases “with the goal of tracking a person all the way through their journey and find out what’s working for 18- to 25-year-old men, what’s working for new mothers,” explains Jacoby in the video.
TED Talk: How bad data traps people in the U.S. justice system
TED Fellow Clementine Jacoby's TED Talk went live on Jan. 13. It describes how we can fix bad data in the criminal justice system, "bringing thousands of people home, reducing costs and improving public safety along the way."
Clementine Jacoby • TED2022
Ojmarrh Mitchell, an associate professor in the School of Criminology and Criminal Justice at Arizona State University, who is not involved with the company, says what Recidiviz is doing is “remarkable.” His perspective goes beyond academic analysis. In his pre-academic years, Mitchell was a probation officer, working within the framework of the “well known, but invisible” information sharing issues that plague criminal justice departments. The flexibility of Recidiviz’s approach is what makes it especially innovative, he says. “They identify the specific gaps in each jurisdiction and tailor a solution for that jurisdiction.”
On the downside, the process used by Recidiviz is “a bit opaque,” Mitchell says, with few details available on how Recidiviz designs its tools and tracks outcomes. By sharing more information about how its actions lead to progress in a given jurisdiction, Recidiviz could help reformers in other places figure out which programs have the best potential to work well.
The eleven states in which Recidiviz is working include California, Colorado, Maine, Michigan, Missouri, Pennsylvania and Tennessee. And a pilot program launched last year in Idaho, if scaled nationally, with could reduce the number of people in the criminal justice system by a quarter of a million people, Jacoby says. As part of the pilot, rather than relying on manual calculations, Recidiviz is equipping leaders and the probation officers with actionable information with a few clicks of an app that Recidiviz built.
Mitchell is disappointed that there’s even the need for Recidiviz. “This is a problem that government agencies have a responsibility to address,” he says. “But they haven’t.” For one company to come along and fill such a large gap is “remarkable.”