FDA, researchers work to make clinical trials more diverse
Nestled in a predominately Hispanic neighborhood, a new mural outside Guadalupe Centers Middle School in Kansas City, Missouri imparts a powerful message: “Clinical Research Needs Representation.” The colorful portraits painted above those words feature four cancer survivors of different racial and ethnic backgrounds. Two individuals identify as Hispanic, one as African American and another as Native American.
One of the patients depicted in the mural is Kim Jones, a 51-year-old African American breast cancer survivor since 2012. She advocated for an African American friend who participated in several clinical trials for ovarian cancer. Her friend was diagnosed in an advanced stage at age 26 but lived nine more years, thanks to the trials testing new therapeutics. “They are definitely giving people a longer, extended life and a better quality of life,” said Jones, who owns a nail salon. And that’s the message the mural aims to send to the community: Clinical trials need diverse participants.
While racial and ethnic minority groups represent almost half of the U.S. population, the lack of diversity in clinical trials poses serious challenges. Limited awareness and access impede equitable representation, which is necessary to prove the safety and effectiveness of medical interventions across different groups.
A Yale University study on clinical trial diversity published last year in BMJ Medicine found that while 81 percent of trials testing the new cancer drugs approved by the U.S. Food and Drug Administration between 2012 and 2017 included women, only 23 percent included older adults and 5 percent fairly included racial and ethnic minorities. “It’s both a public health and social justice issue,” said Jennifer E. Miller, an associate professor of medicine at Yale School of Medicine. “We need to know how medicines and vaccines work for all clinically distinct groups, not just healthy young White males.” A recent JAMA Oncology editorial stresses out the need for legislation that would require diversity action plans for certain types of trials.
Ensuring meaningful representation of racial and ethnic minorities in clinical trials for regulated medical products is fundamental to public health.--FDA Commissioner Robert M. Califf.
But change is on the horizon. Last April, the FDA issued a new draft guidance encouraging industry to find ways to revamp recruitment into clinical trials. The announcement, which expanded on previous efforts, called for including more participants from underrepresented racial and ethnic segments of the population.
“The U.S. population has become increasingly diverse, and ensuring meaningful representation of racial and ethnic minorities in clinical trials for regulated medical products is fundamental to public health,” FDA commissioner Robert M. Califf, a physician, said in a statement. “Going forward, achieving greater diversity will be a key focus throughout the FDA to facilitate the development of better treatments and better ways to fight diseases that often disproportionately impact diverse communities. This guidance also further demonstrates how we support the Administration’s Cancer Moonshot goal of addressing inequities in cancer care, helping to ensure that every community in America has access to cutting-edge cancer diagnostics, therapeutics and clinical trials.”
Lola Fashoyin-Aje, associate director for Science and Policy to Address Disparities in the Oncology Center of Excellence at the FDA, said that the agency “has long held the view that clinical trial participants should reflect the clinical and demographic characteristics of the patients who will ultimately receive the drug once approved.” However, “numerous studies over many decades” have measured the extent of underrepresentation. One FDA analysis found that the proportion of White patients enrolled in U.S. clinical trials (88 percent) is much higher than their numbers in country's population. Meanwhile, the enrollment of African American and Native Hawaiian/American Indian and Alaskan Native patients is below their national numbers.
The FDA’s guidance is accelerating researchers’ efforts to be more inclusive of diverse groups in clinical trials, said Joyce Sackey, a clinical professor of medicine and associate dean at Stanford School of Medicine. Underrepresentation is “a huge issue,” she noted. Sackey is focusing on this in her role as the inaugural chief equity, diversity and inclusion officer at Stanford Medicine, which encompasses the medical school and two hospitals.
Until the early 1990s, Sackey pointed out, clinical trials were based on research that mainly included men, as investigators were concerned that women could become pregnant, which would affect the results. This has led to some unfortunate consequences, such as indications and dosages for drugs that cause more side effects in women due to biological differences. “We’ve made some progress in including women, but we have a long way to go in including people of different ethnic and racial groups,” she said.
A new mural outside Guadalupe Centers Middle School in Kansas City, Missouri, advocates for increasing diversity in clinical trials. Kim Jones, 51-year-old African American breast cancer survivor, is second on the left.
Artwork by Vania Soto. Photo by Megan Peters.
Among racial and ethnic minorities, distrust of clinical trials is deeply rooted in a history of medical racism. A prime example is the Tuskegee Study, a syphilis research experiment that started in 1932 and spanned 40 years, involving hundreds of Black men with low incomes without their informed consent. They were lured with inducements of free meals, health care and burial stipends to participate in the study undertaken by the U.S. Public Health Service and the Tuskegee Institute in Alabama.
By 1947, scientists had figured out that they could provide penicillin to help patients with syphilis, but leaders of the Tuskegee research failed to offer penicillin to their participants throughout the rest of the study, which lasted until 1972.
Opeyemi Olabisi, an assistant professor of medicine at Duke University Medical Center, aims to increase the participation of African Americans in clinical research. As a nephrologist and researcher, he is the principal investigator of a clinical trial focusing on the high rate of kidney disease fueled by two genetic variants of the apolipoprotein L1 (APOL1) gene in people of recent African ancestry. Individuals of this background are four times more likely to develop kidney failure than European Americans, with these two variants accounting for much of the excess risk, Olabisi noted.
The trial is part of an initiative, CARE and JUSTICE for APOL1-Mediated Kidney Disease, through which Olabisi hopes to diversify study participants. “We seek ways to engage African Americans by meeting folks in the community, providing accessible information and addressing structural hindrances that prevent them from participating in clinical trials,” Olabisi said. The researchers go to churches and community organizations to enroll people who do not visit academic medical centers, which typically lead clinical trials. Since last fall, the initiative has screened more than 250 African Americans in North Carolina for the genetic variants, he said.
Other key efforts are underway. “Breaking down barriers, including addressing access, awareness, discrimination and racism, and workforce diversity, are pivotal to increasing clinical trial participation in racial and ethnic minority groups,” said Joshua J. Joseph, assistant professor of medicine at the Ohio State University Wexner Medical Center. Along with the university’s colleges of medicine and nursing, researchers at the medical center partnered with the African American Male Wellness Agency, Genentech and Pfizer to host webinars soliciting solutions from almost 450 community members, civic representatives, health care providers, government organizations and biotechnology professionals in 25 states and five countries.
Their findings, published in February in the journal PLOS One, suggested that including incentives or compensation as part of the research budget at the institutional level may help resolve some issues that hinder racial and ethnic minorities from participating in clinical trials. Compared to other groups, more Blacks and Hispanics have jobs in service, production and transportation, the authors note. It can be difficult to get paid leave in these sectors, so employees often can’t join clinical trials during regular business hours. If more leaders of trials offer money for participating, that could make a difference.
Obstacles include geographic access, language and other communications issues, limited awareness of research options, cost and lack of trust.
Christopher Corsico, senior vice president of development at GSK, formerly GlaxoSmithKline, said the pharmaceutical company conducted a 17-year retrospective study on U.S. clinical trial diversity. “We are using epidemiology and patients most impacted by a particular disease as the foundation for all our enrollment guidance, including study diversity plans,” Corsico said. “We are also sharing our results and ideas across the pharmaceutical industry.”
Judy Sewards, vice president and head of clinical trial experience at Pfizer’s headquarters in New York, said the company has committed to achieving racially and ethnically diverse participation at or above U.S. census or disease prevalence levels (as appropriate) in all trials. “Today, barriers to clinical trial participation persist,” Sewards said. She noted that these obstacles include geographic access, language and other communications issues, limited awareness of research options, cost and lack of trust. “Addressing these challenges takes a village. All stakeholders must come together and work collaboratively to increase diversity in clinical trials.”
It takes a village indeed. Hope Krebill, executive director of the Masonic Cancer Alliance, the outreach network of the University of Kansas Cancer Center in Kansas City, which commissioned the mural, understood that well. So her team actively worked with their metaphorical “village.” “We partnered with the community to understand their concerns, knowledge and attitudes toward clinical trials and research,” said Krebill. “With that information, we created a clinical trials video and a social media campaign, and finally, the mural to encourage people to consider clinical trials as an option for care.”
Besides its encouraging imagery, the mural will also be informational. It will include a QR code that viewers can scan to find relevant clinical trials in their location, said Vania Soto, a Mexican artist who completed the rendition in late February. “I’m so honored to paint people that are survivors and are living proof that clinical trials worked for them,” she said.
Jones, the cancer survivor depicted in the mural, hopes the image will prompt people to feel more open to partaking in clinical trials. “Hopefully, it will encourage people to inquire about what they can do — how they can participate,” she said.
Two years, six million deaths and still counting, scientists are searching for answers to prevent another COVID-19-like tragedy from ever occurring again. And it’s a gargantuan task.
Our disturbed ecosystems are creating more favorable conditions for the spread of infectious disease. Global warming, deforestation, rising sea levels and flooding have contributed to a rise in mosquito-borne infections and longer tick seasons. Disease-carrying animals are in closer range to other species and humans as they migrate to escape the heat. Bats are thought to have carried the SARS-CoV-2 virus to Wuhan, either directly or through another host animal, but thousands of novel viruses are lurking within other wild creatures.
Understanding how climate change contributes to the spread of disease is critical in predicting and thwarting future calamities. But the problem is that predictive models aren’t yet where they need to be for forecasting with certainty beyond the next year, as we could for weather, for instance.
The association between climate and infectious disease is poorly understood, says Irina Tezaur, a computational scientist at Sandia National Laboratories. “Correlations have been observed but it’s not known if these correlations translate to causal relationships.”
To make accurate longer-term predictions, scientists need more empirical data, multiple datasets specific to locations and diseases, and the ability to calculate risks that depend on unpredictable nature and human behavior. Another obstacle is that climate scientists and epidemiologists are not collaborating effectively, so some researchers are calling for a multidisciplinary approach, a new field called Outbreak Science.
Climate scientists are far ahead of epidemiologists in gathering essential data.
Earth System Models—combining the interactions of atmosphere, ocean, land, ice and biosphere—have been in place for two decades to monitor the effects of global climate change. These models must be combined with epidemiological and human model research, areas that are easily skewed by unpredictable elements, from extreme weather events to public environmental policy shifts.
“There is never just one driver in tracking the impact of climate on infectious disease,” says Joacim Rocklöv, a professor at the Heidelberg Institute of Global Health & Heidelberg Interdisciplinary Centre for Scientific Computing in Germany. Rocklöv has studied how climate affects vector-borne diseases—those transmitted to humans by mosquitoes, ticks or fleas. “You need to disentangle the variables to find out how much difference climate makes to the outcome and how much is other factors.” Determinants from deforestation to population density to lack of healthcare access influence the spread of disease.
Even though climate change is not the primary driver of infectious disease today, it poses a major threat to public health in the future, says Rocklöv.
The promise of predictive modeling
“Models are simplifications of a system we’re trying to understand,” says Jeremy Hess, who directs the Center for Health and the Global Environment at University of Washington in Seattle. “They’re tools for learning that improve over time with new observations.”
Accurate predictions depend on high-quality, long-term observational data but models must start with assumptions. “It’s not possible to apply an evidence-based approach for the next 40 years,” says Rocklöv. “Using models to experiment and learn is the only way to figure out what climate means for infectious disease. We collect data and analyze what already happened. What we do today will not make a difference for several decades.”
To improve accuracy, scientists develop and draw on thousands of models to cover as many scenarios as possible. One model may capture the dynamics of disease transmission while another focuses on immunity data or ocean influences or seasonal components of a virus. Further, each model needs to be disease-specific and often location-specific to be useful.
“All models have biases so it’s important to use a suite of models,” Tezaur stresses.
The modeling scientist chooses the drivers of change and parameters based on the question explored. The drivers could be increased precipitation, poverty or mosquito prevalence, for instance. Later, the scientist may need to isolate the effect of one driver so that will require another model.
There have been some related successes, such as the latest models for mosquito-borne diseases like Dengue, Zika and malaria as well as those for flu and tick-borne diseases, says Hess.
Rocklöv was part of a research team that used test data from 2018 and 2019 to identify regions at risk for West Nile virus outbreaks. Using AI, scientists were able to forecast outbreaks of the virus for the entire transmission season in Europe. “In the end, we want data-driven models; that’s what AI can accomplish,” says Rocklöv. Other researchers are making an important headway in creating a framework to predict novel host–parasite interactions.
Modeling studies can run months, years or decades. “The scientist is working with layers of data. The challenge is how to transform and couple different models together on a planetary scale,” says Jeanne Fair, a scientist at Los Alamos National Laboratory, Biosecurity and Public Health, in New Mexico.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts a tall spatial and temporal resolutions.
And it’s a constantly changing picture. A modeling study in an April 2022 issue of Nature predicted that thousands of animals will migrate to cooler locales as temperatures rise. This means that various species will come into closer contact with people and other mammals for the first time. This is likely to increase the risk of emerging infectious disease transmitted from animals to humans, especially in Africa and Asia.
Other things can happen too. Global warming could precipitate viral mutations or new infectious diseases that don’t respond to antimicrobial treatments. Insecticide-resistant mosquitoes could evolve. Weather-related food insecurity could increase malnutrition and weaken people’s immune systems. And the impact of an epidemic will be worse if it co-occurs during a heatwave, flood, or drought, says Hess.
The devil is in the climate variables
Solid predictions about the future of climate and disease are not possible with so many uncertainties. Difficult-to-measure drivers must be added to the empirical model mix, such as land and water use, ecosystem changes or the public’s willingness to accept a vaccine or practice social distancing. Nor is there any precedent for calculating the effect of climate changes that are accelerating at a faster speed than ever before.
The most critical climate variables thought to influence disease spread are temperature, precipitation, humidity, sunshine and wind, according to Tezaur’s research. And then there are variables within variables. Influenza scientists, for example, found that warm winters were predictors of the most severe flu seasons in the following year.
The human factor may be the most challenging determinant. To what degree will people curtail greenhouse gas emissions, if at all? The swift development of effective COVID-19 vaccines was a game-changer, but will scientists be able to repeat it during the next pandemic? Plus, no model could predict the amount of internet-fueled COVID-19 misinformation, Fair noted. To tackle this issue, infectious disease teams are looking to include more sociologists and political scientists in their modeling.
Addressing the gaps
Currently, researchers are focusing on the near future, predicting for next year, says Fair. “When it comes to long-term, that’s where we have the most work to do.” While scientists cannot foresee how political influences and misinformation spread will affect models, they are positioned to make headway in collecting and assessing new data streams that have never been merged.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts at all spatial and temporal resolutions, Fair and her co-authors stated in their recent study. For example real-time data on mosquito prevalence and diversity in various settings and times is limited or non-existent. Fair also would like to see standards set in mosquito data collection in every country. “Standardizing across the US would be a huge accomplishment,” she says.
Understanding how climate change contributes to the spread of disease is critical for thwarting future calamities.
Jeanne Fair
Hess points to a dearth of data in local and regional datasets about how extreme weather events play out in different geographic locations. His research indicates that Africa and the Middle East experienced substantial climate shifts, for example, but are unrepresented in the evidentiary database, which limits conclusions. “A model for dengue may be good in Singapore but not necessarily in Port-au-Prince,” Hess explains. And, he adds, scientists need a way of evaluating models for how effective they are.
The hope, Rocklöv says, is that in the future we will have data-driven models rather than theoretical ones. In turn, sharper statistical analyses can inform resource allocation and intervention strategies to prevent outbreaks.
Most of all, experts emphasize that epidemiologists and climate scientists must stop working in silos. If scientists can successfully merge epidemiological data with climatic, biological, environmental, ecological and demographic data, they will make better predictions about complex disease patterns. Modeling “cross talk” and among disciplines and, in some cases, refusal to release data between countries is hindering discovery and advances.
It’s time for bold transdisciplinary action, says Hess. He points to initiatives that need funding in disease surveillance and control; developing and testing interventions; community education and social mobilization; decision-support analytics to predict when and where infections will emerge; advanced methodologies to improve modeling; training scientists in data management and integrated surveillance.
Establishing a new field of Outbreak Science to coordinate collaboration would accelerate progress. Investment in decision-support modeling tools for public health teams, policy makers, and other long-term planning stakeholders is imperative, too. We need to invest in programs that encourage people from climate modeling and epidemiology to work together in a cohesive fashion, says Tezaur. Joining forces is the only way to solve the formidable challenges ahead.
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.
Scientists use AI to predict how hospital stays will go
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
Here are the promising studies covered in this week's Friday Five:
- The problem with bedtime munching
- Scientists use AI to predict how stays in hospitals will go
- How to armor the shields of our livers against cancer
- One big step to save the world: turn one kind of plastic into another
- The perfect recipe for tiny brains
And an honorable mention this week: Bigger is better when it comes to super neurons in super agers