There is a greater push in the world of medicine to provide personalized care, developing treatments based on the specific needs of one patient at a time.
While personalized care can significantly improve patient outcomes, it provides its own set of challenges. How can a drug manufacturer standardize production? How can clinical researchers ensure the treatment is safe across all demographics? These challenges are even more apparent in early-stage trials which are already comparably smaller than their late-stage counterparts.
Here we examine the changing face of personalized medicine and how the clinical trial industry is evolving around it.
Personalized medicine takes into consideration the unique DNA and genetics of patients in the treatment process. Technology — specifically data analysis and artificial intelligence — allow healthcare professionals to better evaluate patient genetic makeup in order to create targeted treatments.
“Advancements in genomics, proteomics, data analysis and other fields – both medical and technical – are gradually facilitating the development of laser-focused drugs, as well as the ability to predict people’s personal risk factors for particular diseases and how individual responses to various treatments might differ,” writes Chris Lo at Pharmaceutical Technology.
As more researchers turn to personalized medicine, its uses expand. You can find personalized medicine in even the most widespread diseases.
“There is perhaps no more poignant example than the response to the COVID-19 pandemic,” write Francis Collins and Joshua Denny from the National Institutes of Health. “Genomics and molecular technologies were key in identifying the etiologic agent, developing diagnostics and treatments, and creating vaccine candidates.”
The goal of personalized medicine is to increase positive patient outcomes while reducing risk. Just a few negative responses can shut down a trial and impact the lives of patients forever.
Personalized medicine doesn’t refer to only one type of clinical trial. It represents a whole new approach to how researchers create treatments for patients.
Some researchers are using personalized medicine to embrace adaptive clinical trials — trials that change with patient response. Instead of treating a medication with a “pass-fail” criteria (it either worked for the patient or didn’t), adaptive trials switch low-performing treatments and try other options.
Precision medicine trials use a similar approach. “[The precision medicine clinical trial] is different than standard clinical trials in that it has an adaptive design, meaning if a drug is not working, it can be pulled from the trial and another treatment can take its place,” says Aaron Miller, medical oncologist at the UC San Diego Health System. “And if a drug is working, it can move more quickly through the trial and to the FDA for potential approval.”
This adaptive design makes clinical trials more personalized and patient-focused.
However, while personalized medicine can help patients from all walks of life, personalized clinical trials aren’t easy to execute. In the future, researchers may need to develop better collaboration tools and data-sharing with their peers in order to create effective data sets with quality representation.
“Novel trial concepts offer numerous advantages but are complex in design and execution,” write Allen Li and Raymond Bergan, hematology/oncology fellow at the Knight Cancer Institute and deputy director of Buffett Cancer Center at University of Nebraska Medical Center, respectively. “A robust infrastructure is essential. Logistical challenges, including the potential need to work with multiple industry partners and potential competition among the substudies, need to be considered.”
One of the best ways to look into personalized medicine and how its development affects clinical trials is the use of personalized vaccines. With personalized vaccines, researchers take the immune cells of patients and develop an injection based on their specific genomes. Every patient has unique markers and treatment needs, so pulling something from their body seems to be the most effective way to fight offending tumors.
“As soon as we find the tumor, we could start vaccinating [the patient],” says Thomas Marron, director of the early phase trials unit at Tisch Cancer Institute. “That would, potentially, significantly increase the response rates to these immune therapies, because you would give patients that much more potential to have a T-cell response that’s able to recognize their cancer and kill it.”
However, there are drawbacks to this treatment option. Instead of developing one vaccine and testing it on smaller groups in early-phase trials (and then eventually on larger groups for late-phase testing), researchers need to formulate a vaccine for each participant. This takes time.
“The overall timeline for good manufacturing practice (GMP)–compliant on-demand production, from the start of processing of the patient’s sample for mutation discovery to vaccine release for administration, was about 3 to 4 months,” write BioNTech founders Ugur Sahin and Ozlem Tureci. “Patients were treated with other standard or experimental compounds until their personal vaccine had been produced.”
Sahin and Tureci aren’t the only ones concerned about the timeframe required to create personalized vaccines.
“From a manufacturing, clinical trial design perspective, it just takes, at least in the initial stage of these studies..., up to 15 weeks to make such a vaccine,” says Patrick Ott, clinical director of the Melanoma Disease Center at Dana-Farber Cancer Institute.
At the end of the day, researchers need to rely on vaccine production optimization to bring personalized vaccines to market. The company or research firm that figures out the best way to connect patients with their own personalized vaccines will have the most success promoting their treatments.
“Which of the more than two dozen personalized cancer vaccine approaches currently in early-stage trials will ultimately succeed depends not only on determining the numbers and types of neoantigens needed to best improve patient outcomes, but on which vaccine platforms are the most scalable, cost-effective, and quick to produce,” write Jasreet Hundal and Elaine R. Mardis, a personalized cancer vaccine clinical trials manager at the Washington University School of Medicine, and co-executive director of the Institute for Genomic Medicine at Nationwide Children's Hospital, respectively.
Despite the advances in personalized medicine, some doctors and researchers are calling for better diversity and updated best practices to ensure everyone has the same access to the targeted medications and treatments.
“If we don’t get ahead of health disparities at the same time we’re developing these amazing precision technologies, we won’t have accomplished what we set out to do, says Hala Borno, medical oncologist and assistant professor at UCSF Medical Center.
While some people might immediately receive a form of treatment that is developed specifically for them, other patients will have to use whatever off-the-shelf medication is available.
“We can do a lot of artificial intelligence work but we’re not including data on all populations who are impacted by cancer,” says Edith Perez, chief medical officer at Bolt Biotherapeutics and director of the breast cancer translational genomics program at Mayo Clinic. She points to the COVID-19 pandemic as an example of the need for diversity and inclusion in clinical trials.
“Customized T-cell receptor therapy may be more suitable to certain racial and ethnic demographics because we have HLA-B7, but you’re not going to find that in Korea – that’s a very real difference,” says Dr. Jeff Sharman, medical director of hematology research at The US Oncology Network. “It’s not always clear what is and isn’t generalizable, so there’s a strong interest in getting a more robust population of African-Americans or Latinos into those clinical trials so there’s more generalizable data.”
Sharman is referring to a human leukocyte antigen type more common in people of Northern and Western European descent.
Personalized medicine has the potential to help small groups of people with unique diseases as well as large groups from the general population. By creating treatments that respond directly to patient genomes, there’s a greater chance of successful treatment. In the meantime, clinical trials must be diverse enough to include all patients.