It’s a wonderful feeling when you discover clothing that fits just right. Whether it’s a well-fitting shirt, the perfect pair of shoes, or a nicely tailored dress, it feels comfortable, looks good, and seems custom-made for you. Imagine a world, though, where all shirts were the same size and all shoes had the same design, without differences in the cut of men’s and women’s clothing. Getting dressed would be awkward, and garments would be uncomfortable, illustrating that one size truly does not fit all. This is somewhat the current state of medicine.
Despite various biological differences among people based on gender, race, age, and personal history, the standard medical approach is to offer similar treatments to individuals presenting identical symptoms. Naturally, if treatments—from medications to diagnostic testing—were tailored to align with the diverse range of human bodies rather than a generic model, they could be significantly more effective. In an episode of The Conversation Weekly podcast, we discuss with three researchers their efforts to make medicine more personalized to individual needs. The process begins with ensuring that participants in clinical trials reflect the actual patient population the drug aims to benefit. Looking forward, as discussed in this episode, precision medicine could eventually enable personalized healthcare that matches one’s unique biology, much like a tailored piece of clothing.
In 1977, the U.S. Food and Drug Administration issued policy guidelines that explicitly prohibited “women of childbearing age” from participating in clinical trials for new drugs. This action, aimed at preventing birth defects, resulted in new drugs being released with minimal information on their effects on women. Similarly, systemic biases have led to a chronic underrepresentation of people of color in clinical trials. Historically, much medical research has been conducted on healthy, young, and middle-aged men of European descent.
According to Jennifer Miller, a Yale University bioethicist, this poses a risk because if you are not included in the trial, it raises questions about whether the drug’s safety and efficacy data are applicable to patients like you. Recently, researchers, including Julia Liu, a professor of medicine at Morehouse School of Medicine, are exploring ways to increase diversity among clinical trial participants. Liu notes that part of the challenge arises from the misconception that Black people are generally reluctant to participate in medical research, a belief stemming from past abuses by the U.S. medical system, like the Tuskegee Study.
However, when Liu conducted her own trials on a new prostate cancer test at a predominantly African American hospital, she encountered a different scenario. According to Liu, almost everyone she approached was willing to participate, with half of the eligible patients agreeing to join the study. Black patients were as keen on participating as white patients. Liu attributes the lack of diversity in clinical trials to the fact they are primarily held at large research hospitals located in wealthier, predominantly white areas, rather than in hospitals serving diverse communities.
Miller’s research indicates that only 4% of recent trials have used a population representative of broader demographics, but she remains hopeful. Women now have better representation in trials, and for racial equality in clinical trials, the 4% shows that achieving balance is possible. Efforts by Liu and Miller resemble how companies create shirts in different sizes to accommodate various body types. Once this work is underway, healthcare providers can better select drugs that are likely to be more effective and carry fewer risks for diverse patients based on their individual demographics. Better representation is a crucial step, but those fortunate enough to experience custom clothing know that nothing compares to its perfect fit. This concept underpins precision medicine.
Keith Yamamoto, who heads the precision medicine center at the University of California, San Francisco, envisions a future where it’s possible to understand health and disease so well that individual advice, not just general guidance for similar people, could be given. This approach would integrate basic biology, an individual’s genetics, personal history, and extensive medical research knowledge—making precision medicine an exercise in information and computation. This requires robust data, which is often missing from many clinical trials. As Yamamoto puts it, precision medicine’s success hinges on tackling these issues decisively.