This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American
A systemic business problem is impeding the development of many life-saving treatments: the vicious cycle of ever-diminishing returns on drug-discovery investment. Since 1950 the cost of developing a new drug has doubled every nine years. In 1950 approximately 30 drugs were developed for every $1 billion spent on research and development. Today we get about one third of a drug for the same price—or put another way, it costs close to $3 billion to bring a new medicine to market.
This slowing pace and rising cost of R&D has recently been coined Eroom's law, so named because it's the opposite to Moore's law from microelectronics, whereby computing power doubles and cost is halved roughly every 18 months. There are many explanations given for why drug discovery has followed Eroom's law, from cautious regulators to increasing overall R&D costs. But one of the biggest areas holding back progress is inefficiency in the preclinical, animal testing phase of the drug-discovery process. Only one in 10 drugs that enter human clinical trials reach the market after preclinical success.
There also can be a mirror result, where a drug might have been successful in humans, yet because it fails in preclinical animal testing, it never makes it to human trials. The bottom-line consequences of this failure were demonstrated dramatically recently when Biogen's Alzheimer's drug, in development for years at a cost of multiple billions of dollars, failed at Phase III trials. The company lost $18 billion, representing 30 percent of its market value, in a single day.
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Part of the reason for this failure is that animals or cells in simple petri dishes aren't good predictors of how a drug will perform in humans. Advances in technology are making new testing models possible, from 3-D printing of tissues to sophisticated, broader studies that use massive amounts of data from clinical trials or other sources to draw conclusions based on patterns that the data show. There are drawbacks, however, to both approaches. First, 3-D printing subjects the cells to a printing process, which may alter the cells' behavior, and as cells are printed one at a time, this approach is difficult to scale. Data studies, on the other hand, are not an actual physical model and require massive amounts of information, which may not be available when it comes to experimental drugs.
To understand a drug's true efficacy, it is critical to test the interactions involving not only the biology but also the fluid and biophysical environment surrounding the biology. A physical model called a human organ system uses human tissue samples to recreate the complex interactions cells have in a living, breathing organism, at scale. This system has the potential to not only increase significantly the success rate at the clinical stage but also has the potential to reduce or eliminate animal testing altogether.
This technology works by making human tissue samples on biocompatible plastic with microscopic structures, embedded sensors, pumps and controllers. A series of fine needle-tubes align with human tissue samples on the chip, and pumps on top of the chip bathe the cells in fluids, mimicking the natural environment of cells within the body. The result is a proxy for 96 independent human organs in a highly controlled environment. Furthermore, the integrated sensors can provide direct, lifetime monitoring of cell cultures to see how and why changes occur as opposed to current techniques that look at endpoints only.
Using multiple, clinically relevant measures of tissue function has the potential to accelerate drug discovery by enabling human tissue testing before clinical trials or even animal studies begin. Even more important, testing on human tissue rather than on humans opens up entirely new testing opportunities we can't even contemplate today. These could be new possibilities in terms of scale—such as testing hundreds of thousands of copies of a human organ system—or in terms of testing subpopulations with age, ethnic or gender diversity that would be either too expensive or ethically unacceptable to test live. For example, it is unsafe and unethical to test a drug on pregnant women or an 18-month-old child. We can, however, test the tissue from someone who is pregnant or 18 months old without causing harm, thereby getting a much more accurate prediction of a drug's safety and efficacy in those populations.
Testing human organ systems enables the collection of better and more types of data, advancing research into diseases where effective treatments have long been elusive. For example, chronic kidney disease is a growing health burden, affecting one in 10 people worldwide. The disease's progression can lead to kidney failure, and the need to replace kidney function through dialysis. But what if we could learn more about why kidney functions were breaking down so that we could develop a drug that could slow or stop the process? Finding a cure for kidney disease will require studying many drug and environmental conditions on a wide range of populations. Human organ systems enable us to do just that, making it possible to one day proactively manage kidney disease in much the same way we manage heart disease now.
Another example where we're seeing human organ systems research make an impact is in its ability to measure real-time barrier formation, and changes to transport across that barrier. This is particularly important in treating intestinal disorders, such as inflammatory bowel disease. Developing an effective treatment for this painful disorder requires deeper understanding into how the barrier between the bloodstream and gut starts to break down, and whether there are types of bacteria, for example, that cause this breakdown or inflame the barrier. Human organ systems provide a window into understanding this condition that wasn't possible before.
Although in its early days, this technology holds great promise from a business standpoint as well. If the platform is able to make clinical trials even 25 percent more successful, cost savings could run to more than $500 million per approved drug. As a result, several pharma companies, including Pfizer, are using human organ systems, and researchers and start-ups are investigating a range of approaches, making this space an exciting one to watch in the years to come.
Innovations such as human organ systems are one fundamental way that pharma companies can break the cycle of diminishing returns on R&D. Although Eroom's law—the slowing pace and rising cost in R&D—won't be reversed overnight, we don't have to live with it. Unlike Moore's law in microelectronics, there are no laws of physics limiting our advances.