Monoclonal antibodies, which are engineered to hone in on very specific biological targets, have taken off therapeutically in recent years: several are now approved for treating cancers and autoimmune diseases, and nearly 200 are in clinical trials. But one of the challenges of monoclonal-antibody therapy is the fact that some people respond very well to the drugs while others respond only moderately or not at all.
A startup called PIKAMAB, based in Menlo Park, CA, believes that it can make monoclonal antibodies more effective by grouping patients together based on their genotype and offering a customized antibody developed for that genotype. The company hopes that this “stratified” approach to drug development and treatment will help drug companies achieve better results.
Monoclonal antibodies bind only to specific target molecules, giving them a precision that many other drugs lack. These Y-shaped molecules, which are naturally produced by immune cells called B cells, have a nearly identical base but arms that can vary depending on their intended target. The arms bind precisely to the target while the base of the Y provides an anchor for circulating immune cells to attach to.
Monoclonal antibodies were first identified as potential cancer treatments three decades ago, as the molecules could be engineered to bind to cancer cells and provoke an immune response against them. They have also proved useful for treating autoimmune disease and are under investigation as a treatment for many other conditions.
But scientists have found that patients respond differently to these drugs, largely because the antibodies are not able to bind to the immune cells of all patients equally well. Studies have found that the process, called antibody-dependent cell-mediated cytotoxicity (ADCC), plays a major role in how well several monoclonal-antibody drugs work. How an immune cell attaches to an antibody depends on one of two protein receptors at the cell’s surface. People have natural genetic variations in these receptors: certain variations prevent immune cells from binding to antibodies, and these patients respond poorly to these antibody therapies.
Vijay Ramakrishnan, founder and CEO of PIKAMAB, believes that monoclonal-antibody therapies could be improved by taking into account the genetic background of each patient. “A one-size-fits-all antibody drug in this case doesn’t work,” he says.
PIKAMAB’s approach is to first sort patients depending on whether they are expected to respond to a treatment or not. The company is marketing a “theragnostic” test that separates patients into one of nine groups in a matrix according to their receptor type and an analysis of their immune cells. At one end of the matrix are patients likely to respond well to an existing drug; at the other end are those who are likely to respond poorly. Ramakrishnan says that this test alone can benefit treatment, as it could help a clinician decide whether to begin a monoclonal therapy right away in an excellent responder or eschew the drug in favor of other options in a poor responder.
The next step is to develop a portfolio of antibodies that are customized for each group of patients within the matrix. The drugs would be altered slightly so that they can bind specifically to the receptors in patients of each genotype. Ramakrishnan says that the portfolio could consist of a minimum of four and a maximum of nine drugs (one for each group) to achieve a high response rate in each group.
The approach is different from “personalized” medicine that is tailored to an individual. Instead, Ramakrishnan says, this “stratified” approach offers some personalization but in a more manageable way. He believes that a stratified approach to monoclonal-antibody therapies can offer advantages to pharmaceutical companies. If they begin stratifying patients in clinical trials, they could achieve better results and help justify the treatments to regulatory agencies and insurers, he says. Companies could also put a higher premium on drugs if those drugs came with theragnostic tests.
PIKAMAB hopes to work with pharmaceutical companies to create commercial theragnostic tests and stratified therapies involving drugs that are already on the market or in development. Together, they also plan to develop their own monoclonal antibodies.
“I think it’s useful to have a predictive test that can accurately describe whether a particular individual has a receptor that will make ADCC easier or harder to exploit as an anti-tumor mechanism,” says Louis Weiner, a cancer immunologist at Georgetown University who has no ties to PIKAMAB. Weiner is, however, skeptical that customized antibodies are necessary to improve monoclonal-antibody therapies. He sees more potential in “high affinity” monoclonal antibodies that bind tightly to immune cells regardless of a patient’s genotype.
Ramakrishnan argues that such drugs may not completely optimize the responses of all genotypes, and that there is room for further improvement with customized drugs. He points out that when monoclonal antibodies are used to treat cancer, it is usually in combination with radiation or other treatment. By optimizing the drugs, he says, it may be possible that certain patients could receive them as stand-alone therapies, thereby reducing the side effects and cost of treatment.
10 Breakthrough Technologies 2024
Every year, we look for promising technologies poised to have a real impact on the world. Here are the advances that we think matter most right now.
Scientists are finding signals of long covid in blood. They could lead to new treatments.
Faults in a certain part of the immune system might be at the root of some long covid cases, new research suggests.
AI for everything: 10 Breakthrough Technologies 2024
Generative AI tools like ChatGPT reached mass adoption in record time, and reset the course of an entire industry.
What’s next for AI in 2024
Our writers look at the four hot trends to watch out for this year
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.