A quest for more effective drugs

Harvard effort brings disparate fields together

Galit Lahav worked in her laboratory at Harvard Medical School. John Tlumacki/Globe Staff/Globe Staff

Harvard Medical School plans to unveil an initiative today that will bring the tools and techniques of physics, math, computer science, and biology together to build a quantitative understanding of how drugs work in the body and how to better design therapies.

The effort, called systems pharmacology, will ultimately bring in 10 new faculty through a multimillion-dollar investment from the university and is aimed at addressing a major problem in medicine.

Over the past generation, there has been tremendous growth in the understanding of fundamental biology, spurred largely by insights into the genome and advances in molecular biology. But a boom in new drugs that tackle unmet health needs has not followed - in part because even as research has revealed new drug targets, the research does not always reflect the complexity of the network of other cells, tissues, and organs at work in the body.

“If you’re trying to halt traffic in a city, you could say you have this one major street and you could block the traffic on this major street,’’ said Marc Kirschner, chairman of the systems biology department and a leader of the new initiative. “Maybe the traffic might not move as fast, but it would find a way.

“It might be you’d be better off picking three or five major thoroughfares and blocking them each 80 percent. But for you to make that prediction, you really first need a map.’’

In order to construct such maps, Harvard researchers will use a variety of tools and models to understand the complicated interactions that take place when drugs are added to cancer cells or an infection.

To start, the researchers - about a dozen faculty have shifted their research into the new area - are pursuing a broad set of questions, including investigating how existing drugs work. Insights from this research should help guide the design of new medications and pinpoint why drugs fail.

“We don’t understand how most drugs work at a molecular level; therefore we don’t understand who to give them to and we don’t really understand how to make them better,’’ said Peter Sorger, a professor of systems biology.

Projects underway are exploring questions ranging from how cancer cells react to drugs to how combinations of antibiotics work to fight bacteria.

The approach is part of a larger rethinking of how new tools can be used to understand drugs. Two workshops have been held at the National Institutes of Health to bring together people from academia, industry, and government to discuss the emerging field.

“Clearly, if we’re going to do translation based upon drugs we need to understand everything we can about how they interact with cells,’’ Dr. Francis S. Collins, director of the NIH, said during a recent visit to Boston when asked about the new discipline.

Dr. Mark Fishman, president of the Novartis Institutes for BioMedical Research, headquartered in Cambridge, said the company has begun a significant effort aimed at elucidating pathways - the complete biological circuits that are important in disease, in contrast to the more traditional approach of defining the function of each of the 24,000 human genes.

Novartis is interested in understanding whole networks of interactions, he said, with the goal of determining what parts of the circuit are most essential. He compared it to the financial market, where some banks can fail without a significant impact, while others may bring down the whole system.

Novartis is also collaborating with researchers at Harvard, including Galit Lahav, an associate professor of systems biology. Lahav is trying to understand why chemotherapy drugs are so fickle - sometimes working well to kill cancer cells, and sometimes not. For years, it has been known that people with cancer in the same tissue may respond very differently to a drug, but Lahav’s research has shown that even genetically identical cells will not all respond in the same way.

“One of the ultimate goals in cancer treatment is to selectively kill the cancer cells while maintaining the healthy cells,’’ Lahav said. She is studying a pathway that normally suppresses tumors and is mutated in many cancers to see what factors cause seemingly identical cancer cells, when faced with a drug or radiation, to behave differently.

“Biology is complicated. When you add a drug to a cell, there’s a lot of stuff that’s being changed,’’ Lahav said. “Our pure intuition is limited in understanding all those things, and we need help from the computational tools and mathematical models in order to understand these drug actions in cells.’’

Roy Kishony, a physicist and professor of systems biology, thinks that the emerging science will provide a more rational basis for combination therapies increasingly important in fighting infectious disease and cancer.

Kishony has been looking at how combinations of antibiotics work, producing surprising results. He’s found, for example, that two antibiotics sometimes work less well than one of them would work alone, because one drug is suppressing another.

Researchers at other institutions are working on similar approaches. At Mount Sinai School of Medicine, Ravi Iyengar, for example, is using statistical tools to study the genetic data of patients with glioblastoma, a brain cancer. The approach has highlighted two genes that would not traditionally have been looked at as potential drug targets.

Dr. William Chin, executive dean for research at Harvard Medical School, said the systems pharmacology initiative would be the first pillar in a plan to translate basic research into findings that could benefit patients.

“This is not just a problem for Harvard Medical School; this is not just a problem for pharmaceutical companies. In many ways,’’ Chin said, “the lack of new drugs is a problem for society.’’