Feeding the Pipeline
Pfizer Inc. has never looked more like a winner. The New York-based drugmaker managed to reap $2.74 billion in first-quarter earnings excluding one-time items, up from $2.4 billion a year earlier. And it just completed a $58 billion merger with Pharmacia Corp. Yet in its research facilities, Pfizer is struggling with one of the industry's most daunting challenges. Somehow, it must pinpoint the most promising targets for drugs -- meaning enzymes or other proteins that can be blocked to halt disease -- out of thousands of possibilities emerging from sequencing the human genome.
Meeting the challenge isn't critical for this year or next. Pfizer's cost savings from the merger guarantee earnings momentum, with or without a raft of new blockbusters. But by 2006, the company will need a strong portfolio of novel drugs to produce double-digit growth on its mammoth revenue base, expected to top $48 billion this year. For that, the company is counting on its head of research and development, Peter B. Corr, a longtime academic and former research chief at Warner-Lambert Co., which Pfizer purchased in 2000.
With an estimated $7.1 billion in R&D funds at his disposal, Corr's game plan includes examining drug targets whose role in diseases is already well established, and then choosing new targets that closely resemble these. Not surprisingly, Corr is taking aim at a family of 21 enzymes Pfizer already understands well, because one of them is blocked by the company's little blue blockbuster, Viagra.
Pfizer had sequenced the genes for the entire family of enzymes, and three years ago began testing a large number of compounds against 15 of them. The most promising of these drugs were tested at six Pfizer facilities around the world. Now, the labs are studying four compounds for efficacy against bone disease, psychosis, diabetes, and cardiovascular disease. "We used to do these things in sequence, and now we do this in parallel," says Corr, contemplating the extraordinary speed of the endeavor. "The cost savings of doing that are phenomenal."
Pfizer's adept mingling of gene-sequencing and protein analysis is just one of many strategies drugmakers are adopting to achieve an urgent, shared goal: boosting the output of their lagging R&D operations. Based on the number and quality of drugs these techniques have ushered into early-stage testing, most companies are optimistic. Their early successes suggest that the industry should be able to churn out many more effective, safe, and profitable drugs over the next 5 to 10 years.
For the moment, however, the drug industry is staring at a lot of hard work. Most easy-to-treat conditions, such as high blood pressure and elevated cholesterol, have already been addressed. What remain are vastly more complex conditions such as cancer, diabetes, and Alzheimer's disease. Coming up with wonder drugs for these ailments will require a much more detailed understanding of how all the organs of the body function together.
Indeed, the next few years will be rough. After a golden age in the 1990s, when drugmakers launched what seemed to be an endless stream of blockbusters, the industry has hit a disastrous dry spell. R&D pipelines are painfully thin, which has put the squeeze on company margins at some companies, sent stock prices dipping, and led to a series of megamergers. Short-term, Pfizer and the other giants will have trouble finding enough new drugs to generate the strong sales growth seen in years past.
What's more, patents are quickly expiring on existing blockbuster drugs, bringing competition from cheaper generic knockoffs. Market researcher Datamonitor estimates that from 2002 to 2008, U.S. patents on 39 major drugs will expire, including Merck's $5.6 billion cholesterol drug, Zocor, and Pfizer's $3.8 billion hypertension drug, Norvasc. Together, some $56 billion in sales will be put at risk. Meanwhile, productivity in drug labs is falling. The trade group Pharmaceutical Research & Manufacturers of America says the R&D spending it tracks for its big drug company members soared from $21 billion in 1998 to an estimated $32 billion in 2002. But new drug approvals fell from 35 in 1999 to 17 last year.
Against this backdrop, it's no surprise that many large drug companies have revamped their research organizations, often naming new chiefs or even bringing in outsiders -- all of whom are trying a variety of new tactics to reverse the slide. In the past three years alone, Pfizer anointed Corr; Merck & Co. recruited Peter S. Kim, a former hotshot biologist at Massachusetts Institute of Technology's Whitehead Institute; Abbott Laboratories named Dr. Jeffrey M. Leiden, onetime chief of cardiology at the University of Chicago; and Wyeth handed its research reins to Robert R. Ruffolo Jr., a former government researcher and SmithKline Beecham executive. "The traditional guard is retiring, and these [new] people come to the table with strong biotechnology and genomics expertise," says Denise DeMan-Williams, founder and CEO of the pharmaceutical recruiting firm Bench International.
Rapid advances in technology have given this New Guard of drug chiefs some potent weapons. They range from sophisticated computer modeling to illuminate complex disease processes to high-tech systems that reveal previously unknown structures of disease-causing proteins. And while there is no easy way to fill research pipelines, together these tools could have a huge impact. Joseph A. DiMasi, an economist at the Tufts Center for the Study of Drug Development, calculates that raising the success rate of drugs moving through clinical trials from 21.5% to 33% would cut as much as $242 million off the average development tab for a drug, estimated at about $800 million. Here is a rundown of strategies and scientific advances drugmakers have embraced to weed out bad drugs early on and improve the candidates that remain:
UNDERSTANDING A DISEASE. Long before the Genomics Revolution, companies managed to discover biological targets and attack them with drugs. The trouble is, complex diseases are rarely thwarted so simply. That's why researchers such as Didier A. Scherrer, a senior scientist at Foster City (Calif.)-based disease-simulation company Entelos Inc., are looking to understand the mysterious chain of events that causes ailments such as asthma and diabetes. Entelos employs a team of scientists who track everything that is known about the triggers and progression of various illnesses. The information is given to Entelos' dynamic engineers, who translate it into mathematical models -- creating the equivalent of a flight simulator for modeling diseases. Scherrer then helps Big Pharma companies test their hypotheses on virtual patients -- in silico, as they describe it -- before launching into expensive human trials.
Bayer turned to Entelos in 2001 with a common problem: Scientists at the company's research labs in Kyoto, Japan, had identified a gene they thought might play a role in asthma. But before they invested a lot of time on that gene, they wanted to answer a simple question. Even if they could find a drug to block the activity of that gene, would it have a big impact on the disease? Based on the sequence of the gene and where it was turned on in the body, Scherrer and his colleagues came up with six hypotheses on what the gene actually did. Then they ran the six theories through their asthma model.
Their findings: Of the six gene functions posited, only one indicated a point of intervention that would bring significant benefit to asthma patients. If the gene under study did in fact have that function, blocking its activity could produce a winning drug. Experiments yielded positive results, and Bayer has finished early testing compounds against that target, according to Kevin B. Bacon, Bayer's vice-president for respiratory disease research. "We saved a minimum of six months on the target-validation process," he says. Bayer and other companies are now relying on models of everything from single organs to whole diseases. "This is revolutionary," says Sheryl Torr-Brown, head of scientific development at Pfizer, which is investing heavily in such technology, even as it closes some labs in the wake of its merger. "You can change genes with the stroke of a keypad. We've never had the tools, like these, to look at the complexity of disease."
DESIGNING DRUG CANDIDATES. Even if scientists can unravel complex diseases and find the right targets for treatment, coming up with a safe compound that hits that target effectively is no easy feat. Just ask Jonathan Greer, head of structural biology at Abbott Laboratories in North Chicago, Ill. He describes how one team of researchers at the company spent years studying a single candidate for a cancer drug. It appeared to effectively block a protein that leads to uncontrollable cell growth. Unfortunately, it also broke down quickly in the patients' bodies, undermining its usefulness.
In the fall of 2001, Greer's team began using X-ray crystallography to see if they could get around the problem. In this technique, which caught on in drug labs in the 1990s, researchers first create a crystallized form of the protein they wish to block, then hit it with X-rays. The pattern of X-ray diffraction reveals the three-dimensional structure of the protein. In Abbott's case, scientists wanted to tweak the drug candidate so that it would fit in perfectly in the protein and block its action, but not get broken down as it passed through the body.
Because the structure of this small drug molecule remained elusive, Abbott's scientists took it to the federal government's nearby Argonne National Laboratory, home to one of the most powerful X-ray sources in the world. In just five days, Argonne created vivid pictures of precisely how the drug was binding to the target protein, providing clues as to what alterations might make it sturdier. A week later, they had three versions for testing. Combining elements of all three, they solved the problem while preserving the drug's apparent effectiveness. "We went from being a goat to being heroes in five days," Greer says. The drug is now being tested in animal studies.
SPOTTING SIDE EFFECTS. Peter S. Kim is the pharmaceutical industry equivalent of an FBI profiler. The head of Merck's $3 billion a year R&D operation knows that his worst enemy is a drug candidate that initially looks like a lifesaver but later proves toxic. So Kim is determined to spot what he calls criminal profiles of drug molecules. "If you did nothing to my success rate but tell me which compounds would be toxic, I'd be golden," he says.
To identify molecular outlaws, Merck has assembled an unlikely band of astrophysicists and mathematicians. Many of them worked previously for the Defense Dept. or academia developing pattern-recognition technology to track enemy submarines or to locate dark matter in the universe. Those science whizzes work for a company called Rosetta Inpharmatics Inc., which Merck acquired in 2001. Instead of studying patterns in space, they study patterns of how genes turn off or on in response to a drug or a disease.
That complex pattern yields a sort of molecular fingerprint for each drug. Researchers assemble the fingerprints into a database, and algorithms can then be used to make certain predictions about a drug compound based on its unique fingerprint. Say, for example, a new drug candidate is tested on liver tissue. The tissue will show a certain pattern of gene expression, which may resemble the gene patterns in liver tissue samples that have been exposed to drugs known to trigger deadly side effects. If so, scientists get an important red flag that the new drug candidate might be toxic. Merck is now using these patterns to prioritize which compounds go into human testing, with the hope that the lineup will have fewer "criminals" than in the past.
TESTING EFFECTIVENESS. Once researchers have a compound they think could be a winner, they still need to spend millions of dollars doing expensive human trials to prove it. And too often, compounds that look great in the laboratory fizzle in real world testing. To avoid such disappointments, Dr. Michael R. Jackson, senior vice-president for drug discovery at Johnson & Johnson's La Jolla (Calif.) facility, is exploring new trial methodologies. In 1999, the company was looking at a new drug for rheumatoid arthritis, a disease in which the immune system runs amok, attacking patients' joints. Rather than wait for a large-scale trial to show whether the drug actually worked, the company decided to run a small study with just 24 patients. It was no simple pilot study. Jackson's group gave 12 volunteers a dose of an experimental compound being studied for use in RA. Another 12 didn't get the compound. All 24 were then injected with a molecule called lipopolysaccharide (LPS), a component found in the cell wall of bacteria. Since LPS isn't a live bug, it doesn't cause an infection -- but it still triggers an immune response by the body. With luck, the experimental compound would dampen the immune response triggered by the LPS, in which case it might also work against RA.
To gauge the response to LPS, J&J turned to the latest tricks of genomics. Researchers took a series of blood samples from each volunteer over the course of several hours after they received the LPS injection. From that sample, they isolated RNA, the messenger molecules that carry instructions from genes to protein factories in each cell. If the scientists could spot which RNA was present, they would be able to tell which genes were being turned on in their volunteers.
The RNA was tagged with a fluorescent label and put onto tiny glass chips containing samples of genes with known functions. When the RNA linked up with its matching DNA, those spots glowed, showing which genes were active. Jackson's team studied those patterns from the various blood samples and found encouraging results: There was almost no immune response in those patients who got the experimental drug. J&J ran into some side-effect issues and is now reformulating the compound. But for Jackson, there was an important take-away: While large-scale trials are unavoidable, small trials like this one will help spot winners earlier than ever.
Sophisticated techniques like J&J's are needed to crack the toughest challenges in medicine. Instead of treating symptoms of disease, most drugmakers will soon be focusing on the root causes of illness. This is the Mt. Everest of modern medicine -- and on clear days, the destination seems almost within reach. "The growing scientific knowledge and advances in technology more than offset the increasing difficulty of the targets," declares Merck's Peter Kim. If he's right, the benefits will flow not only to drugmakers and investors but also to public health around the world.
By Amy Barrett in New London, Conn., John Carey in West Point, Pa., and Michael Arndt in North Chicago, Ill., with Arlene Weintraub in La Jolla, Calif.
— With assistance by Arlene Weintraub