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Toxicity Software

Pfizer’s R&D headquarters in New London, CT, sits across the Thames River from its Groton research facility, overlooking a large estuary flowing into Long Island Sound. But the idyllic scene of sailboats outside his office window does little to soften the intensity of Stephen Williams, Pfizer’s executive director of clinical technology. Williams’s job is, after all, to worry about failures-especially very expensive ones.

Although failure is a fact of life for drugmakers, the timing of such failures is key. If a compound proves ineffective or possibly toxic while still in the lab, it’s no big deal. But if a compound survives early lab tests only to fail years later during large-scale and expensive human testing, it can cause losses of tens of millions, or even hundreds of millions, of dollars, not to mention the time wasted that could have been spent developing other drugs. Less than 20 percent of compounds beginning human clinical testing survive to the end, and, says Williams, the survival rates “for really novel drugs are worse.” The “horrifically expensive” failures, he adds, are those that occur in Phase III trials, the final set of human clinical tests that often involves thousands of patients in studies that can last years.

One promising means of avoiding these failures is more accurate tests that detect, at an early stage, subtle biological changes going on in a patient that reflect whether a drug is succeeding, failing, or perhaps proving toxic. Such “biomarkers” can help researchers prove a drug is working. But they can also serve as a cheap, easy, and more effective way to weed out drug candidates. “Just by identifying early and cheaply the failures, you make the [productivity] problem go away,” maintains Williams.

The early detection of liver toxicity is one pressing challenge. According to Williams, Pfizer has wasted about $2 billion over the last decade on drugs that failed in advanced human testing-or, in a few instances, were forced off the market-because of liver toxicity problems. Consider the antibiotic drug Trovan, a treatment for severe infections. Pfizer launched the medicine in early 1998 to much fanfare and amid predictions that it would be the company’s next blockbuster. Later that year came the news that all drug manufacturers dread: the medicine was apparently causing potentially fatal liver damage in some patients. In 1999 the FDA severely limited use of the once promising medicine.

A potential method for avoiding a recurrence of this nightmare is to use advanced software to spot otherwise invisible biomarkers. Pfizer mathematicians have developed algorithms to parse out subtle signs of liver toxicity that are missed in conventional analysis of blood tests performed during clinical trials. Normally, reviews of such tests would flag only highly elevated levels of a particular factor. Minor changes are ignored as long as they fall within the normal range. But the new algorithms look for certain patterns within these minor changes. Preliminary testing on a small number of failed drugs showed that such patterns did, in fact exist, says Williams. To validate the findings, the researchers now plan to go back over the company’s vast database of blood tests, which covers years of clinical trials and millions of patients, to see if they can further pinpoint patterns correlated with toxicity.

This project will be complex and costly, but if Pfizer could save a substantial fraction of that $2 billion it spent on liver-damaging drugs, it would roughly represent the annual revenues of a new blockbuster product. And for patients, it could mean avoiding the sufferings of another Trovan.

Better biomarkers could also help find drugs for chronic, progressive diseases like Parkinson’s, in which symptoms can take years to develop, and for mood disorders like depression, whose symptoms are difficult to quantify. Because it’s hard to measure the effectiveness of drugs for these diseases, drugmakers are often reluctant to even attempt to develop them. “If you don’t have a good way of measuring [the progress] of a disease, it is almost impossible to develop a drug for it,” Williams says.

One unconventional but simple biomarker that could help is the sound of a patient’s voice. Pfizer researchers are trying to leverage recent scientific findings that measurable changes in a person’s voice can predict his or her sleepiness; they hope to extend that finding to correlate changes in voice to mood swings in patients with depression or to brain damage caused by neurodegenerative diseases. Pfizer’s preliminary studies indicate a patient’s mood could in fact be gauged by changes in his or her voice. Likewise, the company has encouraging results suggesting that researchers can measure vocal changes in Parkinson’s patients. “It is pretty obvious that there are changes,” says Williams. “You can hear them. But we showed that we could measure changes before they became audible.”

The availability of such inexpensive means of measuring whether a compound is having any effect on a disease could be a boon for researchers testing drugs for such progressive conditions as Parkinson’s and Alzheimer’s. Instead of waiting, say, five to 10 years as symptoms wax or wane, researchers could quickly and easily determine whether a drug is working. Not only would that allow them to test greater numbers of different compounds, it would, says Williams, encourage far more research on diseases that have long been “handicapped by difficulties in measuring them.”

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Tagged: Biomedicine

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