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science/technology
Drug Discovery Mairin B. Brennan C&EN Washington
FiIteriπα Out Failures Early in the Game
and optimization at Molecular Simula tions, San Diego, the symposium fo cused on efforts under way to weed out ι alse negatives will kill you," dead-end drug leads early on. maintains Stephen K. Durham, There are no shortcuts in drug devel a distinguished research fellow opment—at least not yet. According to at Bristol-Myers Squibb, Princeton, NJ. Tufts Center for the Study of Drug Devel These are the drug candidates that give opment, Tufts University, Boston, it takes no hint of having undesirable qualities 12 to 15 years to develop a new drug and until they are in the final stages of test bring it to market. For each successful ing, when they're found to have safety new drug, roughly 5,000 compounds are issues. By that time, years of work and evaluated in laboratory and animal stud millions of dollars have been expended ies. Of these, only five will be found suit on pursuing them. "We simply can't af able for human clinical trials, and only ford to squander money on developing one of the five will gain approval by the compounds that ultimately fail," he Food & Drug Administration as safe to says. "Costs are escalating. Costs run market. Understandably, then, drug de everything—whether we like it or not." velopment is an expensive proposition, Durham's weighty pronouncement estimated by symposium speakers to cur underscores the message of a sympo rently cost as much as $500 million per sium on ADME/Tox (absorption, distri drug. Candidates that fail late in the de bution, metabolism, excretion, and tox velopment stage incur huge, unrecover icity) in early drug discovery held at the able expenses. American Chemical Society's spring Roughly 40% of putative drug candi meeting in San Francisco and spon dates—or new chemical entities, as sored by the society's Division of Chem they're referred to by the drug industry— ical Information. Organized by Osman are rejected because of poor pharmacoki F. Giiner, director of lead identification netics, according to Peter D. J. Grooten-
F
huis, senior director of the molecular de sign group at DuPont Pharmaceuticals Research Laboratories, San Diego. These are the compounds that don't make the grade in absorption, distribution, metabo lism, or excretion. Another 11% or so are eliminated from the candidate pool when they show toxic effects in animals. "But the biggest killer for a [pharma ceutical] company is liver toxicity that doesn't show up in human trials," Giiner observes. "You market the drug, and sud denly it has problems in humans. So you have to pull the drug off the market. This is very costly, but it's also very sad." That's because the cost to the industry is only one factor, Giiner notes. Another is the cost in human suffering or lost lives due to adverse properties that weren't identified before the drug went to mar ket. Indeed, one such drug, Warner-Lam bert's Rezulin, used to treat diabetes, was pulled off the market earlier this year when it was associated with liver toxicity in a subgroup of patients. And Janssen Pharmaceutical Propulsid, a drug some times prescribed for treating gastro esophageal reflux disease, "will soon be JUNE 5,2000 C&EN 6 3
science/technology
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available only through a limited-access question being widely addressed in ceptors it can contain. Compounds that program," says company spokesman drug discovery research is, What makes break the rules usually have unacceptGregory Panico. The drug has been a compound druglike? In other words, able solubility or hydrophobicity properlinked to abnormal heart rhythms that re- What are the chemical and structural ties. Some exceptions exist: for example, sulted in a number of deaths in patients properties that enable a compound to the small percentage of drugs that are who were taking certain other medica- behave like a drug? Knowing these pa- carried across the intestinal wall by transtions or were seriously ill. rameters will go a long way in helping to port proteins. But the preponderance of Anything one can do early on to elim- separate winners from losers at the ear- drugs (an estimated 90%) are absorbed from the gut via a concentration gradient a inate such outcomes would benefit both liest stage of drug discovery. the pharmaceutical industry and huThe ideal drug is given by mouth, is ab- passage called passive transport Current manity, Giiner points out. The best pos- sorbed from the gut through specialized research on absorption is largely focused sible scenario, of course, would be the intestinal cells, and reaches and acts on on this type of compound. ability to eliminate undesirLipinski h a s identified able compounds before they -^^— some of the reasons that highend up in clinical trials. "Costs throughput screening turns Bringing anew drug to market up so many hits that are "outrise precipitously in the later can take 15 years liers"—compounds with propstages of the drug developerties that fall outside the ment process," Giiner points boundaries set by his rules. out. 'The ability to identify the Review and approval by compound | One reason is that highultimate failures at an earlier Food & Drug Administration approved throughput screening tends to stage in the process would sigPhase III: Confirms effectiveness and monitors select for larger and more linificantly reduce expenses adverse reactions from long-term use in 1,000 pophilic compounds, he says. without increasing developto 5,000 patient volunteers. Another reason is related to ment and evaluation time." Phase II: Assesses effectiveness and looks for side effects in 100 to structure-based design: When Mark A Murcko, vice presi500 patient volunteers. chemists know a lot about the dent and senior research fellow Phase I: Evaluates safety and ' structure of the target molecule, 5 compounds enter at Vertex Pharmaceuticals, dosage in 20 to 100 healthy • clinical trials human volunteers. the compounds they design to Cambridge, Mass., agrees. The bind to it often have too many Discovery and preclininal testing: majority of compounds never 5,000 compounds Compounds are identified and evaluated in hydrogen-bond donor and aclaboratory and animal studies for safety, evaluated make it to Phase II clinical tribiological activity, and formulation. ceptor groups. These comals, the stage where the drug is I I I I pounds have poor permeability, 16 12 14 8 10 evaluated for efficacy and safeYears lipinski notes. He acknowledgty in humans, he notes. "Much es that a number of outliers can Source: Tufts Center for the Study of Drug Development of this dropout rate is because be converted into suitable drug of ADME/Tox problems," he candidates by working to resays. Thus, drug companies are gearing its target. Most drugs are subsequently duce their size or manipulating other up to develop computational models metabolized in the liver before being ex- properties. "But you're probably going to and experimental methods that will de- creted. Absorption is dependent on solu- work very hard to do this," he observes. tect ADME/Tox properties early on. It's bility and molecular weight as well as on 'The general pattern is that the farther permeability, which requires that the drug out of the acceptable range the properties a daunting task. Automated high-throughput screen- be hydrophobic enough to pass through are, the harder you have to work." To circumvent this scenario, compaing has exponentially increased the the cell membrane. How well a drug binds number of compounds that can simulta- to its target is influenced by the number of nies large and small are turning to bioinneously be evaluated for their ability to its rotatable bonds—too many of them formatics or other computer-based apinteract with a biological target. Combi- make it too flexible or "floppy" to be a proaches to identify lead candidates and natorial chemistry and the billions of goodfit;too few make it toorigid.How filter out failures early in the game. Most compounds it can generate have en- well a drug is metabolized in the liver de- of these screening approaches include sured an unlimited supply of new chem- pends on its affinity for the cytochrome Iipinski's rules and other criteria—properical entities available for screening. The P450 oxygenases and other enzymes that ties associated with toxicity, for example, or those that make a compound susceptiupshot is that high-throughput screen- render drugs hydrophilic for excretion. "Rules" developed by senior research ble to being denied access to cells. The lating is identifying more and more "hits"—compounds that bind to their fellow Christopher A. Lipinski and col- ter situation arises with compounds that biological targets. Thus, an increasing leagues at Pfizer Central Research, Gro- have a high affinity for P-glycoprotein, a number of compounds are being pur- ton, Conn., have been widely adopted by transmembrane transporter associated sued as drug leads, which requires the pharmaceutical industry as yard- with drug resistance that pumps hydromore R&D manpower and drives up sticks for screening out compounds that phobic substances out of cells. Among emerging approaches deR&D spending, Giiner notes. The prob- are likely to have poor absorption profiles lem is that many of these compounds [Adv. DrugDeliv. Rev., 2 3 , 3 (1997)]. signed to screen virtual combinatorial liturn out to be failures. And this situation Iipinski's rules, as they're now referred braries for potential drug candidates are "has accentuated the need" to winnow to, set limits on a compound's molecular methods developed at Vertex. One apweight and lipophilicity as well as the proach is based on a neural network out the losers at the start, he says. Not surprisingly, a fundamental number of hydrogen-bond donors and ac- that incorporates information from two 6 4 JUNE 5,2000 C&EN
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science/technology distinct databases—the Comprehensive Medicinal Chemistry (CMC) database, a compilation of drugs or "neardrugs," and the Available Chemicals Directory (ACD), a collection of commercially available compounds "that, in general, are not very druglike," Murcko explains. "We used neural networks to ask whether we could come up with a set of descriptors, or properties, that would distinguish the drug molecules from the molecules in the ACD database," he explains. "So when we say a new molecule is druglike, we mean the neural network has classified the new molecule as having properties that are more similar to the molecules in the CMC database" \J. Med. Murcko Murcko Cheni., 4 1 , 3314 (1998); 42,4942(1999)]. Another approach, dubbed REOS, for rapid elimination of swill, incorporates more of the 200 ADME/Tox screening
alerts, or filters, developed over the past five years at Vertex. "These filters are not black-box solutions," Murcko explains. 'They have been generated through the collaborative efforts of pharmacologists, toxicologists, enzymologists, and chemists." Also incorporated into REOS are threshold values for solubility, lipophilicity, molecular weight, and other properties that influence a compound's ADME/Tox profile [Drug Discovery Today, 3,160 (1998)]. Murcko offers an example of REOS's proficiency: A few years ago, the program was used to screen a virtual library of 30 million compounds that could be synthesized from all the ring compounds with a free amine group and all the ring compounds with a free acid group that were in the ACD database. "When we ran REOS, only about a million survived" as druglike, Murcko notes. "With
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the new, stricter rules we have today, the number is down to 200,000." Vertex's efforts are directed at building knowledge-management tools that will help chemists in deciding which molecules to synthesize. 'The vast majority of compounds that a chemist might be able to make are really not worth making," Murcko, himself an organic chemist, asserts. "And all the chemists I've discussed this with agree. But it's important to point out that the chemists decide what molecules go into the virtual analysis and the chemists decide which molecules to pursue." The screening tools are meant "to help them analyze the problem and make the best possible decisions," he says. "I think we are just at the beginning of being able to make predictions in a robust and reliable way," Murcko continues. "None of us knows a whole lot yet about how to do this." A lot of the literature data and experimental information contains errors, he notes. For example, data on bioavailability or blood-brain barrier penetration "can be somewhat sloppy," he says, because measurements vary
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science/technology depending on how and where they were made. To accommo date such discrepancies, Vertex's neural network incorporates Bayesian statistics, which are based on the theory of probabili ty and are "very tolerant of er rors," Murcko says. Still, the neu ral network approach is just one type of "machine learning" that can be used to screen virtual li braries, he says. "We and lots of other people are investigating many different types of machine learning." Among other companies devel oping computational, or in silico, Lipinski (left) and Durham screening approaches are Phar macia of Kalamazoo, Mich., and Pharma Jay T. Goodwin, and is using it to develop copeia of Princeton, N.J. Led by senior structure-based computational models of scientist Philip S. Burton, Pharmacia re cell permeability. searchers are developing models for ab Pharmacopeia has developed compu sorption by relating the results of in vitro tational models for predicting absorption assays to the structural characteristics and blood-brain barrier penetration using and physical-chemical properties of the literature data and data from the compa compounds assayed. The company has ny's own large collection of compounds been collecting such data for the past 10 (C&EN, Feb. 7, page 5). The models are to 15 years, observes research scientist used to screen large combinatorial librar
ies before synthesis as well as small series of compounds, notes William J. Egan, a research scien tist in the company's Center for In formatics & Drug Discovery. "It was a big thorn in our side dealing with literature data, be cause we had to throw out large quantities of it," Egan says. Much of the data was "simply not compa rable," he explains. The problem is due to significant variations among results from different labo ratories, or even the same lab, de pending on experimental method, for example. And that problem needs to be addressed, he insists. Another company creating ADME/Tox models is two-year-old Camitro Corp., Menlo Park, Calif., whose mis sion is "to be the foremost developer and provider" of computational models for de signing optimal therapeutic drug candi dates. 'We are growing so fast"—from five to 25 employees in the past year— says Jie Q. Wu, director of computational modeling. Camitro's complement of sci entists working in concert to build the
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