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Contract Sourcing Trials & Innovations Among us commoners, though, the general impression when a drug fails is it wasn't a good drug. Those mysterious chemists and formulators must have gotten it wrong way back in the lab. They should have known the drug would not only fall short of helping patients, but even harm them. Well, perhaps they did, and perhaps they should, but the plain truth of it is this: innovations don't just happen on the bench, they also happen, however miraculously, in clinical trials. Drug sponsors and suppliers have an enormous stake in new drug approvals, an elite cadre of innovations we collectively call "innovation." Even if a drug fails later in the process, after a given supplier helps it along, the failure's repercussions reach all the way back to the beginning. Just ask the people whose jobs disappeared in the latest R&D; restructuring by their company's Big Pharma client. Clinical sourcing rises and falls on the fate of individual drugs in development. Conversely, even the earliest actions performed with a drug in development affect its chances of success. A clinical trial is not an experiment but a test of the evidence, like an engineering analysis, leading to a yes or no conclusion as to legal use. To a structural engineer, human drug trials are like measuring all the stresses before opening the bridge to traffic. Nevertheless, trials do yield experimental data, and to the extent the data adds to or changes scientific understanding, the trial may unfortunately never catch up to its own findings. Unless you can change the endpoints in 48 LifeScienceLeader.com W By Wayne Koberstein, executive editor hy do new drugs fail to reach the market? Oh boy, what a question — one sure to cause a stir anywhere you go. Regulators get much of the blame from industry and, to an increasing degree, vice versa. response to the feedback of new science and treatment, the trial may become obsolete long before it ends. Because trials are not set up as experiments, however, the data they produce is rarely reproducible. In fact, a general lack of reproducibility plagues most biomedical research, even at the experimental stages, according to Ulo Palm of Forest Labs. At the R&D; Leadership Forum last February, Palm argued that the ubiquity of poor practices in bio/pharma R&D; makes most published drug data "misleading or flat-out wrong." Like a weak radio transmission, the noise of error overwhelms the signal of "statistically significant" findings of safety and efficacy. This point is so important, yet much too complicated to cover adequately here, that I am inserting the following sources, even though I also placed them in one of my previous blogs: "Handbook: Quality Practices In Basic Biomedical Research (QPBR)," WHO, 2006; and "Best Quality Practices For Biomedical Research In Drug Development," American Society For Quality (ASQ), 2012. As I said then, the documents "offer direction toward common data standards that could ameliorate the problem." Another speaker at the Forum, Ken Getz of Tufts CSDD, blamed many clinical trials failures on the so-called reforms that were supposed to make trials more, not less, effective. Expanding eTrials, moving trials to emerging markets, greatly boosting the number but reducing the size of sites, and outsourcing site management were all intended to lower cost, spread risk globally, speed trials, and October 2013 improve patient and investigator retention. But Getz said the complications the reforms added actually had a negative effect on those areas. He called for a "reboot" that emphasizes investigator and site quality. In a surprising number of cases, trial design and execution sideline otherwise promising candidates. Poor selection of endpoints, mishandled recruitment, bad data management, and disordered site management are often at fault. An example of critical trial design was recently noted by legal expert Allan Green, comparing two competitive Phase 2 trials for the orphan condition Fabry's Disease. (http:// www.fdaregs.com/index_files/Page560.htm) The first product failed to gain FDA approval because the sponsor picked a dose not studied in Phase 1, chose a subjective primary endpoint (pain reduction) for one study, added too many secondary endpoints that produced contradictory results, and conducted faulty data auditing and analysis. The second product ultimately won approval largely because the sponsor determined the Phase 2 dose with a previous dose-ranging study, worked with the FDA to define a surrogate endpoint for accelerated assessment of its primary endpoint (renal function), and produced clean, straightforward data. Fabry's is such a rare disease that the FDA required only Phase 2 studies for the two products described, but Phase 2 failure also afflicts many nonorphan drugs. According to the U.K.'s Centre for Medicines Research, the Phase 2 failure rate is running at about 80 percent, compared to about a 50 percent