Managed Care - September 2008 - (Page 22)

EDDY: With any start-up company, it takes time. We’re gaining very rapidly on our costs, but we’re not quite at break-even yet. MC: Is there anyone who wouldn’t want to see Archimedes expand or be successful? EDDY: This model competes with other commercial and academic organizations that build models. Archimedes is a very, very different type of model, and many people find it to be much more flexible, much more powerful, and much better validated than other models. MC: You mentioned earlier that clinical trials are used to validate the model. How does that work? EDDY: We think that the ultimate test of a model ought to be how well the calculations performed in the model match what is actually seen in the real world, so we rerun clinical trials that have not yet been incorporated into Archimedes to make sure we get the same results that appeared when real people were involved. We set up the trial in the model to see if the virtual people in the virtual world have outcomes at the same rates as people in the real world. We do this over and over and over again. We have done about 200 validations — exercises involving different populations, interventions, and outcomes — and the model has turned out to be remarkably accurate. Every year we do 12 to 18 new trials to continually validate the model and make sure it’s right. MC: For the sake of argument, if the model can essentially duplicate a clinical trial’s output, why do the clinical trial at all? EDDY: We don’t promote the model as a substitute for clinical trials. The reason we will always need to do clinical trials goes back to the question you asked earlier: Can the model be wrong? Mother nature always has some surprises up her sleeve, and if you don’t do clinical trials you’ll never find those surprises. So our position is that if it is possible to perform a clinical trial to answer a question, then do the clinical trial. On the other hand, we all know that the number of problems people face and the number of different options that have to be considered far exceed the number of options that you can study with a clinical trial. And when you throw in the phenomenally high cost of clinical trials, the fact that they take years to conduct, and the fact that technology changes while the trial is in progress so that re- sults can be outdated almost the day they are released, there is a need for a tool to answer questions for which a clinical trial cannot feasibly be done. That’s where Archimedes is appropriate. MC: Can you foresee a day when the FDA might use Archimedes data in making a decision on whether a drug should be marketed? EDDY: I can, but Archimedes should not be used to replace the main trials that pharmaceutical companies now have to conduct to demonstrate the effectiveness of a drug on clinical outcomes. That being said, after the effect of the drug has been established there are often additional questions that cannot feasibly be answered by additional clinical trials. These can be good applications of the model. Examples might be the effect of the drug on a population that has a different mix of risk factors than the original trial population, or the effect of a change in a dose of the drug, or the long term effects on utilization and costs. MC: So if a health plan had a drug that might do some good for a pediatric population, could that company run it through Archimedes, see what the effect might be on a pediatric population, and decide that way? EDDY: It would really come down to the extent to which for this particular drug, we can think of children — the pediatric population — as being small adults. That assumption might not hold. We know, for example, that the effects of a growth hormone in a child are different than in an adult. That’s a case where I would not want to say that the results we see in adults could just be transferred down to a younger age group. MC: But do you have algorithms that adjust for the pediatric physiology? EDDY: We would need to go into the basic science and then build in a pediatric version, if you will, of the physiology that’s pertinent to the particular drug and its mechanism of action. Our ability to do that would depend on the quality of the data about those physiological pathways in the pediatric population. If good data exist for building and validating the physiological pathway, then we could do that with confidence; if not, then we could not. We can take this model as far as medical science will go. We do not want to take it beyond that point. MC: Thank you. MC 22 MANAGED CARE / SEPTEMBER 2008

Table of Contents Feed for the Digital Edition of Managed Care - September 2008

Managed Care - September 2008 Editor’s Memo Contents Legislation & Regulation News and Commentary Medication Management Compensation Monitor Archimedes Lends Hippocrates a Hand Some Other Predictive Modeling Programs Messing With Medicare Advantage The Trouble With MAC MedPAC’s Suggestions Sound Familiar The Leader in Patient Satisfaction Formulary Files Plan Watch Tomorrow’s Medicine Ad Index Outlook

Managed Care - September 2008

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