What's inside the box.: the future of clinical trials

Last week I reported for a newspaper on a huge trial on different approaches to diabetes screening published in the Lancet. It looked at 8 different ways of screening for type 2 diabetes in a population of 325,000 people over 50 years.
Except it didn’t really. It used a computer model, the Archimedes model, built up over many years. The model has had in the past, some fantastic successes, predicting the results of the CARDS trial with great accuracy, for example.
But there are times when for all the hundreds of thousands of data points, and the most sophisticated algorithms in the model, it gets things wrong. The model did not predict the results from the Illuminate trial that resulted in Pfizer stopping development on torcetrapib, its drug to reduce HDL levels, because of unexpected adverse results.
There is still a lot about the complex interaction of treatments and human physiology that we don’t understand and where we have to use empirical evidence.
Developing computer models of human physiology and the likely effects of medicines (or screening strategies) is likely only to increase as computing power grows. The Lancet trial would have been impossible to do in real life. It would have had to have begun before I was born and would have cost tens of millions of pounds to carry out. It came up with some results which should inform public policy on managing the diabetes epidemic.
But there will be fewer and fewer people who can understand what is going on inside the box. What are the assumptions made, what is the integrity of the data? Today a reasonably informed person can, with a little work, read published clinical trials and come to a sensible conclusion about their quality. If the findings come as the result of the workings of arcane formulae, and manipulation of complex datasets, there is much less opportunity for a non-specialist to be able to make any kind of judgement. I have seen the future of clinical trials, and it worries me.