Crowdsourcing Project Predicts Progression of ALS
sciencehabit writes Using data from old clinical trials, two groups of researchers have found a better way to predict how amyotrophic lateral sclerosis (ALS) progresses in different patients. The winning algorithms—designed by non-ALS experts—outperformed the judgments of a group of ALS clinicians given the same data. The advances could make it easier to test whether new drugs can slow the fatal neurodegenerative disease. For the competition, participants were given just a slice of this data set, collected over 3 months, and asked to design an algorithm to predict how patients would fare in the subsequent 9 months, according to a standard functional scale that measures their ability to move and care for themselves. When predictions from the two winning algorithms were combined, they outperformed estimates solicited from a dozen ALS clinicians who pored over the same data, the authors report. They estimate that using these algorithms to predict outcomes could allow a drug sponsor to reduce the size of the trial by at least 20% and save as much as $6 million in a large phase III trial.
Or is it?
Seems to me that drug makers will charge whatever maximizes their sales revenue, regardless of their development costs.
Lowering their development costs for them might affect whether or not they bring it to market. But if they do, they'll charge as much as they can get away with.
They can't validate a scale using unintervened progression or existing treatments, then pretend it says ANYTHING about a new/unknown treatment. The whole point of a new treatment is to alter the progression of the disease in a new/different way; the whole point of clinical trials is to determine the NEW course of the disease using the NEW treatment.
The claim made here is: a better tool to predict the time progression of headaches treated with aspirin (or beer or sex) can better predict the time progression of a headache treated with some yet-uninvented drug, so we needn't test the new treatment as thoroughly to characterize it. That's like saying "the more predictable sex with your partner is, the more you know about sex with a different partner"
And yes, I AM a physician and molecular biologist.
To me the most interesting part of the article is the creation of the PRO-ACT database. It's an incredible chunk of data, and I hope it inspires similar projects.