The cost of conducting a clinical trial is massive and complex, with several factors to consider. These factors range from the number and type of interventions involved in the trial, the geographical location of the trial, and the sample size of subjects involved. For instance, a median cost of a clinical trial between 2015 and 2016 was reported to be $19 million, with some reaching up to 100 times that cost!
Among these costly trials are those focused on Motor neurone disease (MND), an uncommon condition that weakens the brain and nerves. Unfortunately, despite continuous research efforts worldwide, the only existing license for MND treatment in the UK is for riluzole - a drug that slows down the progression of MND but doesn’t eradicate it.
Each MND clinical trial, therefore, involves a significant financial investment, but they are critical to finding more effective treatments and hopefully a cure for MND. On that note, an accurate cost estimation of these clinical trials is essential for budget allocation and planning, in order to ensure that funds are utilised efficiently.
So how exactly can the cost of an MND clinical trial be estimated from its protocol?
Fast Data Science has developed a cutting edge Clinical Trial Risk Tool that utilises machine learning to predict the cost of a trial from its protocol text. The tool examines factors such as the number of interventions (and their type), number of subjects, and visits, among others, and uses this data to make accurate predictions about the cost of a trial.
Machine learning is a versatile tool that allows developers to create intricate models that learn patterns from existing data sets and use these patterns to make predictions about new, unseen data. In this case, the tool is trained on prior clinical trial costs and outcomes based on the trial protocol text.
This technology empowers sponsors, healthcare professionals, and scientists to anticipate the costs associated with MND trials (as well as trials for other conditions), allowing for better planning and budgeting for these critical experiments. By carefully managing the resources dedicated to MND trials, every penny can be dedicated to conducting important research, finding effective treatments, and hopefully moving closer toward an eventual cure for this debilitating disease.
Thus machine learning provides us with a powerful method to demystify the costs of MND clinical trials, aiding researchers and doctors in their mission to combat this devastating disease.
