Neglected Tropical Diseases (NTDs) are a group of diverse conditions prevalent mostly among impoverished communities in tropical areas. They require targeted preventive and curative treatments, with nearly 1.6 billion people in the world requiring interventions for at least one of these diseases every year. The cost to the affected communities runs into billions of dollars each year, straining their socioeconomic fabric. NTDs need to rank higher on the global health agenda to achieve the Sustainable Development Goals.
Running clinical trials for NTDs is crucial in finding effective solutions, but the rising costs of these trials can be prohibitive. Many factors including trial protocol design choices, the number of subjects, sites and visits, and the type of interventions can substantially affect their cost.
Fast Data Science aims to mitigate these challenges with the Clinical Trial Risk Tool. This innovative tool uses machine learning algorithms and natural language processing to provide estimations on the cost of clinical trials early during the planning stages.
The tool works by reading and understanding the protocol text, i.e., the document that outlines how to conduct the clinical trial. The protocol text contains essential details about the planned methodology, types of interventions, number of participants, required tests, etc.
Based on the protocol text analysis, the Clinical Trial Risk Tool can predict crucial information such as the total cost, expected timelines, and possible risk factors. The tool can also identify the interventions involved, which are often significant cost factors. For instance, gene and cell therapies are generally more expensive.
This predictive approach allows the involved stakeholders to make informed decisions on resource allocation, identify cost-effective strategies, and mitigate risks proactively. It facilitates planning more sustainable clinical trials, which, in turn, can contribute to addressing NTDs more efficiently.
Fast Data Science’s Clinical Trial Risk Tool has great potential in dealing with the economic challenges related to NTDs clinical trials and can become a reliable ally in strategizing global health policies for the betterment of affected communities.
