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THREAD Blog
Three Keys To Building Effective AI-Driven Products
Artificial intelligence, while already at work in many applications, remains a mystery and even a buzz term for many working in technology. AI will only continue to evolve, and its use will increase. For companies developing products that will utilize AI, it is critical to have clear objectives.
Decentralized Clinical Trials: How to Balance Technology & Humanity
Hybrid and decentralized clinical trials (DCTs) are becoming more prevalent as they can better address the constraints associated with in-person visits including: mobility, proximity to research sites and the time or cost associated with attending the clinic. Although DCTs can be more convenient than in-person trials, is there a risk of relying too much on technology at the expense of person-centered communication?
Consider a DCT provider that collaborates
To better serve the customer to help combat the difficulties faced in early 2020, DCT providers like THREAD, started to partner with organizations in a few key areas to enable additional use cases. But when it comes to recruitment or data and analytics for example, you want to know that DCT provider that you are using can meet the needs of your study.
A look into the hyper-acceleration of life sciences with Sean Vassilaros
We are obviously concerned about the safety and efficacy of clinical research, but we also want to make sure we are going down the right path when it comes to the goal of life sciences: taking care of the patient. In fact, Sean Vassilaros, COO of THREAD uses the phrase, ‘appropriate-effort’ to discuss the matter when asked how he believed this process was able to be expedited. "We just learned in the last year, that if you use appropriate effort to bring something to production, you're allowed to move at lightning speed."
Make the most of data collection with these 4 simple steps
Questions have always existed around data from patients, and it's largely due to the ongoing challenges that are faced that make it difficult to detect noise such as recall bias, observer-expectancy effect, and response bias. The capability to overcome these challenges within the industry is an innovative process of combining these data collection methods into one cohesive offering.