Matthew Michelson, CEO
Evid Science represents a substantial technological shift for healthcare professionals who are used to sifting through a never-ending amount of medical literature in order to stay up to date on the latest medical advancements. In the past, HCPs had to spend a significant amount of time and money to analyze the literature in order to uncover therapy differentiation, answer strategy questions, or optimize clinical protocols. While answers were typically buried in the literature somewhere, it was a daunting task to retrieve them.
Evid Science does the work for them by automatically curating the largest database in the world of patient-level outcomes for various therapies—all backed by the scientific literature. In order to do this at massive scale, the Evid Science team is building and refining artificial intelligence programs aimed at “reading and understanding” the medical papers, just like a person. By automating the process of pulling the main results from the medical literature, this frees HCPs to ask questions “at the top of the funnel”—allowing them to focus on the creative and analytical tasks, rather than the gathering of the data.
In addition, Evid Science does a quality pass over the article, using machine-learning to generate a probability that the article is scientifically sound, which is then turned into a one-, two-, or three-star rating. Finally, the platform contains highly refined user-interfaces to make it easy as possible for HCPs to filter to the results they care about most or discover the most important and novel insights to them. In this way, Evid Science applies the most advanced machine-learning capabilities to one of the crucial problems in healthcare—making access to therapy evidence as simple and efficient as possible.