inVerse - learning from aggregate data to improve outcomes

Volv has developed a way of deriving fine-grained insights and learnings from aggregate data such as summary clinical trial results. This singular ability to "unbake the cake" into its components has been productised as Volv inVerse.

Precision medicine is about knowing individuals

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Volv can generate significant value from failed trials

inVerse - Multiple Sclerosis as a case study

Volv shows how data mining clinical trials can improve outcomes for Multiple sclerosis (MS) patients, (MS is a progressive, immune-mediated disorder), by reducing disease progression through predictive models based on patient phenotypes, which can be utilised by clinicians.