How can social networks be used to study medicines?

Kap-Code provides an innovative epidemiological analysis solution for use with social networks. Through a mathematical, semantic, and numerical approach, our algorithms extract high-quality information about medicines. When it comes to identifying secondary effects, the sensitivity of these algorithms exceeds 80%. Our methods make it possible to scientifically synthesise information by going beyond sentiment and opinion analysis, which is not well suited to analysing medicine-related issues on social networks.

Extract

The initial step in the DETEC’T solution involves selecting your sources of information. These sources can vary depending on the field and are selected according to criteria that guarantee the high-quality of the data collected.

Code

Our algorithms code patient language in standardised medical language by using medical dictionaries such as MedDRA and the ATC classification system.

Analyse

Depending on the desired indicators, we use algorithms produced through rigorous studies that combine semantic, mathematical, and numerical approaches to obtain the best possible results.

OUR DETEC’T DATABASE

ANALYSIS OF OVER 25 MILLION MESSAGES AND 400 MEDICINES

26,862,232

messages analysed

500

medicines analysed

26

sources analysed

12

years of discussion analysed