Within the life science industry it is very important to identify key individuals working on the latest innovations for a particular indication. Advancing R&D involves collaborating with the right external stakeholders. This case provides a good strategy to find these experts.
"We need to find experts in drug development working with machine learning in Europe"
In order to find these experts it is important to use search terms relevant to the specific indication of interest. In this case, three keywords can be used as search terms as described below:
As covered in the Search and Construct Search Strings article, when this search is performed, the logic will be by default "machine learning AND drug discovery AND drug design". This means that the experts must be working with all three search terms in order to show up in the list of results (learn more here if you would like to use a different logic for the search).
It is important to consider that not all the experts returned on the keyword search will be relevant for this use case. For R&D purposes, it is important to not only consider the expert's relevance to the field but also the expert's level of seniority. For this use case, the following filters can be used:
By using "Europe" in the location filter, one can select only experts based in the area.
- Author Characteristics
This filter helps to address a certain level of seniority, based on scientific productivity over time. One can use total number of publications = 100+ and also set the total number of publications as last author = 10+. In Monocl Professional, experts with these characteristics are tagged as "Senior Authors", meaning that you will select only senior experts with these filters. The "Senior Author" tag is represented by a "S" close to the name of each expert in the list (see screenshot below).
Note that the filters and their specification are indicated in the green rectangles in the top of the list. To help rank the experts that are relevant, it is possible to use the sorting option on top of the list. In this case, experts are ranked by "Relevance" and "Active in the last 2 years" in the topic indicated by the keywords.
The screenshot above shows now a list of 579 relevant experts to be considered for this use case. You can quickly check this information not only by looking at the numbers disclosed under each name, but also by exploring the charts for each expert on the right side. After selecting the right experts, it is possible to save the data in a project (see tutorial here) or export the list as an Excel, PowerPoint or CSV files (see tutorial here).