Monty Hussain discusses his experience working with Ontotext’s Target Discovery Solution, and what he and his team have been able to achieve.
Highlights:
- Identifying and prioritizing candidates for cancer research can be time-consuming and resource-heavy due to the large amount of data to sift through.
- If Monty’s team were going to manually do this, going from these large data sets to picking out a few candidates, Ontotext Target Discovery saved them time.
- Target Discovery has impacted research by unlocking new thinking patterns, expanding beyond prior criteria and allowing for the compilation of all available literature.
- The process of working with Ontotext has shifted from small-scale user-guided input to AI-driven large-scale prioritization of candidates, which has been phenomenal.
- It was easy to upload all the criteria to all the genes and compile all the resources we needed to answer our specific research question, which was great.
- It can be an excellent tool for researchers, always open as a tab, providing quick access to literature search, patterns, and building rationale for research.
Do you think your use case can benefit from the Ontotext Target Discovery solution?
