What will you learn?
The development of medicinal chemistry is advancing very rapidly. Big pharmaceutical companies, research institutes and universities are working on ground-breaking solutions to help patients combat all kinds of diseases. During that development process, tons of data are generated – not only from the lab environment but also from clinical trials. Since discovering more potent, safer and cheaper drugs is the ultimate goal of all research bodies, we should all focus on making the data we gather FAIR: Findable, Accessible, Interoperable, and Reusable to push the boundaries of drug development even further.
With the currently available methods such as artificial intelligence, machine learning, many toolkits, software and access to various databases, managing big data is now inherently linked to medicinal chemistry and helps to make this area as efficient as it can be.
In this training session, we will explore some concepts related to FAIR data principles and medicinal chemistry, explore the available chemical and pharmacological databases, and perform some basic data analyses using the Galaxy interface.
Participants are encouraged to familiarise themselves with the Galaxy platform and available training materials.
Who is this for?
Everyone interested in data management in medicinal chemistry is welcome to attend.
When registering, please indicate your experience in the listed fields so that we can adjust the level of the training session or divide the participants into groups.
Course prerequisites
None.
However, you should specify your experience in the listed fields in the registration form. Participants are encouraged to get familiar with the Galaxy platform and available training materials.
Questions and contact
Should you have any questions, please contact us at [email protected]
This course is funded as part of the UKRI Innovation Scholars. Data Science Training in Health and Bioscience call (DaSH). (MR/V038966/1)
