Chemspace now offers a NEW SERVICE – DEL-ML-CS Approach!
But what is it all about?
The classical Discovery of small molecule therapeutics is an expensive and long process. Machine Learning (ML) has been actively used to solve this problem, but to achieve good results the model must be trained properly. This requires a huge amount of data obtained under the same or similar conditions.
A combined DNA-Encoded Library (DEL) – Machine Learning strategy is an approach proposed by Kevin McCloskey and his team that we at Chemspace implemented in this service.
Using a DEL screen, it is possible to access quite a big chemical space in a single experiment. This data can be further used to build an ML model with great prediction accuracy. A huge plus is that by using DEL we obtain both positive and negative results for the compounds, which is a crucial point.
Application of such a model to ultra-large chemical space of small molecules provided by Chemspace (CS) allows identifying potent hits from the first screen. This will help to drastically facilitate early Drug Discovery and save a lot of money.
If you are interested or have any questions, feel free to contact us at firstname.lastname@example.org!