Putting to the test: Creating Irrefutable Proofpoints

Once MolecuLern’s AI engine was built, it was time to put it to the test and develop solutions to some of the most challenging drug targets. Examples of actual drugs created by MolecuLern include:

• Neurology: compound targeting ALS where previous candidates have failed due to lack of isoform specificity causing failure to achieve efficacy.
• Metabolics: compound targeting diabetes and cardiovascular disorders where previous candidates have failed due to lack of isoform specificity causing off target effects.
• Oncology: molecular degrader targeting solid tumors where previous candidates have failed to achieve significant efficacy in pre-clinical studies.

Traditional pharmaceutical development, with trial and error, would have taken several years and millions of dollars to develop. MolecuLern was able to design and optimize these compounds from discovery to optimized lead candidates in an average of just six months.

Companies have already begun realizing how to leverage the power of 

• Hit Identification/Lead Optimization
• End-to-End pre-clinical collaboration
• Custom compound optimization
• Custom library screening
• Screen our entire physical/virtual library