Development of one new medicine takes about 15 years and costs up to 2-5 billion USD. Usually, 10,000 compounds are tested in the discovery phase, from which 250 preclinical lead substances are selected; the success rate is only 2.5% (hit to lead). Furthermore, from these 250 lead molecules only 5 reach clinical trials (lead to clinic); success rate is 2%.
The success of the process highly depends on selecting the right molecules as starting points. The primary need of chemists in drug discovery is to access the largest possible database of drug-like compounds which they can search intelligently to find the best hit and lead compounds. Up to now, more than 100 million chemical compounds have been synthesised and characterised. However, out of these 100 million molecules only 7-8 million compounds are available “off-the-shelf”.
By developing a method for predicting compounds that are not yet synthesised but can be prepared with robust reactions from existing building blocks and reagents at an affordable price, we are extending the existing chemical space with “virtual molecules”. Mcule realised that the currently accessible chemical space of commercially available compounds is limited. Therefore, last year we started our new project, called ULTIMATE, supported by the European Commission under the Horizon 2020 R&D programme. The goal of the project is to develop a commercial database of 500 million novel, diverse and synthetically feasible compounds with fixed prices, acceptable delivery time and 80% synthetic success rate. The database will be accessible via Mcule from 2019. Beta testing will start soon.
Such a large chemical space would present a major advantage for pharma and biotech companies by increasing their chances to identify novel, effective compounds, which is essential for successful drug discovery. Scientists will find hits and leads more efficiently and, therefore, save time and money. ULTIMATE will save millions of USD for pharmaceutical companies and will reduce the time of early drug discovery to less than 3.5 years from the 6.5 years in average. Thus, the total development time of a new drug can be reduced by 3 years.