Drug discovery is a process that takes several years , as it includes several different plashes, apart from being complicated, expensive, and time-consuming. Because of that, nowadays scientists and informatics are increasingly working together in the processes of drug discovery using technology based on Artificial Intelligence (AI).
Computer tools were developed for being able to identify potential biological active molecules from great numbers of candidate compounds quickly and cheaply. But, when drug discovery moved into the area of AI and big data, using Machine Learning (ML) and Deep Learning (DL) was started to be possible to analyze clinically relevant massive amounts of data that guide the discovery of new potential targets, and consequently drug discovery.
As of today, several drugs were discovered using this technology. For example, the first drug created using AI was DSP-1181, which is a potent serotonin 5-HT1A receptor agonist. The time that took the discovery of it was less than 12 months from initial screening to the end of preclinical testing.
Now we closed the publication phase and launched the post-publication phase of the conference. REVIEWWWERS'08 Brainstorming Workshop is Now Open from 2023-Jan-01 to 2023-Jan-31. MOL2NET Committee, Authors, and Validated Social Media Followers Worldwide are invited to Post Moderated Questions/Answers, Comments, about papers.
Please kindly post your public Answers (A) to the following questions in order to promote interchange of scientific ideas.
These are my Questions (Q) to you, please kindly post your public Answers (A) below to promote scientific discussion and training of conference readers :
Q1. Have any specific limitations or challenges been encountered in the use of AI and ML in drug discovery?
Q2. Have there been any unsuccessful trials using these technologies?
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