{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/chemgan-challenge-for-drug-discovery-can-ai","title":"ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity?","arxiv_id":"1708.08227","date":"2017-08-28","proceeding":null,"authors":["Mostapha Benhenda"],"abstract":"Generating molecules with desired chemical properties is important for drug\ndiscovery. The use of generative neural networks is promising for this task.\nHowever, from visual inspection, it often appears that generated samples lack\ndiversity. In this paper, we quantify this internal chemical diversity, and we\nraise the following challenge: can a nontrivial AI model reproduce natural\nchemical diversity for desired molecules? To illustrate this question, we\nconsider two generative models: a Reinforcement Learning model and the recently\nintroduced ORGAN. Both fail at this challenge. We hope this challenge will\nstimulate research in this direction.","url_abs":"http://arxiv.org/abs/1708.08227v3","url_pdf":"http://arxiv.org/pdf/1708.08227v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"chemgan-challenge-for-drug-discovery-can-ai","repo_url":"https://github.com/aricsvenz/AI_for_Drugs","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"chemgan-challenge-for-drug-discovery-can-ai","repo_url":"https://github.com/cool21th/ai_drug_discovery","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"chemgan-challenge-for-drug-discovery-can-ai","repo_url":"https://github.com/mostafachatillon/ChemGAN-challenge","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"diversity","task_name":"Diversity"},{"task_slug":"drug-discovery","task_name":"Drug Discovery"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1708.08227","atlas_url":"https://app.syntology.ai/?focus=1708.08227","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}