With the global Artificial Intelligence (AI) in Drug Discovery Market size expected to exceed $3,900 million by 2027, this year’s agenda will .. Read more encompass key drivers leading the way into a shorter, cheaper, and more successful R&D era. The conference will cover hot topics including; machine learning techniques for improving early drug discovery, effective prediction of ADMET properties, data quality, and innovative applications of AI for undruggable targets. This year’s event will focus on 4 key themes: machine learning and automation for improved drug discovery pipelines; effective prediction of compound properties; data robustness and curation; innovative use of AI for rare and undruggable diseases. The agenda will highlight key case studies across these themes, uncovering key developments in pharma of data optimization and to aid therapeutic discovery. This two-day agenda offers you peer-to-peer networking with industry experts including directors and heads of informatics, data & AI, molecular design, and computational chemistry, to explore the latest developments in the industry, regulatory updates, and case studies from leading pharmaceutical and biotechnology companies. AI in Drug Discovery will explore the latest industry case studies from leading pharma and biotech companies on machine learning and improved drug discovery pipelines. Understand how AI can be effectively implemented to enhance discovery R&D, delve into best practices in data quality, curation and validation, and examine novel uses of AI to unlock therapies that have evaded traditional drug discovery.
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