Learning to Discover Medicines
Discovering new medicines is the hallmark of human endeavor to live a better and longer life. Yet the pace of discovery has slowed down as we need to venture into more wildly unexplored biomedical space to find one that matches today's high standard. Modern AI-enabled by powerful computing, large biomedical databases, and breakthroughs in deep learning-offers a new hope to break this loop as AI is rapidly maturing, ready to make a huge impact in the area. In this paper we review recent advances in AI methodologies that aim to crack this challenge. We organize the vast and rapidly growing literature of AI for drug discovery into three relatively stable sub-areas: (a) representation learning over molecular sequences and geometric graphs; (b) data-driven reasoning where we predict molecular properties and their binding, optimize existing compounds, generate de novo molecules, and plan the synthesis of target molecules; and (c) knowledge-based reasoning where we discuss the construction and reasoning over biomedical knowledge graphs. We will also identify open challenges and chart possible research directions for the years to come.
Code (0)
등록된 구현이 없습니다.
Tasks
Drug DiscoveryKnowledge GraphsRepresentation LearningSimilar Papers 제목 키워드 기반
Analysis of Bacteriostatic Effect of Chinese Herbal Medicine Against E.coli
To analyze the bacteriostatic effect of Chinese traditional herbal medicines on E. coli, total 35 different preparations (decoction, volatile oil and distillate) of Chinese traditional herbal medicines were tested using …
Cultural Vocal Bursts Intensity PredictionMedicines Question Answering System, MeQA
In this paper we present the first system in Spanish capable of answering questions about medicines for human use, called MeQA (Medicines Question Answering), a project created by the Spanish Agency for Medicines and Hea…
Question AnsweringRecoMed: A Knowledge-Aware Recommender System for Hypertension Medications
Background and Objective High medicine diversity has always been a significant challenge for prescription, causing confusion or doubt in physicians' decision-making process. This paper aims to develop a medicine recommen…
Decision MakingGraph MiningRecommendation SystemsClinical Decision Support System for Unani Medicine Practitioners
Like other fields of Traditional Medicines, Unani Medicines have been found as an effective medical practice for ages. It is still widely used in the subcontinent, particularly in Pakistan and India. However, Unani Medic…
DiagnosticIndustry-Scale Orchestrated Federated Learning for Drug Discovery
To apply federated learning to drug discovery we developed a novel platform in the context of European Innovative Medicines Initiative (IMI) project MELLODDY (grant n{\deg}831472), which was comprised of 10 pharmaceutica…
Drug DiscoveryFederated Learning