How artificial intelligence is changing drug discovery

By Nicole Fleming. Nature, 2018

363 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/04b3d8f9d191cbf259c459b9f9f2e249db5270ba

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In Computational Theory and Mathematics

In Molecular Biology

Citations in the corpus

The ethics of AI in health care: A mapping review. (2020, background): “…in diagnosis (Arieno et al., 2019; De Fauw et al., 2018; Kunapuli et al., 2018), drug discovery (Álvarez-Machancoses and Fernández-Martínez, 2019; Fleming, 2018), epidemiology (Hay et al., 2013), personalised medicine (Barton et al., 2019; Cowie et al., 2018; Dudley et al., 2015) and operational…”
Artificial intelligence in drug discovery and development (2020, background): “Even then, nine out of ten therapeutic molecules fail Phase II clinical trials and regulatory approval [31,32].”
Artificial intelligence vs COVID-19: limitations, constraints and pitfalls (2020, background): “Even long before the COVID-19 outbreak, AI was lauded for its potential to contribute to new drug discovery, see e.g. Coldeway (2019), Fleming (2018), Segler et al. (2018) and Smith (2018).”
A Structure-Based Drug Discovery Paradigm (2019, background): “, a UK-based world class AI-driven drug design company [93] is collaborating with Sanofi to find a cure for metabolic disorders [94], and Clegene, another leading pharmaceutical company, aims to accelerate drug discovery in the areas of autoimmunity and oncology [95].”
Deep Learning for Deep Chemistry: Optimizing the Prediction of Chemical Patterns (2019, methodology): “The latter have been applied for e.g., in QSAR models and drug design (Kadurin et al., 2017; Chen et al., 2018; Fleming, 2018; Green et al., 2018; Gupta et al., 2018; Li et al., 2018b; Lo et al., 2018; Popova et al., 2018; Simões et al., 2018) aiming at identifying systems, molecules and materials…”
Artificial Intelligence and Management: The Automation–Augmentation Paradox (2020, background): “AI is, for example, the major driver behind the current trend toward personalized medicine, with treatments being tailored to each patient ’ s specific biological profile (Fleming, 2018; Lichfield, 2018).”
The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies (2022, background): “Many more examples are available 3,32–37 , showing that AI-based methods can accelerate the drug discovery process and enable the development of more effective medications.”