AIMC Topic: Drug Discovery

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Deep learning in preclinical antibody drug discovery and development.

Methods (San Diego, Calif.)
Antibody drugs have become a key part of biotherapeutics. Patients suffering from various diseases have benefited from antibody therapies. However, its development process is rather long, expensive and risky. To speed up the process, reduce cost and ...

Leveraging artificial intelligence in the fight against infectious diseases.

Science (New York, N.Y.)
Despite advances in molecular biology, genetics, computation, and medicinal chemistry, infectious disease remains an ominous threat to public health. Addressing the challenges posed by pathogen outbreaks, pandemics, and antimicrobial resistance will ...

Artificial intelligence and cheminformatics tools: a contribution to the drug development and chemical science.

Journal of biomolecular structure & dynamics
In the ever-evolving field of drug discovery, the integration of Artificial Intelligence (AI) and Machine Learning (ML) with cheminformatics has proven to be a powerful combination. Cheminformatics, which combines the principles of computer science a...

Integrating inflammatory biomarker analysis and artificial-intelligence-enabled image-based profiling to identify drug targets for intestinal fibrosis.

Cell chemical biology
Intestinal fibrosis, often caused by inflammatory bowel disease, can lead to intestinal stenosis and obstruction, but there are no approved treatments. Drug discovery has been hindered by the lack of screenable cellular phenotypes. To address this, w...

OCMR: A comprehensive framework for optical chemical molecular recognition.

Computers in biology and medicine
Artificial intelligence (AI) has achieved significant progress in the field of drug discovery. AI-based tools have been used in all aspects of drug discovery, including chemical structure recognition. We propose a chemical structure recognition frame...

Emerging Pharmacotherapeutic Strategies to Overcome Undruggable Proteins in Cancer.

International journal of biological sciences
Targeted therapies in cancer treatment can improve efficacy and reduce adverse effects by altering the tissue exposure of specific biomolecules. However, there are still large number of target proteins in cancer are still undruggable, owing to the f...

New directions in psychiatric drug development: promising therapeutics in the pipeline.

Expert opinion on drug discovery
INTRODUCTION: Psychiatric disorders are a leading cause of disability worldwide, calling for an urgent need for new treatments, early detection, early intervention, and precision medicine. Drug discovery and development in psychiatry continues to exp...

A statistical comparison between Matthews correlation coefficient (MCC), prevalence threshold, and Fowlkes-Mallows index.

Journal of biomedical informatics
Even if assessing binary classifications is a common task in scientific research, no consensus on a single statistic summarizing the confusion matrix has been reached so far. In recent studies, we demonstrated the advantages of the Matthews correlati...

Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES.

Journal of computer-aided molecular design
Using generative deep learning models and reinforcement learning together can effectively generate new molecules with desired properties. By employing a multi-objective scoring function, thousands of high-scoring molecules can be generated, making th...

Quantum computing for near-term applications in generative chemistry and drug discovery.

Drug discovery today
In recent years, drug discovery and life sciences have been revolutionized with machine learning and artificial intelligence (AI) methods. Quantum computing is touted to be the next most significant leap in technology; one of the main early practical...