AIMC Topic: Drug Development

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Artificial Intelligence for Clinical Trial Design.

Trends in pharmacological sciences Jul 17, 2019
Clinical trials consume the latter half of the 10 to 15 year, 1.5-2.0 billion USD, development cycle for bringing a single new drug to market. Hence, a failed trial sinks not only the investment into the trial itself but also the preclinical developm...
Clinical Trials, Phase III as Topic Clinical Protocols Artificial Intelligence Patient Compliance Humans Clinical Trials as Topic Drug Development Patient Selection
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The Missing Pieces of Artificial Intelligence in Medicine.

Trends in pharmacological sciences Jul 2, 2019
Stakeholders across the entire healthcare chain are looking to incorporate artificial intelligence (AI) into their decision-making process. From early-stage drug discovery to clinical decision support systems, we have seen examples of how AI can impr...
Humans Artificial Intelligence Delivery of Health Care Drug Evaluation, Preclinical Precision Medicine Clinical Trials as Topic Drug Development Interdisciplinary Research
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Trader as a new optimization algorithm predicts drug-target interactions efficiently.

Scientific reports Jun 27, 2019
Several machine learning approaches have been proposed for predicting new benefits of the existing drugs. Although these methods have introduced new usage(s) of some medications, efficient methods can lead to more accurate predictions. To this end, w...
ROC Curve Computational Biology Drug Development Software Algorithms Datasets as Topic Proteins Data Mining Humans Machine Learning
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A Study on the Application and Use of Artificial Intelligence to Support Drug Development.

Clinical therapeutics Jun 24, 2019
PURPOSE: The Tufts Center for the Study of Drug Development (CSDD) and the Drug Information Association (DIA) in collaboration with 8 pharmaceutical and biotechnology companies conducted a study examining the adoption and effect of artificial intelli...
Humans Artificial Intelligence Drug Industry Biotechnology Surveys and Questionnaires Drug Development
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Prediction of Drug Target Sensitivity in Cancer Cell Lines Using Apache Spark.

Journal of computational biology : a journal of computational molecular cell biology May 23, 2019
Breast Neoplasms Cell Line, Tumor Drug Development Software Female Humans Machine Learning
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Exploiting machine learning for end-to-end drug discovery and development.

Nature materials Apr 18, 2019
A variety of machine learning methods such as naive Bayesian, support vector machines and more recently deep neural networks are demonstrating their utility for drug discovery and development. These leverage the generally bigger datasets created from...
Humans Machine Learning Algorithms Neural Networks, Computer Support Vector Machine Drug Repositioning Nanomedicine Technology, Pharmaceutical Drug Discovery Computational Biology Bayes Theorem Computer Simulation Drug Development Drug Design
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Is one-shot learning a viable option in drug discovery?

Expert opinion on drug discovery Mar 18, 2019
Drug Development Machine Learning Drug Discovery Humans Neural Networks, Computer
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Predicting drug-target interactions using Lasso with random forest based on evolutionary information and chemical structure.

Genomics Dec 11, 2018
The identification of drug-target interactions has great significance for pharmaceutical scientific research. Since traditional experimental methods identifying drug-target interactions is costly and time-consuming, the use of machine learning method...
Software Drug Development Receptors, Cytoplasmic and Nuclear Machine Learning Databases, Protein Receptors, G-Protein-Coupled Ion Channels Protein Conformation Position-Specific Scoring Matrices
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Closed-loop discovery platform integration is needed for artificial intelligence to make an impact in drug discovery.

Expert opinion on drug discovery Nov 29, 2018
Humans Drug Development Machine Learning Artificial Intelligence Drug Discovery
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Learning for Personalized Medicine: A Comprehensive Review From a Deep Learning Perspective.

IEEE reviews in biomedical engineering Aug 7, 2018
With the recent advancements in analyzing high-volume, complex, and unstructured data, modern learning methods are playing an increasingly critical role in the field of personalized medicine. Personalized medicine (i.e., providing tailored medical tr...
Drug Development Precision Medicine Humans Deep Learning Research
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