| Description |
1 online resource |
| Contents |
Introduction to drug discovery -- Introduction to artificial intelligence and machine learning -- Data types and resources -- Target identification and validation -- Hit discovery -- Lead optimization -- Evaluating safety and toxicity -- Precision medicine -- Image analysis in drug discovery -- Clinical trials, real-world evidence, and digital medicine -- Beyond the patient: advanced techniques to help predict the fate and effects of phamaceuticals in the environment -- Index. |
| Summary |
The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and industries, including the pharmaceutical industry. In an environment where producing a single approved drug costs millions and takes many years of rigorous testing prior to its approval, reducing costs and time is of high interest. This book follows the journey that a drug company takes when producing a therapeutic, from the very beginning to ultimately benefitting a patient's life. This comprehensive resource will be useful to those working in the pharmaceutical industry, but will also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics. |
| Subject |
Drug development -- Data processing.
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Artificial intelligence.
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Pharmaceutical industry -- Data processing.
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Artificial Intelligence |
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Médicaments -- Développement -- Informatique. |
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Intelligence artificielle. |
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Industrie pharmaceutique -- Informatique. |
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artificial intelligence. |
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Artificial intelligence |
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Pharmaceutical industry -- Data processing |
| Added Author |
Ashenden, Stephanie Kay.
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| Other Form: |
Print version: 0128200456 9780128200452 (OCoLC)1158474853 |
| ISBN |
9780128204498 (electronic bk.) |
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0128204494 (electronic bk.) |
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