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| Language | English |
| Format | PDF (Premium Digital) |
| Ownership | Permanent download — yours forever |
Applied Artificial Intelligence for Drug Discovery by Antonio Lavecchia
The integration of artificial intelligence (AI) into pharmaceutical research has redefined the landscape of drug discovery, enabling unprecedented advances across data integration, molecular design, clinical translation, and therapeutic innovation.
Applied Artificial Intelligence for Drug Discovery is a comprehensive and forward-looking volume that explores how AI, machine learning (ML), and deep learning (DL) are revolutionizing the discovery and development of new drugs. Spanning 27 chapters authored by leading international experts, this book presents state-of-the-art methods and practical applications covering the entire drug discovery pipeline.
Topics include AI-based drug target identification, pathway analysis, structure- and ligand-based drug design, generative models for de novo design, peptide discovery, ADMET prediction, retrosynthesis, drug repurposing, and nanomedicine. Dedicated chapters focus on the implementation of large language models, contrastive and few-shot learning, quantum machine learning, federated and explainable AI, and clinical trial optimization.
With its balance of foundational theory, applied case studies, and emerging perspectives, the book offers a unique resource for computational chemists, pharmaceutical scientists, bioinformaticians, data scientists, and R&D professionals.
This volume serves not only as a scientific reference but also as a strategic guide for those looking to adopt AI in pharmaceutical pipelines and therapeutic development. It is equally suited for academic researchers and industrial innovators seeking to unlock the full potential of AI in healthcare.
| ISBN 13 | 9783031980213 |
|---|---|
| ISBN 10 | 3031980212 |
| Author | Antonio Lavecchia |
| Condition | New |
| Binding Type | Hardback |
| Publisher | Springer International Publishing AG |
| Year published | 2026-01-10 |
| Number of pages | 842 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
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"Kindle Unlimited kept raising prices. This is a one-time purchase and the file is permanently on my iPad. Best decision I've made for my reading habit."
"I compared Kindle vs this store. Kindle is cheaper monthly but you don't own anything. Here I paid once and the PDF is mine for life. Highly recommend."
"Left Kindle behind after they removed a book I was reading mid-series. With this PDF, nobody can take it away from me. True ownership feels good."
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