A Handbook of Artificial Intelligence in Drug Delivery 1st Edition

Grab the future of pharmaceutics with A Handbook of Artificial Intelligence in Drug Delivery, 1st Edition by Anil Philip, Aliasgar Shahiwala, Mamoon Rashid, and Md Faiyazuddin. This compelling guide connects cutting‑edge AI techniques with practical drug delivery challenges, making it an essential resource for scientists, formulators, and decision‑makers worldwide.

Explore clear, application‑focused chapters that demystify machine learning, deep learning, and predictive modeling for formulation design, nanoparticle engineering, targeted delivery, and pharmacokinetic optimization. The book balances theory with real‑world examples, showing how data‑driven approaches reduce development time, improve targeting accuracy, and enhance clinical translation. Regulatory considerations, validation strategies, and ethical aspects are addressed to support safe, scalable deployment in industry and academia.

Whether you’re a pharmaceutical researcher in India, a biotech engineer in Europe, or a clinician‑scientist in North America, this handbook delivers actionable insights that accelerate innovation. It’s ideal for graduate students, R&D teams, and regulatory professionals seeking to integrate AI into formulation pipelines and translational studies.

Readable yet rigorous, the text highlights workflows, model selection tips, and troubleshooting guidance so teams can implement AI solutions confidently. Forward‑looking sections map future trends and opportunities for collaboration between AI specialists and drug delivery experts.

Order your copy of A Handbook of Artificial Intelligence in Drug Delivery today to empower your research and product development with smart, evidence‑based strategies that meet global standards and drive measurable results.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.