AI Applications in Pharmaceutical Sciences
Artificial intelligence in drug discovery, formulation and manufacturing; predictive modelling; AI tools and their real-world pharmaceutical applications.
Shree Sai Prakashan is writing a full set of B.Pharm titles to this new NEP 2020 syllabus. Get notified the moment the book for this subject is released, or pre-book sets for your college.
Course contents — unit by unit · PCI NEP 2020 BP604T
Unit 1 · AI in Natural Products & Pharmacognostic Data Modeling 6 hrs
Representing crude-drug data (morphological, microscopic, phytochemical and chromatographic features) and structuring herbal datasets; classification models for authenticating crude drugs; regression models for predicting secondary-metabolite yield; AI in phytochemical screening and herb–drug-interaction prediction; and the limitations of predictive modelling in natural products.
Unit 2 · AI in Medicinal & Pharmaceutical Chemistry 6 hrs
Converting molecular structures into numerical descriptors (MW, logP, HBD/HBA, TPSA); QSAR modelling on structured chemical datasets; regression and classification models for predicting biological activity (IC₅₀, solubility, ADMET) and toxicity; virtual screening and lead optimisation; and the limits of ML models in chemistry.
Unit 3 · AI in Drug Product Design & Performance Prediction 6 hrs
Dosage-form development and formulation variables; machine learning in formulation optimisation and excipient selection; regression modelling for solubility and bioavailability enhancement; time–concentration modelling of drug release; stability-study design and degradation-trend modelling; and shelf-life estimation.
Unit 4 · AI in Process Monitoring & Production Systems 6 hrs
Digital data acquisition in pharmaceutical production; Critical Quality Attributes and Critical Process Parameters; correlation analysis for process variability; logistic-regression models for batch pass/fail prediction; feature importance and predictive-maintenance concepts; and ethical and regulatory considerations in automated decision-making.
Unit 5 · AI in Pharmaceutical Analysis & Chemometrics 6 hrs
Introduction to chemometrics and multivariate analytical data; spectroscopic data modelling (UV/IR interpretation); regression analysis in quantitative pharmaceutical analysis; chromatographic peak modelling; classification models for genuine-versus-counterfeit detection; and handling noise and variability in analytical datasets.
Adopting the new NEP 2020 B.Pharm syllabus?
Pre-book new-syllabus B.Pharm sets at institutional pricing.