https://www.saapjournals.org/index.php/baddt <p>Bulletin of Advanced Drug Delivery and Therapeutics</p> South Asian Academic Publications en-US Bulletin of Advanced Drug Delivery and Therapeutics 3139-776X https://www.saapjournals.org/index.php/baddt/article/view/965 <p>Self-emulsifying drug delivery systems (SEDDS) are lipid-based formulations generally containing oil, surfactant and co-surfactant or a cosolvent. Dilution results in formation of fine dispersions, enabling solubilization of lipophilic drugs and/or improving their dissolution and/or absorption. While formulation of SEDDS remains largely empirical and requires extensive experimentation, artificial intelligence (AI) can be leveraged for predictive excipient selection, design of critical quality attribute (CQA) space, multi-objective optimization, precipitation risk ranking and active design of experiments. This review proposes an AI-integrated SEDDS loop encompassing molecular descriptors, excipients, formulation design, gastrointestinal performance and pharmacokinetic (PK) outcomes. Bayesian optimization, explainable AI, supersaturable and solid SEDDS, digital twin and self-driving lab concepts are also discussed. The overall perspective is that AI should complement traditional pharmaceutical experimentation and that standardized dataset creation and external validation are critical enablers.</p> Govinda Rao Y Copyright (c) 2026 2026-09-30 2026-09-30 1 11 10.37022/baddt.v1i2.965 https://www.saapjournals.org/index.php/baddt/article/view/966 <p>Clinical pharmacogenomics (PGx) is an emerging component of precision medicine that examines how inherited genetic variation influences an individual's response to medicines. Genetic differences affecting drug-metabolizing enzymes, transporters, receptors, immune pathways and therapeutic targets can contribute to interindividual variability in drug efficacy, toxicity and pharmacokinetics. Integration of pharmacogenomic information into clinical practice can therefore support selection of appropriate medicines, individualized dosing and prevention of avoidable adverse drug reactions. Important gene–drug associations include CYP2C19–clopidogrel, CYP2D6–codeine and antidepressants, CYP2C9/VKORC1–warfarin, TPMT/NUDT15–thiopurines, DPYD–fluoropyrimidines and HLA-B*57:01–abacavir. Clinical implementation is supported by evidence-based resources and guidelines developed by organizations such as the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Dutch Pharmacogenetics Working Group (DPWG), PharmGKB and regulatory agencies. However, challenges involving test accessibility, cost, interpretation, healthcare professional education, electronic health record integration, reimbursement, ethical considerations and population diversity continue to limit widespread implementation. Recent developments in pre-emptive panel testing, clinical decision-support systems and standardized genotype-to-phenotype interpretation are facilitating broader integration of PGx into healthcare. This review discusses the principles, clinical applications, implementation strategies, benefits and limitations of clinical pharmacogenomics and highlights its potential role in individualized and safer pharmacotherapy.</p> Kalyani R Copyright (c) 2026 2026-09-30 2026-09-30 12 17 10.37022/baddt.v1i2.966