Machine Learning

Abstract The presented work investigates critical aspects of rational formulation design through machine learning (ML) methodology to identify essential patterns...

Abstract Nose-to-brain drug delivery via nasal sprays is severely limited by low olfactory deposition. In this study, we integrate machine...

Abstract Creating high-quality datasets for training machine learning models in specialized domains like pharmaceutical research is often constrained by the...

Abstract Since Pfizer developed the mRNA vaccine for COVID-19 by leveraging artificial intelligence (AI) for designing the vaccine, integrating AI...

Abstract Formulation development of protein biopharmaceuticals has become increasingly challenging due to new modalities and higher target drug substance concentrations....

Abstract The development of dry powder inhalers (DPIs) for pulmonary drug delivery is complex, requiring optimization of variable factors to...

Abstract The transition from traditional batch to continuous pharmaceutical manufacturing puts additional demands on the efficient process development and operation....

Abstract Amorphous solid dispersions (ASDs) represent a promising formulation strategy for improving the solubility and bioavailability of poorly water-soluble drugs,...

Abstract Ribbon splitting, a phenomenon that can occur during the roller compaction operation used in dry granulation processes, can lead...

Abstract Background/Objectives: The integration of machine learning (ML) and artificial intelligence (AI) has revolutionized the pharmaceutical industry by improving drug...