Eric H. Rosenn

Lipid nanoparticle (LNP) delivery constructs provide a precise and targeted therapeutic platform for nucleic-acid and subunit vaccines. By shielding fragile antigens and genetic cargo from premature degradation, these constructs help vaccines overcome the physiological barriers that separate an injection site from its intracellular target, increasing specificity, potency, and the precision of controlled release. This capability has broadened the range of immunomodulatory targets in the fight against infectious disease and has opened the door to vaccines that treat tumors and cancer. Increasingly, artificial intelligence (AI) and machine learning (ML) are being applied to predict the LNP formulations that maximize mRNA-vaccine efficacy, and the same computational strategies are now being extended across diverse vaccine modalities. By approximating in vivo pharmacokinetics and pharmacodynamics, in silico methods promote rational, data-driven design that is reshaping the drug-development pipeline. In this Review we summarize current literature on the optimization of LNP delivery constructs for vaccine therapeutics using ML, survey the rapid clinical translation of LNP-mRNA technology since 2021, and discuss the limitations and predictive capabilities of computer-simulated experimental models.

1. The human microbiota refers to the collection of microorganisms, including bacteria, viruses, fungi, and archaea, inhabiting distinct niches such as the gut, oral cavity, skin, and genitourinary...

Metabolomics has emerged as a powerful discipline for capturing dynamic biochemical states and linking molecular processes to human health, disease, and biotechnology. This chapter explores the evolution of metabolomics from early profiling efforts to its current integration with advanced analytical platforms, computational biology, and precision medicine. We highlight how targeted and untargeted metabolomic strategies have advanced biomarker discovery, clarified disease mechanisms, and informed the development of personalized therapies in cancer, cardiovascular disease, diabetes, and other conditions. The role of pharmacometabolomics in refining drug response predictions and guiding therapeutic decisions is also examined. Beyond biomedicine, metabolomics drives innovation in biotechnology, synthetic biology, and bio-based production, while emerging tools such as single-cell metabolomics and machine learning continue to expand its scope. By directly tracing metabolic fluxes and engineering new pathways, metabolomics is becoming a practical engine for designing microbes, optimizing bioprocesses, and accelerating drug discovery.

Intracellular bacterial pathogens have evolved sophisticated metabolic strategies to persist and replicate within the hostile intracellular environments of their hosts. By leveraging their metabolic plasticity, these pathogens dynamically modulate host metabolic processes in response to immunological, environmental, and pharmacological stressors. This review examines the diverse metabolic adaptations employed by intracellular pathogens, including nutrient acquisition, modulation of host metabolism, and stress-induced metabolic shifts that contribute to persistence and virulence. Emphasis is placed on how distinct intracellular niches- such as vacuoles and the cytosol- shape pathogen metabolism, and how bipartite metabolic strategies enable pathogens to balance energy production with biosynthetic demands. Species-specific adaptations in representative pathogens, including Listeria monocytogenes , Legionella pneumophila , Shigella flexneri , and Chlamydia trachomatis , are analyzed, with a focus on mechanisms of metabolic reprogramming (the alteration of cellular metabolic pathways in response to environmental cues, such as infection or stress, which allows the pathogen to adapt its metabolic state to support survival, replication, and virulence within the host), stress tolerance (refers to a pathogen’s ability to survive and function under harsh environmental conditions, such as oxidative stress, nutrient scarcity, and antimicrobial exposure), and lifecycle transitions (refer to the changes in a pathogen’s developmental or replication stages, such as switching from active growth to a dormant or persistent state during infection). Finally, the review considers how these metabolic strategies intersect with antimicrobial resistance and highlights the potential of targeting host-pathogen metabolic interactions for the development of novel interventions, including host-directed therapies (HDTs).