Drug-drug interactions (DDIs) represent a substantial challenge in contemporary
pharmacotherapy, especially given polypharmacy, the effects of foods, and the modification
of host-microbiota systems on drugs. Although useful, existing DDI identification techniques have
many constraints related to cost, time, and scalability.
A literature review was conducted using PubMed, Scopus, Web of Science, and IEEE
Xplore, focusing on machine learning techniques, deep neural architectures, and network-based
models that integrate multi-omic, pharmacological, and clinical data.
By combining chemical, biological, and clinical data into scalable computer platforms,
demonstrated that artificial intelligence techniques, such as machine learning (ML) and deep learning
(DL), are changing the prediction of DDI. Some notable studies, such as DeepDDI, TP-DDI, and
Decagon, use approaches that successfully capture the intricate PK-PD interactions of pharmaceuticals.
On the other hand, food-drug interactions and microbiome-mediated drug interactions were also
successfully predicted using multimodal and graph-based models, respectively.
Critical issues, such as insufficient data, class imbalance, and model interpretability,
must be addressed through explainable AI and multimodal fusion techniques.
The purpose of this article is to present an overview of how artificial intelligence might
serve not only as a tool but also as a strategic solution for safe prescribing and tailored pharmacotherapy,
hence opening up new avenues for the field of drug safety science.
D. Tripathi, Ankita Wal, Vivek Kumar Gupta et al.· Current Bioinformatics· 0 citations
G-protein Coupled Receptors (GPCRs) are the largest family of classical membrane receptors and the most important class of pharmacological targets, playing roles in many physiological and pathological processes. Targeting a GPCR is a challenging approach because traditional drugs and similar therapeutics have a number of significant drawbacks, including low aqueous solubility, low bioavailability, rapid metabolic degradation, low tissue specificity, and off-target effects. This review discusses different nanocarrier-based drug delivery strategies to improve the therapeutic efficacy, targeting efficiency, and translational potential of drugs acting on GPCRs.
A systematic review of peer-reviewed published articles to explore the latest developments in GPCR biology, GPCR signalling pathways, and drug delivery using nanocarriers was conducted. Major nanoplatforms, such as liposomes, polymeric nanoparticles, dendrimers, and hybrid nanosystems, were studied based on their design principles, targeting strategies, and therapeutic applications. Preclinical, mechanistic, and early translational studies that were relevant were included.
Nanocarrier-based systems have multiple advantages in GPCR-targeted therapy, such as enhanced drug stability, increased bioavailability, controlled release, and reduced systemic toxicity. Functionalization of nanocarriers may improve delivery in a receptor-specific manner and facilitate transport across biological barriers, such as the blood-brain barrier. These systems also support multiple functions, including co-delivery of therapeutics, nucleic acids, and diagnostic components. Promising applications have been identified in oncology, neurological disorders, cardiovascular diseases, and inflammatory conditions. However, there are still challenges in translation, particularly with regard to immunogenicity, long-term safety, manufacturing scalability, and regulatory approval.
The combined use of GPCR pharmacology with state-of-the-art nanocarrier engineering is a promising approach to improve receptor selectivity and therapeutic precision. Novel instruments, such as artificial intelligence, molecular modelling, and systems pharmacology, may further aid the optimisation of ligand selection, carrier design, and personalised therapeutic development.
Nanocarrier-mediated drug delivery is a sensible and highly promising strategy to address the limitations of conventional GPCR therapeutics. In addition, developments in targeted nanomedicine may accelerate the development of accurate and individualised GPCR-targeted therapeutic treatments.
Pranay Wal, Jyotsana Dwivedi, K. Khairunnisa et al.· Current Drug Targets· 0 citations
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