Drug Metabolism: Latest Advances and Prospects
A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Pharmacology and Drug Metabolism".
Deadline for manuscript submissions: 30 December 2024 | Viewed by 97
Special Issue Editors
2. Research Center for Toxicogenomics and Human Health (ToxOmics), Universidade NOVA de Lisboa, 1099-085 Lisboa, Portugal
Interests: pharmaco/toxico-kinetics; pharmaco/toxico genomics; drug metabolism; cytochrome P450; adverse drug reactions (ADRs); drug-induced liver injury (DILI); cancer drug resistance; metabolic liver disease
2. ECTS, School of Health Sciences and Technologies, Universidade Lusófona, 1749-024 Lisboa, Portugal
Interests: genetics; clinical biochemistry; genotoxicology; mutagenicity; xenobiotic metabolism; cytochrome P450; in vitro models; pesticides
Special Issue Information
Dear Colleagues,
Drug metabolism, a pivotal process governing the fate of pharmaceutical compounds within the human body, has witnessed remarkable advancements and holds promising prospects in recent scientific exploration. Understanding drug metabolism pathways is crucial for predicting a drug's efficacy, safety, and potential interactions within biological systems.
In recent years, significant strides have been made in elucidating the intricate mechanisms governing drug metabolism. The integration of advanced technologies, such as high-resolution mass spectrometry, computational modeling, and omics approaches, has provided unprecedented insights into metabolic pathways, metabolite identification, and enzyme kinetics.
Moreover, the role of drug metabolism in personalized medicine has garnered substantial attention. The emergence of pharmacogenomics and the identification of genetic variants influencing drug-metabolizing enzymes have revolutionized drug development and patient care. Tailoring treatments based on individual metabolic profiles holds immense promise for optimizing drug efficacy, minimizing adverse reactions, and improving therapeutic outcomes.
The future of drug metabolism research is promising. Advances in artificial intelligence and machine learning algorithms are poised to revolutionize the predictive modeling of drug metabolism, enabling faster and more accurate predictions of metabolic pathways and metabolite profiles for new drug candidates.
Dr. Michel Kranendonk
Dr. Bernardo Brito Palma
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- xenobiotic metabolism
- drug-metabolizing enzymes
- pharmacokinetics/toxicokinetics
- pharmacody-namics/toxicodinamics
- biotransformation
- metabolomics
- drug clearance
- polymophisms
- metabolic profiling
- personalized medicine
- adverse drug reactions (ADRs)
- drug-induced liver injury (DILI)
