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Special Issue "In Silico Pharmacology for Evidence-Based and Precision Medicine"
A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Clinical Pharmaceutics".
Deadline for manuscript submissions: closed (20 January 2023) | Viewed by 19047
Special Issue Editor
Interests: pharmacokinetics & pharmacodynamics; PBPK modeling and simulation; drug interactions; computational medicine; in silico pharmacology; pharmacometrics; computational oncology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Personalized/precision medicine (PM), initiating from clinical and molecular pharmacology, introduces a new era in healthcare that aims to identify and predict the optimum treatments for a patient or a cohort. Evidence-based medicine (EBM) integrates information from basic in vivo, observational studies and clinical trials up to meta-analysis data for clinical consideration. Hence, it can be stated that EBM often see the forest (population averages) but misses the trees (individual patients), whereas the utilization of PM may not see the forest for the trees.
State-of-the-art tools for modeling and simulation (M&S) in pharmacology try to extrapolate knowledge gained through experimental procedures with either top-down or bottom-up approaches. M&S often try to “connect the dots” and reveal the bigger picture, the “population/forest”, considering what kind of “individuals/trees” are in there. These approaches have been providing state-of-the-art tools in research and development (R&D) for novel, more efficient and effective molecules, with improved safety profiles and the chance to proceed in clinical trials. In addition, they contribute to the R&D of novel drug-delivery systems and finally assist regarding drug repurposing.
This Special Issue invites research and review articles on pharmacological approaches incorporating M&S to promote EBM and PM knowledge for potential clinical extrapolation. Articles utilizing experimental or clinical data through M&S biomedical tools for disease progression dynamics, machine learning and relevant bioengineering approaches for drug response prediction (including drug interactions, adverse drug reactions and drug repurposing), PK/PD models for special population groups or novel drug delivery systems extrapolating in vitro/in vivo data to the clinical level are some of the (but not the only) research areas that this Special Issue aims to include.
Dr. Marios Spanakis
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. Pharmaceutics 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 2600 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.
- personalized/precision medicine
- evidence-based medicine approaches for therapy optimization
- physiologically based PK/PD models
- drug targeting and response prediction
- multiscale M&S for disease dynamics
- population pharmacokinetics/pharmacodynamics
- in silico clinical trials
- big data and systems pharmacology
- M&S in clinical settings
- translational and biomedical informatics in precision medicine