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Special Issue "In Silico Drug Testing and Optimization, Coupling Physical-Based Modeling and Machine Learning"
A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Pharmacokinetics and Pharmacodynamics".
Deadline for manuscript submissions: 31 July 2023 | Viewed by 6938
Special Issue Editors
2. BIOIRC, Bioengineering Research and Development Center, 34000 Kragujevac, Serbia
Interests: computational modeling; biomechanics; biomedical engineering; software engineering; machine learning; cardiovascular and respiratory disease; drug testing and optimization; in silico clinical trials
Interests: organic synthesis; antioxidative activity; coumarin derivatives; molecular modelling; transition metal complexes; DFT
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
In silico numerical simulations may provide additional information regarding the mechanisms guiding drug testing and optimization. The aim of this Special Issue is to use physical-based modeling methods such as continuum computational fluid dynamics (CFD), computational solid dynamics (CSD), discrete molecular dynamics (MD), dissipative particle dynamics (DPD), discrete phase modelling (DPM) and physiologically based pharmacokinetic (PBPK) coupled with machine learning methods to better describe drug transfer and distribution inside organs. The design of new prospective drugs, as well as carriers for their successful delivery, will be welcomed. It focuses on cardiovascular and lung biomechanics but is not limited to other organs. A comprehensive list of patient-specific features such as genetic, biological, pharmacologic, clinical, imaging and cellular aspects can be taken into account. The optimization and testing of medical devices and drug treatment strategies with the purpose of maximizing positive therapeutic outcomes should be considered. The aim is to avoid adverse effects, drug interactions, prevent sudden patient death and shorten the time between drug treatment commencement and the achievement of desired results. In silico methods could open a new avenue for medical device and drug testing, reducing the use of real preclinical and clinical trials.
Prof. Dr. Nenad D. Filipović
Prof. Dr. Zoran Markovic
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.
- in silico methods
- continuum-based modeling
- discrete-based modeling
- machine learning
- cardiovascular and respiratory biomechanics
- drug testing and optimization