ReviewPharmaceutics2023
The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery.
Review in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
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- Synthesis of carbazole and naphthyl-pyrimidine-based inhibitors of Xanthomonas for tomato bacterial spot management.Molecular diversity · 2026Article
- Integrative Medicine for Liver Fibrosis: Bioactive Constituents and Therapeutic Potential of Scutellaria baicalensis.Chinese journal of integrative medicine · 2026Review
- Preliminary Assessment of p-Anisidinium-Based Ionic Solids as Potential DNA Staining Agents: DFT and Molecular Docking Studies.Journal of fluorescence · 2026Article
- Research Progress on Novel Lead Compounds for Central Nervous System Diseases.Pharmaceuticals (Basel, Switzerland) · 2026Review
- When Does Machine Learning Add Value over Theory? Predicting API Solubility in Binary Mixtures with COSMO-RS and DOOIT2 Across Diverse and Homogeneous Systems.Molecules (Basel, Switzerland) · 2026Article
- Visceral Leishmaniasis: Integrated In Silico Screening of Djiboutian Medicinal Plant Phytoconstituents TargetingPharmaceuticals (Basel, Switzerland) · 2026Article
- Application of New Approach Methodologies to Improve Oral Biopharmaceutic Assessments.Pharmaceutics · 2026Review
- Integrated QSAR, Molecular Docking, ADMET Profiling, and Antioxidant Evaluation of Substituted Chromone and Aryloxyalkanoic Acid Derivatives as Potential CysLTPharmaceuticals (Basel, Switzerland) · 2026Article
- Integration of Machine Learning With PBPK and QSAR Modeling Approaches to Facilitate Drug Discovery and Development.CPT: pharmacometrics & systems pharmacology · 2026Review
- Chrysin and Luteolin from Moroccan Propolis to Prevent Aggressive Periodontitis Caused byPharmaceuticals (Basel, Switzerland) · 2026Article
- Design, synthesis, biological evaluation, andRSC advances · 2026Article
- Eco-friendly synthesis of an antimicrobial polymer (1,4-bis(methacryloyl)piperazine) via maghnite catalysis:Frontiers in chemistry · 2026Article
- Decoding the Bioactivity of Prunus armeniaca L. Essential Oil: Cheminformatics-Supported Exploration of Its Antioxidant and Antibacterial Potential.Chemistry & biodiversity · 2026Article
- Identification of Potential Dual HDAC6 and HSP90 Inhibitors for the Treatment of Cancer using Molecular Docking, Molecular Dynamics and MM/PBSA Studies: A ComprehensiveMedicinal chemistry (Shariqah (United Arab Emirates)) · 2026Article
- Discovery of Polyphenolic Compounds fromCurrent computer-aided drug design · 2026Article
- In silico-driven protocol for hit-to-lead optimization: a case study on PDE9A inhibitors.Journal of computer-aided molecular design · 2025Article
- New Quinazolin-4(3Molecules (Basel, Switzerland) · 2025Article
- Drug Design and Delivery for Intracellular Bacteria: Emerging Paradigms.Drug development research · 2025Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Drug discovery and development are aimed at identifying new chemical molecular entities (NCEs) with desirable pharmacokinetic profiles for high therapeutic efficacy. The plasma concentrations of NCEs are a biomarker of their efficacy and are governed by pharmacokinetic processes such as absorption, distribution, metabolism, and excretion (ADME). Poor ADME properties of NCEs are a major cause of attrition in drug development. ADME screening is used to identify and optimize lead compounds in the drug discovery process. Computational models predicting ADME properties have been developed with evolving model-building technologies from a simplified relationship between ADME endpoints and physicochemical properties to machine learning, including support vector machines, random forests, and convolution neural networks. Recently, in the field of in silico ADME research, there has been a shift toward evaluating the in vivo parameters or plasma concentrations of NCEs instead of using predictive results to guide chemical structure design. Another research hotspot is the establishment of a computational prediction platform to strengthen academic drug discovery. Bioinformatics projects have produced a series of in silico ADME models using free software and open-access databases. In this review, we introduce prediction models for various ADME parameters and discuss the currently available academic drug discovery platforms.
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