ReviewPharmacological research2015
Molecular mechanism matters: Benefits of mechanistic computational models for drug development.
Review in Pharmacological research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed.
- SMART Planning of Early-Stage Health Economic Decision Models for Mechanism-Based Precision Treatments in Rare Cancers: An Application and Tool Update.PharmacoEconomics · 2026Review
- Leveraging quantum chemical properties in transfer learning for predicting blood-brain barrier permeability of drugs.Drug delivery and translational research · 2026Article
- Structural tuning of diclofenac for enhanced medicinal efficacy and reduced adverse effects: an integrating computational validation.RSC advances · 2026Article
- Mechanistic model of phase-transitioning therapeutics injected into poroelastic tissue for improved targeting of superficial tumors.Scientific reports · 2026Article
- Mechanistic model of phase-transitioning therapeutics injected into poroelastic tissue for improved targeting of superficial tumors.Research square · 2025Article
- V-Cornea: A computational model of corneal epithelium homeostasis, injury, and recovery.PLoS computational biology · 2025Article
- Mechanistic computational modeling of sFLT1 secretion dynamics.PLoS computational biology · 2025Article
- Semi-mechanistic modeling of resistance development to β-lactam and β-lactamase-inhibitor combinations.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Review
- Modelling the effects of 4-factor prothrombin complex concentrate for the management of factor Xa-associated bleeding.PloS one · 2024Article
- Development of and insights from systems pharmacology models of antibody-drug conjugates.CPT: pharmacometrics & systems pharmacology · 2022Review
- Recent Advances Regarding the Molecular Mechanisms of Triterpenic Acids: A Review (Part I).International journal of molecular sciences · 2022Review
- Impact of sex and pathophysiology on optimal drug choice in hypertensive rats: quantitative insights for precision medicine.iScience · 2021Article
- A Review on Applications of Computational Methods in Drug Screening and Design.Molecules (Basel, Switzerland) · 2020Review
- Discovery of Novel Multi-target Inhibitor of angiotensin type 1 receptor and neprilysin inhibitors from Traditional Chinese Medicine.Scientific reports · 2019Article
- Tumor and endothelial cells collaborate via transcellular receptor complexes.The Journal of pathology · 2019Article
- Considerations for anFrontiers in pharmacology · 2019Review
- Mechanistic Models of Cellular Signaling, Cytokine Crosstalk, and Cell-Cell Communication in Immunology.Frontiers in immunology · 2019Article
- Development of a Novel 3D Tumor-tissue Invasion Model for High-throughput, High-content Phenotypic Drug Screening.Scientific reports · 2018Article
- The Spectrum of Mechanism-Oriented Models and Methods for Explanations of Biological Phenomena.Processes (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Making drug development a more efficient and cost-effective process will have a transformative effect on human health. A key, yet underutilized, tool to aid in this transformation is mechanistic computational modeling. By incorporating decades of hard-won prior knowledge of molecular interactions, cellular signaling, and cellular behavior, mechanistic models can achieve a level of predictiveness that is not feasible using solely empirical characterization of drug pharmacodynamics. These models can integrate diverse types of data from cell culture and animal experiments, including high-throughput systems biology experiments, and translate the results into the context of human disease. This provides a framework for identification of new drug targets, measurable biomarkers for drug action in target tissues, and patient populations for which a drug is likely to be effective or ineffective. Additionally, mechanistic models are valuable in virtual screening of new therapeutic strategies, such as gene or cell therapy and tissue regeneration, identifying the key requirements for these approaches to succeed in a heterogeneous patient population. These capabilities, which are distinct from and complementary to those of existing drug development strategies, demonstrate the opportunity to improve success rates in the drug development pipeline through the use of mechanistic computational models.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.