ReviewPharmaceutics2023
A Review of Quantitative Systems Pharmacology Models of the Coagulation Cascade: Opportunities for Improved Usability.
Review in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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
8 citing papers in PubMed, 11 citations in OpenAlex.
- AI and network biology for rational polypharmacology in signaling drug design: a review.NPJ precision oncology · 2026Review
- Computational modeling of pro-inflammatory cytokine-enhanced blood coagulation.bioRxiv : the preprint server for biology · 2026Article
- Computational Modeling of Pro-inflammatory Cytokine-Enhanced Blood Coagulation.Computational and structural biotechnology journal · 2026Article
- Predictive AI in Clinical Pharmacology: A Call to Action to Develop Robust Benchmarking Practices.CPT: pharmacometrics & systems pharmacology · 2026Article
- Mechanistic modeling of cell viability assays with in silico lineage tracing.PLoS computational biology · 2025Article
- The Role of Cross-Institutional and Interdisciplinary Collaboration in Defining and Executing a Quantitative Systems Pharmacology Strategy.Handbook of experimental pharmacology · 2025Review
- A physiologically-based pharmacokinetic/pharmacodynamic modeling approach for drug-drug-gene interaction evaluation of S-warfarin with fluconazole.CPT: pharmacometrics & systems pharmacology · 2024Article
- Critical evaluation of kinetic schemes for coagulation.PloS one · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the numerous therapeutic options to treat bleeding or thrombosis, a comprehensive quantitative mechanistic understanding of the effects of these and potential novel therapies is lacking. Recently, the quality of quantitative systems pharmacology (QSP) models of the coagulation cascade has improved, simulating the interactions between proteases, cofactors, regulators, fibrin, and therapeutic responses under different clinical scenarios. We aim to review the literature on QSP models to assess the unique capabilities and reusability of these models. We systematically searched the literature and BioModels database reviewing systems biology (SB) and QSP models. The purpose and scope of most of these models are redundant with only two SB models serving as the basis for QSP models. Primarily three QSP models have a comprehensive scope and are systematically linked between SB and more recent QSP models. The biological scope of recent QSP models has expanded to enable simulations of previously unexplainable clotting events and the drug effects for treating bleeding or thrombosis. Overall, the field of coagulation appears to suffer from unclear connections between models and irreproducible code as previously reported. The reusability of future QSP models can improve by adopting model equations from validated QSP models, clearly documenting the purpose and modifications, and sharing reproducible code. The capabilities of future QSP models can improve from more rigorous validation by capturing a broader range of responses to therapies from individual patient measurements and integrating blood flow and platelet dynamics to closely represent in vivo bleeding or thrombosis risk.
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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.