Simvastatin, sold under the brand name Zocor among others, is a statin, a type of lipid-lowering medication. It is used along with exercise, diet, and weight loss to decrease elevated lipid levels. It is also used to decrease the risk of heart problems in those at high risk. It is taken by mouth.
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Simvastatin topic overview
The analysis highlights History, Community, Culture and Applications as prominent areas in the source structure around Simvastatin.
Related topics
70
Source areas
8
Connected nodes
78
Extracted relationships
137
Concept neighborhoods
18
Bridge connections
78
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Overview · 13 topics
Interactions · 12 topics
Pharmacology · 12 topics
History · 11 topics
Society and culture · 9 topics
Adverse effects · 6 topics
Contraindications · 5 topics
Medical uses · 2 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
3D model (JSmol)
Interactive image
AHFS/Drugs.com
Monograph
ATC code
C10AA01 (WHO)
Bioavailability
5%
CAS Number
79902-63-9 Y
ChEBI
CHEBI:9150 Y
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How Simvastatin connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around Simvastatin shows recurring relationship patterns in the source. For example, Simvastatin → Australia, Austria, Berlin Pharmaceutical Industry Co, Bestatin, Brand, Co, Denan, France, Germany, India, Israel, Italy, Japan, Lipex, Liponorm, Lipovas, Lodales, Ltd, Merck, New Zealand Another extracted example is Simvastatin → Akira Endo, Aspergillus, Biochemist Jesse Huff, By, Carl Hoffman, Daiichi Sankyo, HMG-CoA, Hoffman, Huff, In, Japan, Karl Folkers, Max Planck Institute, Merck, MK-733, Penicillium, The, This, While. Use these groups to spot repeated connection types before inspecting the individual relationships.
Simvastatin
Top relations
related to Brand names· 38
Simvastatin → Australia, Austria, Berlin Pharmaceutical Industry Co, Bestatin, Brand, Co, Denan, France, Germany, India, Israel, Italy, Japan, Lipex, Liponorm, Lipovas, Lodales, Ltd, Merck, New Zealand
related to history· 19
Simvastatin → Akira Endo, Aspergillus, Biochemist Jesse Huff, By, Carl Hoffman, Daiichi Sankyo, HMG-CoA, Hoffman, Huff, In, Japan, Karl Folkers, Max Planck Institute, Merck, MK-733, Penicillium, The, This, While
related to Economics· 12
Simvastatin → Affordable Care Act, Co, Merck, Patient Protection, PPACA, Prior, Task Force, Under, United States, United States Preventive Services, US, USPSTF
related to Pharmacodynamics· 9
Simvastatin → All, HMG, HMG-CoA, However, LDL, LDL-cholesterol, PPAR-alpha, Statins, This
has effect· 8
Simvastatin → Cholestatic, Clinical Pharmacogenetics Implementation Consortium, Common, DNA, In, Serious, SNP, There
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 137 structured relationships around Simvastatin. Examples in this analysis include Simvastatin → 3D model (JSmol) → Interactive image and Simvastatin → AHFS/Drugs.com → Monograph. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Simvastatin
3D model (JSmol)
Interactive image
1.00
infobox
Simvastatin
AHFS/Drugs.com
Monograph
1.00
infobox
Simvastatin
ATC code
C10AA01 (WHO)
1.00
infobox
Simvastatin
Bioavailability
5%
1.00
infobox
Simvastatin
CAS Number
79902-63-9 Y
1.00
infobox
Simvastatin
ChEBI
CHEBI:9150 Y
1.00
infobox
Simvastatin
ChEMBL
ChEMBL1064 Y
1.00
infobox
Simvastatin
ChemSpider
49179 Y
1.00
infobox
Simvastatin
CompTox Dashboard (EPA)
DTXSID0023581
1.00
infobox
Simvastatin
DrugBank
DB00641 Y
1.00
infobox
Simvastatin
ECHA InfoCard
100.115.749
1.00
infobox
Simvastatin
Elimination half-life
2 hours for simvastatin and 1.9 hours for simvastatin acid
1.00
infobox
Simvastatin
Excretion
Kidney 13%, faecal 60%
1.00
infobox
Simvastatin
Formula
C25H38O5
1.00
infobox
Simvastatin
IUPHAR/BPS
2955
1.00
infobox
Simvastatin
KEGG
D00434 Y
1.00
infobox
Simvastatin
Legal status
AU: S4 (Prescription only)
1.00
infobox
Simvastatin
Legal status
UK: POM (Prescription only)
1.00
infobox
Simvastatin
Legal status
US: ℞-only
1.00
infobox
Simvastatin
Legal status
EU: Rx-only
1.00
infobox
Simvastatin
License data
US DailyMed: Simvastatin
1.00
infobox
Simvastatin
MedlinePlus
a692030
1.00
infobox
Simvastatin
Metabolism
Liver (CYP3A4)
1.00
infobox
Simvastatin
Molar mass
418.574 g·mol−1
1.00
infobox
Simvastatin
Pregnancy category
AU: D
1.00
infobox
Simvastatin
Pronunciation
/ˈsɪmvəstætɪn/ ⓘ
1.00
infobox
Simvastatin
Protein binding
95%
1.00
infobox
Simvastatin
PubChem CID
54454
1.00
infobox
Simvastatin
Routes of administration
By mouth
1.00
infobox
Simvastatin
Trade names
Zocor, other
1.00
infobox
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around Simvastatin bring nearby vocabulary together. In this analysis, examples include Heart, Including and Risk. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Simvastatin
Heart
Including
Risk
Drugs
Patients
Cardiovascular
Ldl
Disease
Citation
Also
Levels
Muscle
simvastatin
Heart
Including
Risk
Drugs
Patients
Cardiovascular
Ldl
Disease
Citation
Also
Levels
Muscle
heart problems
May
People
Used
Risk
Simvastatin
Ldl
Zocor
Cholesterol
Disease
Effects
Include
Dose
scandinavian simvastatin survival study
Heart
Including
Risk
Drugs
Patients
Cardiovascular
Ldl
Disease
Citation
Also
Levels
Muscle
elevated lipid levels
Side
Risk
Citation
Muscle
Needed
Effects
Simvastatin
Include
Ldl
Problems
Disease
Dose
muscle breakdown
Dose
Fda
Lower
Side
Evidence
Including
Liver
Drugs
Patients
Drug
Risk
Simvastatin
heart protection study
People
Risk
Simvastatin
Ldl
Zocor
Cholesterol
Disease
Effects
Include
Pregnancy
Problems
Events
adverse effects
Side
Include
Risk
Evidence
May
Liver
Levels
Muscle
Heart
Cholesterol
Simvastatin
Ldl
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For Simvastatin, one of the stronger structural bridges in this analysis connects Simvastatin with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Simvastatin
Nodes79
Edges78
Triples137
Avg. degree1.97
Density0.025316
Components1
Source & methodology
TTTA analyzes the structure around Simvastatin to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Community, Culture & Applications, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
