Clinical Pharmacokinetics

, Volume 52, Issue 9, pp 727–749 | Cite as

Ginkgo biloba Extracts: A Review of the Pharmacokinetics of the Active Ingredients

  • Christian Ude
  • Manfred Schubert-Zsilavecz
  • Mario WurglicsEmail author
Review Article


Ginkgo biloba is among the most favourite and best explored herbal drugs. Standardized extracts of Ginkgo biloba represent the only herbal alternative to synthetic antidementia drugs in the therapy of cognitive decline and Alzheimer’s diseases. The clinical efficiency of such standardized Ginkgo biloba extracts (GBE) is still controversial, but authors of numerous international clinical studies recommended the use of GBE in the described therapies.

Extracts of Ginkgo biloba are a mixture of substances with a wide variety of physical and chemical properties and activities. Numerous pharmacological investigations lead to the conclusion that the terpene trilactones (TTL) and the flavonoids of GBE are responsible for the main pharmacological effects of the extract in the therapy of cognitive decline. Therefore, the quality of GBE products must be oriented on a defined quantity of TTL and flavonoids. Furthermore, because of their toxic potential the amount of ginkgolic acid should be less than 5 ppm.

However, data on pharmacokinetics and bioavailability, especially related to the central nervous system (CNS), which is the target tissue, are relatively rare. A few investigations characterize the TTL and flavonoids of Ginkgo biloba pharmacokinetically in plasma and in the brain. Recent investigations show that significant levels of TTL and Ginkgo biloba flavonoids cross the blood–brain barrier and enter the CNS of rats after oral application of GBE. Knowledge about the pharmacokinetic behaviour of these substances is necessary to discuss the pharmacological results on a more realistic basis.


Flavonoid Quercetin Kaempferol Isorhamnetin Ginkgo Biloba 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors wish to thank Dr. Brigitte Held for editorial support and Astrid Kaiser for technical assistance.


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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Christian Ude
    • 1
  • Manfred Schubert-Zsilavecz
    • 1
  • Mario Wurglics
    • 1
    Email author
  1. 1.Institute of Pharmaceutical Chemistry/ZAFES, Goethe UniversityFrankfurt am MainGermany

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