Evidence map›Paper›PMID 26579403›Full record

ReviewActa pharmaceutica Sinica. B2014

Pharmacokinetic aspects and in vitro-in vivo correlation potential for lipid-based formulations.

Sivacharan Kollipara, Rajesh Kumar Gandhi

Abstract readReview
In one paragraph

Review in Acta pharmaceutica Sinica. B, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Bioavailability by design - Vitamin DNanomedicine : nanotechnology, biology, and medicine · 2022
    Article
  13. Article
  14. Article
  15. Review
  16. Acta pharmaceutica Sinica. B · 2021
    Review
  17. Article
  18. Article
  19. Review
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Sivacharan KolliparaFormulations Department, Pharmaceutical & Analytical Development, Technical R&D, Novartis Healthcare Pvt. Ltd., Hyderabad 500078, Andhra Pradesh, India.
Rajesh Kumar GandhiFormulations Department, Pharmaceutical & Analytical Development, Technical R&D, Novartis Healthcare Pvt. Ltd., Hyderabad 500078, Andhra Pradesh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lipid-based formulations have been an attractive choice among novel drug delivery systems for enhancing the solubility and bioavailability of poorly soluble drugs due to their ability to keep the drug in solubilized state in the gastrointestinal tract. These formulations offer multiple advantages such as reduction in food effect and inter-individual variability, ease of preparation, and the possibility of manufacturing using common excipients available in the market. Despite these advantages, very few products are available in the present market, perhaps due to limited knowledge in the in vitro tests (for prediction of in vivo fate) and lack of understanding of the mechanisms behind pharmacokinetic and biopharmaceutical aspects of lipid formulations after oral administration. The current review aims to provide a detailed understanding of the in vivo processing steps involved after oral administration of lipid formulations, their pharmacokinetic aspects and in vitro in vivo correlation (IVIVC) perspectives. Various pharmacokinetic and biopharmaceutical aspects such as formulation dispersion and lipid digestion, bioavailability enhancement mechanisms, impact of excipients on efflux transporters, and lymphatic transport are discussed with examples. In addition, various IVIVC approaches towards predicting in vivo data from in vitro dispersion/precipitation, in vitro lipolysis and ex vivo permeation studies are also discussed in detail with help of case studies.

Indexed as

ADME, absorption/distribution/metabolism/eliminationAUC, area under the curveBCS, biopharmaceutics classification systemBDDCS, biopharmaceutics drug disposition classification systemCACO, human epithelial colorectal adenocarcinoma cellsCmax, maximum plasma concentrationCMC, critical micellar concentrationCYP, cytochromeDDS, drug delivery systemsEfflux transportersFaSSGF, fasted-state simulated gastric fluidFaSSIF, fasted-state simulated intestinal fluidFeSSIF, fed-state simulated intestinal fluidFood effectGIT, gastrointestinal tractIVIVCIVIVC, in vitro in vivo correlationLCT, long chain triglycerideLFCS, lipid formulation classification systemLipolysislog P, n-octanol/water partition coefficientLymphatic deliveryMCT, medium chain triglycerideMDCK, Madin–Darby canine kidney cellsNCE, new chemical entityP-app, apparent permeabilityP-gp, permeability glycoproteinPharmacokineticsSCT, short chain triglycerideSEDDS, self-emulsifying drug delivery systemSIF, simulated intestinal fluidSMEDDS, self-microemulsifying drug delivery systemSNEDDS, self-nanoemulsifying drug delivery systemVit E, vitamin E

Identifiers

PMID26579403
PMCPMC4629105

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.