Evidence mapPaperPMID 41952026Full record

ReviewAAPS PharmSciTech2026

Functional Reclassification of Lipid-Based Drug Delivery Systems and Advances in Formulation Strategies and Manufacturing Challenges.

Pranal Chhetri

Abstract readReview
PubMed Publisher
In one paragraph

Review in AAPS PharmSciTech, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

1 author.

Pranal ChhetriAmity Institute of Pharmacy, Amity University, Raipur, Chhattisgarh, India. pranalchhetri1@gmail.com.ORCID http://orcid.org/0009-0009-7994-770X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lipid-based drug delivery systems have progressed from a simple empirical solubilization tool towards a highly precise engineered platform, capable of delivering small drug molecules, biologics and nucleic acids. Despite proven achievements reflected through the success of lipid nanoparticles-based mRNA vaccine and siRNA medicines, wider clinical translation across complex diseases still remains limited by a fragmented classification system, inaccurate IVIVC, scale-up complexity and continuously evolving and highly demanding regulatory frameworks. This review re-evaluates lipid systems by providing a functional reclassification system that directly links formulation design with biological performance and scale-up science. Instead of categorising based on simple lipid composition and structural features, lipid-based drug delivery systems are reclassified based on their primary functional roles inside the biological system. Further, this review assesses methods to strengthen IVIVC for Lipid-based drug delivery systems and how quality-by-design and emerging quality-by-digital-design approaches supported by mechanistic modelling, in-process analytical tools and machine learning can be utilised to produce a smart and robust next generation lipid carrier. Lastly, this review also highlights persistent regulatory and transitional challenges, pointing out major gaps related to standardisation, comparability and late-stage failure.

Indexed as

Drug Delivery SystemsLipidsChemistry, PharmaceuticalDrug CarriersDrug CompoundingHumansNanoparticlesDrug CarriersLipidsCQAsIVIVClipid-based drug delivery systemsLNPsQbD

Identifiers

What Socratic holds

Textmetadata
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 Socratic graph.