Evidence map›Paper›PMID 41737296›Full record

ArticleRSC pharmaceutics2026

QbD product development: rapid optimization and scale-up of PBAE-based siRNA delivery

Adrian P E Kromer, Laetitia J M Eller, David C Jürgens, Olivia M Merkel

Abstract read
In one paragraph

Article in RSC pharmaceutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Adrian P E KromerDepartment of Pharmacy, Ludwig-Maximilians-Universität Munich Butenandtstrasse 5-13 Haus B 81377 Munich Germany.
Laetitia J M EllerDepartment of Pharmacy, Ludwig-Maximilians-Universität Munich Butenandtstrasse 5-13 Haus B 81377 Munich Germany.
David C JürgensDepartment of Pharmacy, Ludwig-Maximilians-Universität Munich Butenandtstrasse 5-13 Haus B 81377 Munich Germany.
Olivia M MerkelDepartment of Pharmacy, Ludwig-Maximilians-Universität Munich Butenandtstrasse 5-13 Haus B 81377 Munich Germany.ORCID https://orcid.org/0000-0002-4151-3916

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Poly(β-amino ester) (PBAE)-based nanoparticles have emerged as promising carriers for RNA delivery, yet clear design rules linking formulation parameters to performance are still lacking. In this study, a Quality by Design (QbD)-guided and Design of Experiments (DoE)-driven approach was combined with high-throughput microfluidics to rapidly identify formulations with favorable physicochemical properties and consistent critical quality attributes (CQAs). Response Surface Modeling revealed that high total flow rates (TFR ≥ 10), nitrogen to phosphorus (N/P) ratios ≥10, and a Flow Rate Ratio (FRR) of 1 : 3 (buffer : ethanol) led to the formation of smaller, more stable particles. Among the polymers tested, a polymer candidate with a balanced composition of hydrophobic and hydrophilic side chains demonstrated optimal intraparticle stability and gene silencing performance. Notably, transfection efficiency depended strongly on formulation parameters beyond polymer type and N/P ratio, with flow rate ratio emerging as a key driver of gene knockdown kinetics. The lead formulation achieved ∼95% gene knockdown even after two weeks of storage at 4 °C. Scale-up production of the lead candidate confirmed the transferability of optimized Critical Process Parameters (CPPs) and preserved CQA profiles, validating the robustness of the design space. This study establishes a robust and scalable QbD-guided workflow for the development of microfluidically manufactured siRNA nanoparticles, enabling rapid optimization, reliable scale-up, and clinically relevant performance.

Identifiers

PMID41737296
PMCPMC12926864

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Registered trials

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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.