Flexibility in Drug Product Development: A Perspective

Kapoor, Yash; Meyer, Robert; Ferguson, Heidi; Skomski, Daniel; Daublain, Pierre; Troup, Gregory M.; Dalton, Chad; Ramasamy, Manoharan; Templeton, Allen C.

doi:10.1021/acs.molpharmaceut.1c00210

Cited by 6 publications

(2 citation statements)

References 33 publications

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“…Here, we investigated local modeling to automatically identify similar samples within the training set and then establish a fit-for-purpose model to quantify the unloaded cargo concentration and loading capacity in LNP formulations. Recently, other spectroscopy-based modeling approaches have also been investigated for characterizations of LNP systems; for example, a Raman microscopy equipped with PLS analysis showed great potential to characterize LNP compositions . Compared to previous experimental and modeling strategies, our LWR modeling approach may further spare the efforts for multivariate analyses tailored to cargo and lipid species, thereby simplifying the analytical process and better serving the HTS needs.…”

Section: Resultsmentioning

confidence: 99%

Spectroscopy-Based Local Modeling Method for High-Throughput Quantification of Nucleic Acid Loading in Lipid Nanoparticles

Fan¹,

Shi²,

Ma³

et al. 2022

Anal. Chem.

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Lipid nanoparticles (LNPs) are the most widely investigated delivery systems for nucleic acid-based therapeutics and vaccines. Loading efficiency of nucleic acids may vary with formulation conditions, and it is considered one of the critical quality attributes of LNP products. Current analytical methods for quantification of cargo loading in LNPs often require external standard preparations and preseparation of unloaded nucleic acids from LNPs; therefore, they are subject to tedious and lengthy procedures, LNP stability, and unpredictable recovery rates of the separated analytes. Here, we developed a modeling approach, which was based on locally weighted regression (LWR) of ultraviolet (UV) spectra of unpurified samples, to quantify the loading of nucleic acid cargos in LNPs in-situ. We trained the model to automatically tune the training library space according to the spectral features of a query sample so as to robustly predict the nucleic acid cargo concentration and rank loading capacity with similar performance as the more complicated experimental approaches. Furthermore, we successfully applied the model to a wide range of nucleic acid cargo species, including antisense oligonucleotides, single-guided RNA, and messenger RNA, in varied lipid matrices. The LWR modeling approach significantly saved analytical time and efforts by facile UV scans of 96-well sample plates within a few minutes and with minimal sample preprocessing. Our proof-of-concept study presented the very first data mining and modeling strategy to quantify nucleic acid loading in LNPs and is expected to better serve high-throughput screening workflows, thereby facilitates early-stage optimization and development of LNP formulations.

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Section: Resultsmentioning

confidence: 99%

Spectroscopy-Based Local Modeling Method for High-Throughput Quantification of Nucleic Acid Loading in Lipid Nanoparticles

Fan¹,

Shi²,

Ma³

et al. 2022

Anal. Chem.

View full text Add to dashboard Cite

show abstract

“…Combinations of these ∼160 approved drugs and ∼350 drug‐like basic molecules with ∼500 approved carboxylic acid drugs in a matrix fashion would provide a huge pool of starting point cocrystals that contain a relatively small number of heterosynthons that have already been optimized for enhanced bioavailability. Two recent papers, one on a pyrimidine drug inhibitor [45] and another on drug product development, [46] as well as the US‐FDA approval of drug–drug cocrystal Seglentis [47] attest to the timeliness of our proposal in the context of accelerating drug discovery and pharmaceutical development.…”

Section: Figurementioning

confidence: 99%