Effect of particle size on in vivo performances of long-acting injectable drug suspension

Ho, Myoung Jin; Jeong, Min Ho; Jeong, Hoe Taek; Kim, Min Seob; Park, Hyun Jin; Kim, Dong Yoon; Lee, Hyo Chun; Song, Woo Heon; Kim, Chang‐Hyun; Lee, Choong Hyun; Choi, Young Wook; Choi, Yong Seok; Han, Young Taek; Kang, Myung Joo

doi:10.1016/j.jconrel.2021.12.011

Cited by 34 publications

(17 citation statements)

References 55 publications

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“…The impact of particle size on the inflammatory reaction at the depot site has been previously reported [ 30 ]. However, with expected significant inter-individual variability due to fluctuation in the immune response for the different rabbits in the study, a formulation-specific inflammation based on particle size was not integrated into the model at this stage.…”

Section: Discussionmentioning

confidence: 99%

Development of Mechanistic In Vitro–In Vivo Extrapolation to Support Bioequivalence Assessment of Long-Acting Injectables

Amaral Silva,

Le Merdy,

Alam

et al. 2024

Pharmaceutics

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Long-acting injectable (LAI) formulations provide sustained drug release over an extended period ranging from weeks to several months to improve efficacy, safety, and compliance. Nevertheless, many challenges arise in the development and regulatory assessment of LAI drug products due to a limited understanding of the tissue response to injected particles (e.g., inflammation) impacting in vivo performance. Mechanism-based in silico methods may support the understanding of LAI–physiology interactions. The objectives of this study were as follows: (1) to use a mechanistic modeling approach to delineate the in vivo performance of DepoSubQ Provera® and formulation variants in preclinical species; (2) to predict human exposure based on the knowledge gained from the animal model. The PBPK model evaluated different elements involved in LAI administration and showed that (1) the effective in vivo particle size is potentially larger than the measured in vitro particle size, which could be due to particle aggregation at the injection site, and (2) local inflammation is a key process at the injection site that results in a transient increase in depot volume. This work highlights how a mechanistic modeling approach can identify critical physiological events and product attributes that may affect the in vivo performance of LAIs.

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Section: Discussionmentioning

confidence: 99%

Development of Mechanistic In Vitro–In Vivo Extrapolation to Support Bioequivalence Assessment of Long-Acting Injectables

Amaral Silva,

Le Merdy,

Alam

et al. 2024

Pharmaceutics

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“…Behind this dilemma is a quite simple principle which seems to be neglected so far: An ideal long-acting formulation need a proper, not just slow, release rate to keep local drug concentration within a range between the effective and toxic thresholds. To this end, controlling the particle size of drug crystals is a promising strategy to achieve a suitable release rate 26 , 28 . Following this idea, in this study we compared the release profile and anesthetic efficacy of RB particles with different size.…”

Section: Discussionmentioning

confidence: 99%

Size control of ropivacaine nano/micro-particles by soft-coating with peptide nanosheets for long-acting analgesia

Liu,

Wu,

Peng

et al. 2024

Theranostics

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Rationale: To meet the need of long-acting analgesia in postoperative pain management, slow-releasing formulations of local anesthetics (LAs) have been extensively investigated. However, challenges still remain in obtaining such formulations in a facile and cost-effective way, and a mechanism for controlling the release rate to achieve an optimal duration is still missing. Methods: In this study, nanosheets formed by a self-assembling peptide were used to encapsulate ropivacaine in a soft-coating manner. By adjusting the ratio between the peptide and ropivacaine, ropivacaine particles with different size were prepared. Releasing profile of particles with different size were studied in vitro and in vivo . The influence of particle size and ropivacaine concentration on effective duration and toxicity were evaluated in rat models. Results: Our results showed that drug release rate became slower as the particle size increased, with particles of medium size (2.96 ± 0.04 μm) exhibiting a moderate release rate and generating an optimal anesthetic duration. Based on this size, formulations at different ropivacaine concentrations generated anesthetic effect with different durations in rat sciatic nerve block model, with the 6% formulation generated anesthetic duration of over 35 h. Long-acting analgesia up to 48 h of this formulation was also confirmed in a rat total knee arthroplasty model. Conclusion: This study provided a facile strategy to prepare LA particles of different size and revealed the relationship between particle size, release rate and anesthetic duration, which provided both technical and theoretical supports for developing long-acting LA formulations with promising clinical application.

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“…This is not unexpected since wet bead milling has several advantages as it is a robust, reproducible, scalable, organic solvent-free, and environmentally friendly process [ 3 , 4 ]. It enables the preparation of concentrated stable suspensions of drug particles [ 3 ], which can have several applications in drug delivery such as modulating drug dissolution and absorption [ 5 , 6 , 7 , 8 , 9 ] and the design of long acting injectables (LAI) [ 10 , 11 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Development of a Semi-Mechanistic Modeling Framework for Wet Bead Milling of Pharmaceutical Nanosuspensions

Clancy,

Guner,

Chattoraj

et al. 2024

Pharmaceutics

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This study aimed to develop a practical semi-mechanistic modeling framework to predict particle size evolution during wet bead milling of pharmaceutical nanosuspensions over a wide range of process conditions and milling scales. The model incorporates process parameters, formulation parameters, and equipment-specific parameters such as rotor speed, bead type, bead size, bead loading, active pharmaceutical ingredient (API) mass, temperature, API loading, maximum bead volume, blade diameter, distance between blade and wall, and an efficiency parameter. The characteristic particle size quantiles, i.e., x10, x50, and x90, were transformed to obtain a linear relationship with time, while the general functional form of the apparent breakage rate constant of this relationship was derived based on three models with different complexity levels. Model A, the most complex and general model, was derived directly from microhydrodynamics. Model B is a simpler model based on a power-law function of process parameters. Model C is the simplest model, which is the pre-calibrated version of Model B based on data collected from different mills across scales, formulations, and drug products. Being simple and computationally convenient, Model C is expected to reduce the amount of experimentation needed to develop and optimize the wet bead milling process and streamline scale-up and/or scale-out.

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Effect of particle size on in vivo performances of long-acting injectable drug suspension

Cited by 34 publications

References 55 publications

Development of Mechanistic In Vitro–In Vivo Extrapolation to Support Bioequivalence Assessment of Long-Acting Injectables

Development of Mechanistic In Vitro–In Vivo Extrapolation to Support Bioequivalence Assessment of Long-Acting Injectables

Size control of ropivacaine nano/micro-particles by soft-coating with peptide nanosheets for long-acting analgesia

Development of a Semi-Mechanistic Modeling Framework for Wet Bead Milling of Pharmaceutical Nanosuspensions

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