A physiologically-based nanocarrier biopharmaceutics model to reverse-engineer the in vivo drug release

Nagpal, Shakti; Braner, Svenja; Modh, Harshvardhan; Tan, Ada Xi Xin; Mast, Marc-Phillip; Chichakly, Karim J.; Albrecht, Volker; Wacker, Matthias G.

doi:10.1016/j.ejpb.2020.06.004

Cited by 21 publications

(31 citation statements)

References 55 publications

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“…The total plasmaconcentration time profile is analyzed based on the model assumption of a volume of distribution of the encapsulated fraction (V DC ) corresponding to the actual plasma volume of the investigated species [48]. This was confirmed by several investigations and is explained by the limited mobility of large particles in the vascular system [26]. For the present investigation, the physiological blood plasma volume of Wistar rats was used [48].…”

Section: Physiologically-based Nanocarrier Biopharmaceutics Modelmentioning

confidence: 97%

“…For NanoCore-6.4, total and the free drug concentrations decrease more rapidly compared to NanoCore-7.4 indicating a more rapid release from the nanodelivery system ( Figure 5). As compared to the clinical protocols, the tmax value corresponds to the first sampling time point with no further delay due to the vascular transit [26]. In the NCA, both formulation prototypes, (NanoCore-6.4 and NanoCore-7.4) are characterized by a very similar AUCall while a considerable difference in the areas during the first hour (AUC0 → 1h) indicates a difference in the key characteristics of both carriers.…”

Section: Non-compartmental Analysismentioning

confidence: 99%

“…Compartmental analysis of the plasma concentration-time profiles was carried out using the PBNB model ( Figure 6) [26]. It provides a simple but effective alternative to bioanalytical assays that often require a considerable volume of blood.…”

Section: Physiologically-based Nanocarrier Biopharmaceutics Modelmentioning

confidence: 99%

“…Compared to more conventional modeling approaches [49], the PBNB model uses a very limited number of physiological parameters and summarizes different organs in the accumulation and periphery compartment ( Figure 6). This makes it more robust to differences in the exact biodistribution of formulations [26]. The distribution and elimination behavior of free doxorubicin was estimated using the pharmacokinetic parameters observed for the free drug including k F , k 12 , k 21 , and V DF .…”

Section: Physiologically-based Nanocarrier Biopharmaceutics Modelmentioning

confidence: 99%

“…In a pharmacokinetic study in rats, we gained more insight into the distribution and elimination behavior of the carrier. To elucidate the role of the encapsulated and the nonencapsulated fraction, the physiologically-based nanocarrier biopharmaceutics (PBNB) model was applied [26].…”

Section: Introductionmentioning

confidence: 99%

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Exploring the Interplay between Drug Release and Targeting of Lipid-Like Polymer Nanoparticles Loaded with Doxorubicin

et al. 2021

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Targeted delivery of doxorubicin still poses a challenge with regards to the quantities reaching the target site as well as the specificity of the uptake. In the present approach, two colloidal nanocarrier systems, NanoCore-6.4 and NanoCore-7.4, loaded with doxorubicin and characterized by different drug release behaviors were evaluated in vitro and in vivo. The nanoparticles utilize a specific surface design to modulate the lipid corona by attracting blood-borne apolipoproteins involved in the endogenous transport of chylomicrons across the blood–brain barrier. When applying this strategy, the fine balance between drug release and carrier accumulation is responsible for targeted delivery. Drug release experiments in an aqueous medium resulted in a difference in drug release of approximately 20%, while a 10% difference was found in human serum. This difference affected the partitioning of doxorubicin in human blood and was reflected by the outcome of the pharmacokinetic study in rats. For the fast-releasing formulation NanoCore-6.4, the AUC0→1h was significantly lower (2999.1 ng × h/mL) than the one of NanoCore-7.4 (3589.5 ng × h/mL). A compartmental analysis using the physiologically-based nanocarrier biopharmaceutics model indicated a significant difference in the release behavior and targeting capability. A fraction of approximately 7.310–7.615% of NanoCore-7.4 was available for drug targeting, while for NanoCore-6.4 only 5.740–6.057% of the injected doxorubicin was accumulated. Although the targeting capabilities indicate bioequivalent behavior, they provide evidence for the quality-by-design approach followed in formulation development.

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Section: Physiologically-based Nanocarrier Biopharmaceutics Modelmentioning

confidence: 97%

Section: Non-compartmental Analysismentioning

confidence: 99%

Section: Physiologically-based Nanocarrier Biopharmaceutics Modelmentioning

confidence: 99%

Section: Physiologically-based Nanocarrier Biopharmaceutics Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Exploring the Interplay between Drug Release and Targeting of Lipid-Like Polymer Nanoparticles Loaded with Doxorubicin

et al. 2021

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Physiologically based pharmacokinetic modeling of intravenously administered nanoformulated substances

Minnema

Borgos

Liptrott

et al. 2022

Drug Deliv. and Transl. Res.

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The use of nanobiomaterials (NBMs) is becoming increasingly popular in the field of medicine. To improve the understanding on the biodistribution of NBMs, the present study aimed to implement and parametrize a physiologically based pharmacokinetic (PBPK) model. This model was used to describe the biodistribution of two NBMs after intravenous administration in rats, namely, poly(alkyl cyanoacrylate) (PACA) loaded with cabazitaxel (PACA-Cbz), and LipImage™ 815. A Bayesian parameter estimation approach was applied to parametrize the PBPK model using the biodistribution data. Parametrization was performed for two distinct dose groups of PACA-Cbz. Furthermore, parametrizations were performed three distinct dose groups of LipImage™ 815, resulting in a total of five different parametrizations. The results of this study indicate that the PBPK model can be adequately parametrized using biodistribution data. The PBPK parameters estimated for PACA-Cbz, specifically the vascular permeability, the partition coefficient, and the renal clearance rate, substantially differed from those of LipImage™ 815. This emphasizes the presence of kinetic differences between the different formulations and substances and the need of tailoring the parametrization of PBPK models to the NBMs of interest. The kinetic parameters estimated in this study may help to establish a foundation for a more comprehensive database on NBM-specific kinetic information, which is a first, necessary step towards predictive biodistribution modeling. This effort should be supported by the development of robust in vitro methods to quantify kinetic parameters. Graphical abstract

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Nanomedicine at the crossroads – A quick guide for IVIVC

Mast

Modh

Champanhac

et al. 2021

Advanced Drug Delivery Reviews

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A physiologically-based nanocarrier biopharmaceutics model to reverse-engineer the in vivo drug release

Cited by 21 publications

References 55 publications

Exploring the Interplay between Drug Release and Targeting of Lipid-Like Polymer Nanoparticles Loaded with Doxorubicin

Exploring the Interplay between Drug Release and Targeting of Lipid-Like Polymer Nanoparticles Loaded with Doxorubicin

Physiologically based pharmacokinetic modeling of intravenously administered nanoformulated substances

Nanomedicine at the crossroads – A quick guide for IVIVC

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