Intrinsic Dissolution Rate Profiling of Poorly Water-Soluble Compounds in Biorelevant Dissolution Media

Teleki, Alexandra; Nylander, Olivia; Bergström, Christel A S

doi:10.3390/pharmaceutics12060493

Cited by 29 publications

(19 citation statements)

References 66 publications

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“…For example, the weak base cinnarizine shows increased solubility in media simulating the fed intestine (fed-state simulated intestinal fluid, FeSSIF) compared with the fasted intestine (fasted-state simulated intestinal fluid, FaSSIF). This observation is in accordance with the in vivo performance, since cinnarizine shows a positive food effect [70]. Such investigations can also be very beneficial in the early developmental stages, since knowledge about drug solubility and dissolution rates can guide the choice of formulation strategies to overcome potential limitations and provide for more robust formulations against the various GI conditions.…”

Section: Design and Optimization Of Biorelevant In Vitro Methodssupporting

confidence: 78%

Application of In Vivo Imaging Techniques and Diagnostic Tools in Oral Drug Delivery Research

et al. 2022

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Drug absorption following oral administration is determined by complex and dynamic interactions between gastrointestinal (GI) physiology, the drug, and its formulation. Since many of these interactions are not fully understood, the COST action on “Understanding Gastrointestinal Absorption-related Processes (UNGAP)” was initiated in 2017, with the aim to improve the current comprehension of intestinal drug absorption and foster future developments in this field. In this regard, in vivo techniques used for the characterization of human GI physiology and the intraluminal behavior of orally administered dosage forms in the GI tract are fundamental to gaining deeper mechanistic understanding of the interplay between human GI physiology and drug product performance. In this review, the potential applications, advantages, and limitations of the most important in vivo techniques relevant to oral biopharmaceutics are presented from the perspectives of different research fields.

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Section: Design and Optimization Of Biorelevant In Vitro Methodssupporting

confidence: 78%

Application of In Vivo Imaging Techniques and Diagnostic Tools in Oral Drug Delivery Research

et al. 2022

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“…Fukui indices are frontier orbital indices, indicating atomic electron affinity and a molecule’s ability to become polarised upon changes to electron density [ 54 , 55 ]. Similar Fukui indices were previously important properties governing the intrinsic dissolution rate of PWSDs in biorelevant media [ 56 ] and in support vector machine modelling to predict GFA for compounds between 200 and 300 g/mol. In this case, a high value, which denoted increased electron reactivity, suggested a non-glass former [ 9 ].…”

Section: Discussionsupporting

confidence: 52%

Artificial Neural Networks to Predict the Apparent Degree of Supersaturation in Supersaturated Lipid-Based Formulations: A Pilot Study

et al. 2021

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In response to the increasing application of machine learning (ML) across many facets of pharmaceutical development, this pilot study investigated if ML, using artificial neural networks (ANNs), could predict the apparent degree of supersaturation (aDS) from two supersaturated LBFs (sLBFs). Accuracy was compared to partial least squares (PLS) regression models. Equilibrium solubility in Capmul MCM and Maisine CC was obtained for 21 poorly water-soluble drugs at ambient temperature and 60 °C to calculate the aDS ratio. These aDS ratios and drug descriptors were used to train the ML models. When compared, the ANNs outperformed PLS for both sLBFCapmulMC (r2 0.90 vs. 0.56) and sLBFMaisineLC (r2 0.83 vs. 0.62), displaying smaller root mean square errors (RMSEs) and residuals upon training and testing. Across all the models, the descriptors involving reactivity and electron density were most important for prediction. This pilot study showed that ML can be employed to predict the propensity for supersaturation in LBFs, but even larger datasets need to be evaluated to draw final conclusions.

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“…Equation (48) describes the dissolution constant enhancement for the two equilibriums, before and after the particle size decrease. The Fenofibrate dissolution was approximated as a first-order reaction, according to experimental time profile data [23,47]:…”

Section: Solubility Enhancement Prediction and Experimental Validationmentioning

confidence: 99%

Integrating Elastic Tensor and PC-SAFT Modeling with Systems-Based Pharma 4.0 Simulation, to Predict Process Operations and Product Specifications of Ternary Nanocrystalline Suspensions

Davidopoulou

Kachrimanis

2021

Pharmaceutics

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Comminution of BCS II APIs below the 1 μm threshold followed by solidification of the obtained nanosuspensions improves their dissolution properties. The breakage process reveals new crystal faces, thus creating altered crystal habits of improved wettability, facilitated by the adsorption of stabilizing polymers. However, process-induced transformations remain unpredictable, mirroring the current limitations of our atomistic level of understanding. Moreover, conventional equations of estimating dissolution, such as Noyes–Whitney and Nernst–Brunner, are not suitable to quantify the solubility enhancement due to the nanoparticle formation; hence, neither the complex stabilizer contribution nor the adsorption influence on the interfacial tension occurring between the water and APIs is accounted for. For such ternary mixtures, no numeric method exists to correlate the mechanical properties with the interfacial energy, capable of informing the key process parameters and the thermodynamic stability assessment of nanosuspensions. In this work, an elastic tensor analysis was performed to quantify the API stability during process implementation. Moreover, a novel thermodynamic model, described by the stabilizer-coated nanoparticle Gibbs energy anisotropic minimization, was structured to predict the material’s system solubility quantified by the application of PC-SAFT modeling. Comprehensively merging elastic tensor and PC-SAFT analysis into the systems-based Pharma 4.0 algorithm provided a validated, multi-level, built-in method capable of predicting the critical material quality attributes and corresponding key process parameters.

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Intrinsic Dissolution Rate Profiling of Poorly Water-Soluble Compounds in Biorelevant Dissolution Media

Cited by 29 publications

References 66 publications

Application of In Vivo Imaging Techniques and Diagnostic Tools in Oral Drug Delivery Research

Application of In Vivo Imaging Techniques and Diagnostic Tools in Oral Drug Delivery Research

Artificial Neural Networks to Predict the Apparent Degree of Supersaturation in Supersaturated Lipid-Based Formulations: A Pilot Study

Integrating Elastic Tensor and PC-SAFT Modeling with Systems-Based Pharma 4.0 Simulation, to Predict Process Operations and Product Specifications of Ternary Nanocrystalline Suspensions

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