Pulmonary dissolution of poorly soluble drug substances (DSs) may limit the drug absorption rate and consequently influence clinical performance. Dissolution rate is thus an important quality attribute, and its influence on in vivo drug release must be characterized, understood, and controlled early in the development process. The aim of this study is to establish an in vitro dissolution method with the capability to capture therapeutically relevant differences in the dissolution rate between drug batches and drug compounds. A method was developed by which a biorelevant aerosol fraction was captured on a filter using a sedimentation technique in a modified Andersen cascade impactor to avoid particle agglomeration. Subsequently, the filters were transferred to a commercial Transwell system where dissolution in 3 mL of phosphate buffer at pH 6.8 with 0.5% sodium dodecyl sulfate (SDS) occurred at sink conditions. Dissolved DS was quantified over time using UPLC-UV. Dissolution data was obtained on a series of micronized and aerosolized lipophilic DSs, budesonide, fluticasone furoate (FF), fluticasone propionate (FP), and AZD5423. The latter is a lipophilic AstraZeneca development compound available in two different mass median diameters (MMD), 1.3 (AZD5423) and 3.1 μm (AZD5423). Dissolution data were evaluated using a Weibull fit and expressed as t, the time to dissolution of 63% of the initial dose. The following rank-order of t was obtained (mean t and MMD in brackets), budesonide (10 min, 2.1 μm) = AZD5423 (10 min, 1.3 μm) < AZD5423 (19 min, 3.1 μm) < FP (38 min, 2.4 μm) < FF (63 min, 2.5 μm). The method could differentiate between different drug compounds with different solubility but similar particle size distribution, as well as between the same drug compound with different particle size distributions. Furthermore, a relation between the in vitro dissolution rate ( t) and mean pulmonary absorption time in man (literature data) was observed, indicating clinical relevance. It is thus concluded, that the method may be useful for the characterization and ranking of DSs and drug products in early development, as well as being a potential tool for the control of dissolution as a potential quality attribute.
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http://dx.doi.org/10.1021/acs.molpharmaceut.8b00796 | DOI Listing |
Sci Rep
November 2024
Institute of Trauma Surgery, Munich, Technical University Munich, Munich, 81675, Germany.
Solid organ transplantation continues to be the only or most efficient therapeutic solution for several end-stage diseases. The success of such transplantation is largely dependent on the swift transportation of organs from donors to recipients, as Cold Ischemia Time (CIT) plays a critical role in determining the recipient's medical outcome. This study explores the potential of Advanced Air Mobility (AAM) in the context of organ transplantation in Austria and Germany.
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December 2024
Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Needle-based injections currently enable the administration of a wide range of biomacromolecule therapies across the body, including the gastrointestinal tract, through recent developments in ingestible robotic devices. However, needles generally require training, sharps management and disposal, and pose challenges for autonomous ingestible systems. Here, inspired by the jetting systems of cephalopods, we have developed and evaluated microjet delivery systems that can deliver jets in axial and radial directions into tissue, making them suitable for tubular and globular segments of the gastrointestinal tract.
View Article and Find Full Text PDFNature
November 2024
Department of Thoracic and Head and Neck Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Materials (Basel)
June 2024
Material and Chemical Research Laboratories, Industrial Technology Research Institute, Hsinchu 31040, Taiwan.
This study explores the integration of machine learning (ML) techniques to predict and optimize the compressive strength of alkali-activated materials (AAMs) sourced from four industrial waste streams: blast furnace slag, fly ash, reducing slag, and waste glass. Aimed at mitigating the labor-intensive trial-and-error method in AAM formulation, ML models can predict the compressive strength and then streamline the mixture compositions. By leveraging a dataset of only 42 samples, the Random Forest (RF) model underwent fivefold cross-validation to ensure reliability.
View Article and Find Full Text PDFCirc Cardiovasc Interv
July 2024
Division of Cardiology, Center for Structural Heart Disease, Henry Ford Health System, Detroit, MI (M.B.B., W.W.O.).
Background: Prior studies have found that patients with chronic kidney disease (CKD) have worse outcomes following percutaneous coronary intervention (PCI). There are no data about patients with advanced CKD undergoing Impella-supported high-risk PCI. We, therefore, aimed to evaluate angiographic characteristics and clinical outcomes in patients with CKD who received Impella-supported high-risk PCI as part of the catheter-based ventricular assist device PROTECT III study (A Prospective, Multi-Center, Randomized Controlled Trial of the IMPELLA RECOVER LP 2.
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