A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes

2018 ◽  
Vol 549 (1-2) ◽  
pp. 415-435 ◽  
Author(s):  
Bernd Van Snick ◽  
Jens Dhondt ◽  
Kenny Pandelaere ◽  
Johny Bertels ◽  
Roel Mertens ◽  
...  
2019 ◽  
Vol 57 (7) ◽  
pp. 625-635 ◽  
Author(s):  
NVVSS Narayana Murty Nagulakonda ◽  
Ravi Shekar Ananthula ◽  
T Krishnamurthy ◽  
Muguda Ravi Prasada Rao ◽  
Gollapalli Nageswara Rao

Abstract Tazarotene is internationally accepted common name for ethyl 6-[(4,4-dimethylthiochroman-6-yl)ethynyl]nicotinate. It is a synthetic retinoid used for the topical treatment of mild to moderate plaque psoriasis, acne vulgaris and photo aging. To ensure the quality of drug product and drug substance, a LC–MS compatible UHPLC method was developed for quantification of drug and its related substances. Stationary phase with fused core particle technology is used for the separation of impurities. Limit of quantification and limit of detection of the method are 0.1 and 0.03%, respectively. Precision of the method for Tazarotene and all its related substances is less than 2.2% RSD. The correlation coefficient is >0.999. Accuracy of method is ranged from 95.3% to 107.0%. Application of this method in stability analysis has been demonstrated by analyzing stressed samples. Experimental design is used for the verification of robustness of the method. To ensure the safety, an in silico toxicity of the drug and its related substances were determined using TOPKAT and DEREK toxicity predictions Both UHPLC and in silico methods were validated as per the ICH Q2 and ICH M7 guidelines, which will enable a rapid product development of Tazarotene topical formulations while ensuring the safety and quality of product.


Pharmaceutics ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 297
Author(s):  
Joana T. Pinto ◽  
Inês Cachola ◽  
João F. Pinto ◽  
Amrit Paudel

The use of physiologically based pharmacokinetic (PBPK) models to support drug product development has become increasingly popular. The in vitro characterization of the materials of the formulation provides valuable descriptors for the in silico prediction of the drug’s pharmacokinetic profile. Thus, the application of an in vitro–in silico framework can be decisive towards the prediction of the in vivo performance of a new medicine. By applying such an approach, this work aimed to derive mechanistic based insights into the potential impact of carrier particles and powder bulk properties on the in vivo performance of a lactose-based dry powder inhaler (DPI). For this, a PBPK model was developed using salbutamol sulphate (SS) as a model drug and the in vitro performance of its low-dose blends (2% w/w) with different types of lactose particles was investigated using different DPI types (capsule versus reservoir) at distinct airflows. Likewise, the influence of various carrier’s particle and bulk properties, device type and airflow were investigated in silico. Results showed that for the capsule-based device, low-dose blends of SS had a better performance, when smaller carrier particles (Dv0.5 ≈ 50 μm) with about 10% of fines were used. This resulted in a better predicted bioavailability of the drug for all the tested airflows. For the reservoir type DPI, the mean particle size (Dv0.5) was identified as the critical parameter impacting performance. Shear cell and air permeability or compressibility measurements, particle size distribution by pressure titration and the tensile strength of the selected lactose carrier powders were found useful to generate descriptors that could anticipate the potential in vivo performance of the tested DPI blends.


2013 ◽  
Vol 999 (999) ◽  
pp. 1-15
Author(s):  
H.K. Ho ◽  
G. Nemeth ◽  
Y.R. Ng ◽  
E. Pang ◽  
C. Szantai-Kis ◽  
...  

Author(s):  
Md. Chayan Ali ◽  
Mst. Shanzeda Khatun ◽  
Sultana Israt Jahan ◽  
Raju Das ◽  
Yeasmin Akter Munni ◽  
...  

Author(s):  
Elahe Akbari ◽  
Kimia Kardani ◽  
Ali Namvar ◽  
Soheila Ajdary ◽  
Esmat Mirabzadeh Ardakani ◽  
...  

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