Inhalation Drug Products Containing Nanomaterials
Anthony J. Hickey, Sandro R.P. da Rocha in Pharmaceutical Inhalation Aerosol Technology, 2019
According to the FDA (FDA 2017), the following attributes should be described and measured for any nanomaterial in a drug product: (i) chemical composition; (ii) average particle size; (iii) particle size distribution (PSD); (iv) shape and morphology; (v) physical stability; and (vi) chemical stability. The following additional attributes may also be needed to describe nanomaterials, including: (vii) assay and distribution of the API (bound/conjugated to the carrier versus free); (viii) structural attributes that relate to function (e.g. core-shell); (ix) surface properties (surface area, surface charge, ligand); (x) coating properties, including how coatings are bound to nanomaterials; (xi) porosity; (xii) particle concentration; (xiii) in vitro release; (xiv) crystal form; (xv) impurities; and (xvi) sterility and endotoxin levels. These measured attributes are in addition to characterizations required for all medical products of similar intended application (e.g. efficacy, toxicity).
X-Ray, MRI, and Ultrasound Agents Basic Principles
George C. Kagadis, Nancy L. Ford, Dimitrios N. Karnabatidis, George K. Loudos in Handbook of Small Animal Imaging, 2018
During manufacture, the easiest means to sterilize solutions is through autoclaving of the sealed vials at temperatures >100°C. Therefore high chemical stability is highly desirable. This latter requirement was a primary flaw of metrizamide (Table 15.2). Despite its dramatically improved tolerance relative to its predecessors, imparted by its nonionized nature, a lack of shelf stability in solution meant that metrizamide had to be lyophilized sterile and the user was required to dissolve it in bicarbonate solution. It was therefore an easy target to be replaced by molecules (e.g., iopamidol and iohexol in Table 15.3) that were more stable. Interestingly, XRCAs can achieve their 1 M solubility requirement through innate solubility or through supersaturation, a state of non-equilibrium that is stable for lack of a path to precipitation such as a seed crystal. Terminal heat sterilization also aids in ensuring that microscopic seed crystals are not present in the vial through accidental local evaporation. So, in addition to extreme water solubility, extreme chemical/thermal stability is required to survive the sterilization procedure, plus withstand any hydrolysis over a 2-year expected shelf-life in aqueous solution. De-iodination is inhibited by the >50 kcal aromatic C–I bonds. Note that the water for injection used in these formulations must be strictly free of metals such as copper (Cu), which can catalyze de-iodination. With three I per aromatic ring and relatively compact substituents, I atoms now represent ~50% of the molecular weight of the CA molecules. The leading molecules are now bulk-synthesized in extremely automated manufacturing plants at the 1000 ton/year scale.
Nanosuspensions as Nanomedicine: Current Status and Future Prospects
Debarshi Kar Mahapatra, Sanjay Kumar Bharti in Medicinal Chemistry with Pharmaceutical Product Development, 2019
In addition to physical stability, chemical stability is an important aspect of drug delivery platforms in the pharmaceutical sciences [106]. Generally, nanosuspensions have been prepared in a dispersion medium of water or water-mixture environments, although a few processes have used non-aqueous media [107]. Therefore, chemical reactions, such as hydrolysis and oxidation, are considerable problems in the formulation of nanosuspensions and limit drug chemical stability in nanosuspensions [61]. The preparation of chemically stable nanosuspensions to prevent the hydrolysis of labile compounds remains challenging.
High-throughput screening of antibody variants for chemical stability: identification of deamidation-resistant mutants
Published in mAbs, 2018
Danielle M. DiCara, Nisana Andersen, Ruby Chan, James A. Ernst, Gai Ayalon, Greg A. Lazar, Nicholas J. Agard, Amy Hilderbrand, Isidro Hötzel
This work focuses on asparagine deamidation following thermal stress, but it is likely that the methods described could also be applicable to other chemical modifications, including but not limited to methionine and tryptophan oxidation and isomerization of aspartyl residues. It may also facilitate evaluation of the impact of extrinsic conditions on chemical stability (Supplementary Figure 4). It is important to note that modifications that do not affect affinity will not be detected by this assay, and that if the affinity of the modified antibody for antigen is relatively similar to that of the parental antibody, the presence of these modifications may difficult or impossible to detect using this method. Ideally, the antigen should be monodisperse and monovalent, in order to minimize deviations from a 1:1 binding model that are not due to induced modifications. To confidently distinguish reductions in relative activity that are due to chemical modification from those reductions that are due to physical effects such as aggregation, confirmation studies (for example by LC-MS) are strongly recommended. However, the binding assay described uses laboratory equipment routinely available in antibody discovery and engineering laboratories and can provide stability data less than three weeks following the availability of microgram quantities of protein. Thus, this method represents a useful screen for rapid identification of stable variants, particularly at the earlier stages of therapeutic antibody research, and is an excellent complement to more direct but lower-throughput bioanalytical analyses.
Development of nanodispersion-based sildenafil metered-dose inhalers stabilized by poloxamer 188: a potential candidate for the treatment of pulmonary arterial hypertension
Published in Pharmaceutical Development and Technology, 2019
Charisopon Chunhachaichana, Rutthapol Sritharadol, Somchai Sawatdee, Paul Wan Sia Heng, Teerapol Srichana
After 6-month storage, sildenafil content and aerosol characteristics of F5–F12 were reevaluated (see Figure 8). The findings indicated a significant decrease (p < 0.01) in the amount of sildenafil delivered from F5 and F9 after 6 months, thus falling outside the acceptance limit (80–120%). Also, the FPF of F5 and F9 decreased significantly (p < 0.05), but their MMAD remained relatively unchanged. The chemical stability results were in good agreement with the data on physical stability discussed earlier. The decrease in the amount of sildenafil delivered from F5 and F9 might have caused some crystal growth on storage as the formulations did not contain P188. In addition, a significant (p < 0.01) decrease in the amount of sildenafil content in F11 and F12 was also observed after 6 months (see Figure 8(A)). The decrease in sildenafil content could be linked to high EtOH and P188 concentration which caused the instability in the canisters and could turn the formulations from solution-like nanosuspension to suspension MDIs which has fewer drug particles per droplet (Stein 2008). The instability resulted in a decrease in ED and FPF, as well as an increase in MMAD (see Figure 8(B,C)).
Prediction of saxagliptin stability using a new approach based on Partial Least Squares and Design of Experiments
Published in Pharmaceutical Development and Technology, 2020
Nika Jordan, Jure Zakrajšek, Simona Bohanec, Robert Roškar, Iztok Grabnar
In the paper we evaluated factors that influence drug product stability and formation of main degradation products with the use of DoE methodology and PLS. The aim was to improve the understanding of stability of the drug product early in the stability study. This kind of approach could enable us to predict influences of various factors and their combinations on chemical stability and more accurately predict the drug product shelf life. Furthermore, we predicted results of the responses for two-year shelf life with PLS models based on 18 months data for both long-term stability conditions and compared the model predicted results to the actual results of a 24-month stability study. Finally, a comparison of response prediction with PLS and simple linear least squares regression was made.
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