Semiautomated Sample Preparation for Protein Stability and Formulation Screening via Buffer Exchange.

A novel semiautomated buffer exchange process workflow was developed to enable efficient early protein formulation screening. An antibody fragment protein, BMSdab, was used to demonstrate the workflow. The process afforded 60% to 80% cycle time and scientist time savings and significant material efficiencies. These efficiencies ultimately facilitated execution of this stability work earlier in the drug development process, allowing this tool to inform the developability of potential candidates for development from a formulation perspective. To overcome the key technical challenges, the protein solution was buffer-exchanged by centrifuge filtration into formulations for stability screening in a 96-well plate with an ultrafiltration membrane, leveraging automated liquid handling and acoustic volume measurements to allow several cycles of exchanges. The formulations were transferred into a vacuum manifold and sterile filtered into a rack holding 96 glass vials. The vials were sealed with a capmat of individual caps and placed in stability stations. Stability of the samples prepared by this process and by the standard process was demonstrated to be comparable. This process enabled screening a number of formulations of a protein at an early pharmaceutical development stage with a short sample preparation time.

Formation of reactive impurities in aqueous and neat polyethylene glycol 400 and effects of antioxidants and oxidation inducers.

A 2,4-dinitrophenylhydrazine (DNPH) precolumn derivatization high-performance liquid chromatography-ultraviolet detection (HPLC-UV) method was developed to quantify levels of formaldehyde and acetaldehyde in polyethylene glycol (PEG) solutions. Formic acid and acetic acid were quantified by HPLC-UV. Samples of neat and aqueous PEG 400 solutions were monitored at 40°C and 50°C to determine effects of excipient source, water content, pH, and trace levels of hydrogen peroxide or iron metal on the formation of reactive impurities. The effects of antioxidants were also evaluated. Formic acid was the major degradation product in nearly all cases. The presence of water increased the rate of formation of all impurities, especially formic acid as did the presence of hydrogen peroxide and trace metals. Acidic pH increased the formation of acetaldehyde and acetic acid. A distribution of unidentified degradation products formed in neat PEG 400 disappeared upon addition of HCl with corresponding increase of formic acid, indicating they were likely to be PEG-formyl esters. Other unidentified degradation products reacted with DNPH to form a distribution of derivatized products likely to be PEG aldehydes. Antioxidants butylated hydroxyanisole, butylated hydroxytoluene, propyl gallate d-alpha tocopheryl polyethylene glycol-1000 succinate, and sodium metabisulfite were effective in limiting reactive impurity formation, whereas ascorbic acid and acetic acid were not.

Reactive impurities in excipients: profiling, identification and mitigation of drug-excipient incompatibility.

Reactive impurities in pharmaceutical excipients could cause drug product instability, leading to decreased product performance, loss in potency, and/or formation of potentially toxic degradants. The levels of reactive impurities in excipients may vary between lots and vendors. Screening of excipients for these impurities and a thorough understanding of their potential interaction with drug candidates during early formulation development ensure robust drug product development. In this review paper, excipient impurities are categorized into six major classes, including reducing sugars, aldehydes, peroxides, metals, nitrate/nitrite, and organic acids. The sources of generation, the analytical method for detection, the stability of impurities upon storage and processing, and the potential reactions with drug candidates of these impurities are reviewed. Specific examples of drug-excipient impurity interaction from internal research and literature are provided. Mitigation strategies and corrective measures are also discussed.

Phase behavior of TPGS-PEG400/1450 systems and their application to liquid formulation: a formulation platform approach.

Vitamin E D-alpha-tocopheryl polyethylene glycol succinate (TPGS) and polyethylene glycol are common excipients used in both preclinical and commercial formulations. In this paper, the phase diagrams of TPGS and polyethylene glycol 400 (PEG 400) in the presence of either water or ethanol were constructed. The effect of water and ethanol on the cloud point temperature of TPGS-PEG 400 mixtures was investigated. In general, the cloud point temperature was reduced by the presence of either water or ethanol in the formulation. However, water was more effective in lowering the cloud point temperature than ethanol. Similarly, the phase diagram of TPGS-PEG 1450 was constructed. The cloud point temperature was observed to decrease with increasing TPGS concentration. It was found that TPGS and PEG 1450 could form a single phase when TPGS concentration was above 75%, based on differential scanning calorimetry, and FT-Raman analysis indicated that a vibration at 1330 cm(-1) disappeared in the melted single phase. In addition, a systematic melting point depression was observed for the mixtures of TPGS-PEG 1450. In the presence of Ibuprofen, a model compound, the cloud point temperature was also reduced. Finally, the extended Flory-Huggins theory for polymer solution was used to analyze the entropic and enthalpic contributions of water and ethanol to the free energy of mixing.

Predicting effect of food on extent of drug absorption based on physicochemical properties.

PURPOSE: To develop a statistical model for predicting effect of food on the extent of absorption (area under the curve of time-plasma concentration profile, AUC) of drugs based on physicochemical properties. MATERIALS AND METHODS: Logistic regression was applied to establish the relationship between the effect of food (positive, negative or no effect) on AUC of 92 entries and physicochemical parameters, including clinical doses used in the food effect study, solubility (pH 7), dose number (dose/solubility at pH 7), calculated Log D (pH 7), polar surface area, total surface area, percent polar surface area, number of hydrogen bond donor, number of hydrogen bond acceptors, and maximum absorbable dose (MAD). RESULTS: For compounds with MAD >or= clinical dose, the food effect can be predicted from the dose number category and Log D category, while for compounds with MAD < clinical dose, the food effect can be predicted from the dose number category alone. With cross validation, 74 out of 92 entries (80%) were predicted into the correct category. The correct predictions were 97, 79 and 68% for compounds with positive, negative and no food effect, respectively. CONCLUSIONS: A logistic regression model based on dose, solubility, and permeability of compounds is developed to predict the food effect on AUC. Statistically, solubilization effect of food primarily accounted for the positive food effect on absorption while interference of food with absorption caused negative effect on absorption of compounds that are highly hydrophilic and probably with narrow window of absorption.