Herein, we describe the development of a functionally selective liver X receptor β (LXRβ) agonist series optimized for Emax selectivity, solubility, and physical properties to allow efficacy and safety studies in vivo. Compound 9 showed central pharmacodynamic effects in rodent models, evidenced by statistically significant increases in apolipoprotein E (apoE) and ATP-binding cassette transporter levels in the brain, along with a greatly improved peripheral lipid safety profile when compared to those of full dual agonists. These findings were replicated by subchronic dosing studies in non-human primates, where cerebrospinal fluid levels of apoE and amyloid-β peptides were increased concomitantly with an improved peripheral lipid profile relative to that of nonselective compounds. These results suggest that optimization of LXR agonists for Emax selectivity may have the potential to circumvent the adverse lipid-related effects of hepatic LXR activity.

The effects of the mammography film processing replenishment rate on contrast and speed are studied sensitometrically. Two experiments studied decreasing replenishment rates in the Kodak RP developer and quantified changes in the developer by measuring bromide ion concentrations. First, values of NaBr concentration from 1.7 to 8.4 g/L, achieved by reducing the replenishment rate, were tested with sensitometry strips. Second, the developer replenishment rate of a high volume dedicated mammography processor was reduced by one-third, to 20 cm3/1560 cm2, so that the NaBr concentration rose from 2.0 to 12.36. Sensitometric results for four film types and patient films were tested for changes from standard values as NaBr concentration was restored to 3.31 g/L. Fifty-five clinical images obtained at 7.3-9.3 NaBr g/L were compared to their matching previous films, with NaBr levels of 2-3 g/L, for contrast and visibility of the skin line. For the range of the NaBr ion from 1.7 to 7 g/L, no significant sensitometric differences were found. Above 7 g/L, different film types had different sensitometric results. From 7.3 to 9.3 NaBr g/L, 47.5% of the clinical films reviewed by four radiologists had less contrast compared to previous films. Dedicated mammography processors with high film volume (i.e., those that do not have excessive oxidation or foreign dye problems) can operate at lower replenishment rates than are currently employed. All common mammography film types are stable at these lower replenishment rates up to 7.0 NaBr g/L.

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Chemical and physical stabilities are two key features considered in pharmaceutical development. Chemical stability is typically reported as a combination of potency and degradation product. For peptide products, it is common to measure physical stability via aggregation or fibrillation using the fluorescent reporter Thioflavin T. Executing stability studies is a lengthy process and requires extensive resources. To reduce the resources and shorten the process for stability studies during the development of a product, we introduce a machine learning based model for predicting the chemical stability over time using both the formulation conditions as well as the aggregation curve. In this work, we explore the relationships between the formulation, stability time point, and the measurements of chemical stability and achieve a coefficient of determination on a random test set of 0.945 and a mean absolute error (MAE) of 0.421 when using a multilayer perceptron (MLP) neural network for total degradation. Similarly, we achieve a coefficient of determination of 0.908 and an MAE of 1.435 when predicting the potency using a random forest model. When measurements of physical stability are included into the model, the MAE in the prediction of TD decreases to 0.148 for the MLP model. Using a similar strategy for the prediction of potency, the MAE decreases to 0.705 for the random forest model. Therefore, we can conclude two important points: first, chemical stability can be modeled using machine learning techniques and second there is a relationship between the physical stability of a peptide and its chemical stability.