Database screening as a strategy to identify endogenous candidate metabolites to probe and assess mitochondrial drug toxicity.

Adverse drug reactions (ADRs) are considered an inherent risk of medication use, and some ADRs have been associated with off-target drug interactions with mitochondria. Metabolites that reflect mitochondrial function may help identify patients at risk of mitochondrial toxicity. We employed a database strategy to identify candidate mitochondrial metabolites that could be clinically useful to identify individuals at increased risk of mitochondrial-related ADRs. This led to L-carnitine being identified as the candidate mitochondrial metabolite. L-carnitine, its acetylated metabolite, acetylcarnitine and other acylcarnitines are mitochondrial biomarkers used to detect inborn errors of metabolism. We hypothesized that changes in L-carnitine disposition, induced by a "challenge test" of intravenous L-carnitine, could identify mitochondrial-related ADRs by provoking variation in L-carnitine and/or acetylcarnitine blood levels. To test this hypothesis, we induced mitochondrial drug toxicity with clofazimine (CFZ) in a mouse model. Following CFZ treatment, mice received an L-carnitine "challenge test". CFZ-induced changes in weight were consistent with previous work and reflect CFZ-induced catabolism. L-carnitine induced differences in whole blood acetylcarnitine concentrations in a manner that was dependent on CFZ treatment. This supports the usefulness of a database strategy for the discovery of candidate metabolite biomarkers of drug toxicity and substantiates the potential of the L-carnitine "challenge test" as a "probe" to identify drug-related toxicological manifestations.

Real-time concentration monitoring using a compact composite sensor array for in situ quality control of aqueous formulations.

Recent advancements have demonstrated the feasibility of refrigerator-sized pharmaceutical manufacturing platforms (PMPs) for integrated end-to-end manufacturing of active pharmaceutical ingredients (APIs) into formulated drug products. Unlike typical laboratory- or industrial-scale setups, PMPs present unique requirements for process analytical technology (PAT) with respect to versatility, flexibility, and physical size to fit into the PMP space constraints. In this proof of principle study, a novel compact composite sensor array (CCSA) combining ultraviolet (UV) and near infrared (NIR) features at four different wavelengths (280, 340, 600, 860 nm) with temperature measuring capability in a 380 × 30 mm housing (length x diameter, 7 mm diameter at the probe head), were evaluated. The results indicate that the CCSA prototype is capable of measuring the solution and suspension concentrations in aqueous formulations of four model APIs (warfarin sodium isopropanol solvate, lidocaine hydrochloride monohydrate, 6-mercaptopurine monohydrate, acetaminophen) in situ and in real-time with similar accuracy as an established Raman spectrometer commonly applied for method development.

Solubility Determination and Correlation of Warfarin Sodium 2­Propanol Solvate in Pure, Binary, and Ternary Solvent Mixtures.

The solubility of warfarin sodium isopropanol solvate (WS·IPA), a widely used anticoagulant, was determined at temperatures ranging from 278.15 to 333.15 K in four pure solvents (acetone, ethanol, IPA, and water), five binary solvent mixtures (IPA + acetone, IPA + ethanol, IPA + water, IPA + heptane, and IPA + hexane), and five ternary solvent mixtures (IPA + acetone + heptane, IPA + acetone + hexane, IPA + ethanol + heptane, IPA + ethanol + hexane, and IPA + water + heptane) using the polythermal method. It was demonstrated that the solubility of WS·IPA increases with increasing temperature in the pure solvents and at constant solvent composition in the solvent mixtures. In addition, the solubility of WS·IPA in IPA increases with increasing content of acetone, ethanol, and water, which act as cosolvents, and decreases with increasing content of heptane and hexane, which act as antisolvents. The experimental solubility data of WS·IPA in pure solvents and binary and ternary solvent mixtures were correlated using the modified Apelblat and λh model equations. The correlated solubility data agree with the experimental data based on the relative deviation and the average relative deviation (ARD %) values. Thus, the correlated and experimentally derived solubility data of WS·IPA provide a pathway to engineer advanced pharmaceutical crystallization processes for WS·IPA.