Predicting drug solubility in organic solvents mixtures: A machine-learning approach supported by high-throughput experimentation.

A novel approach based on supervised machine-learning is proposed to predict the solubility of drugs and drug-like molecules in mixtures of organic solvents. Similar to quantitative structure-property relationship (QSPR) models, different solvent types are identified by molecular descriptors, which, in this study, are considered as UNIFAC subgroups. To overcome the potential lack of UNIFAC subgroups for the complex Active Pharmaceutical Ingredients (APIs) currently developed in the pharmaceutical industry, the API molecule is considered as a unique entity in the proposed modelling approach. Therefore, API solubility is predicted as a function of temperature, functional subgroups of the solvents and composition of the solvent mixture; in turn, regressors' correlation is handled through Partial Least-Squares (PLS) regression. The method is developed and tested with experimental data of a real API and 14 organic solvents that are industrially employed for crystallisation. Solubility predictions are accurate and precise for single solvents, binary mixtures and ternary mixtures of organic solvents at different compositions and temperatures, with a determination coefficient R2 ≥ 0.90. To further test the applicability of the model, the proposed approach is applied to 9 literature organic solubility datasets of drugs and drug-like compounds and compared to benchmark solubility models in the literature. Results show that the proposed approach provides satisfactory predictions: the majority of validation and calibration data have R2 = 0.95-0.99; the ratio between RMSE (root mean squared error) of the proposed method and the range of measured solubility values is from 1 to 3 orders of magnitude smaller than the RMSE ratio obtained by the benchmark models.

Investigation of the Formaldehyde-Catalyzed NNitrosation of Dialkyl Amines: An Automated Experimental and Kinetic Modelling Study Using Dibutylamine.

The potential for drug substances and drug products to contain low levels of N-nitrosamines is of continued interest to the pharmaceutical industry and regulatory authorities. Acid-promoted nitrosation mechanisms in solution have been investigated widely in the literature and are supported by kinetic modelling studies. Carbonyl compounds, particularly formaldehyde, which may be present as impurities in excipients and drug product packaging components or introduced during drug substance manufacturing processes are also known to catalyze nitrosation, but their impact on the risk of N-nitrosamine formation has not been systematically investigated to date. In this study, we experimentally investigated the multivariate impact of formaldehyde, nitrite and pH on N-nitrosation in aqueous solution using dibutylamine as a model amine. We augmented a published kinetic model by adding formaldehyde-catalyzed nitrosation reactions. We validated the new kinetic model vs. the experimental data and then used the model to systematically investigate the impact of formaldehyde levels on N-nitrosamine formation. Simulations of aqueous solution systems show that at low formaldehyde levels the formaldehyde-catalyzed mechanisms are insignificant in comparison to other routes. However, formaldehyde-catalyzed mechanisms can become more significant at neutral and high pH under higher formaldehyde levels. Model-based sensitivity analysis demonstrated that under high nitrite levels and low formaldehyde levels (where the rate of formaldehyde-catalyzed nitrosation is low compared to the acid-promoted pathways) the model can be used with kinetic parameters for model amines in the literature without performing additional experiments to fit amine-specific parameters. For other combinations of reaction parameters containing formaldehyde, the formaldehyde-catalyzed kinetics are non-negligible, and thus it is advised that, under such conditions, additional experiments should be conducted to reliably use the model.

Integrating In Vitro Biopharmaceutics into Physiologically Based Biopharmaceutic Model (PBBM) to Predict Food Effect of BCS IV Zwitterionic Drug (GSK3640254).

A strategy followed to integrate in vitro solubility and permeability data into a PBBM model to predict the food effect of a BCS IV zwitterionic drug (GSK3640254) observed in clinical studies is described. The PBBM model was developed, qualified and verified using clinical data of an immediate release (IR)-tablet (10-320 mg) obtained in healthy volunteers under fasted and fed conditions. The solubility of GSK3640254 was a function of its ionization state, the media composition and pH, whereas its permeability determined using MDCK cell lines was enhanced by the presence of mixed micelles. In vitro data alongside PBBM modelling suggested that the positive food effect observed in the clinical studies was attributed to micelle-mediated enhanced solubility and permeability. The biorelevant media containing oleic acid and cholesterol in fasted and fed levels enabled the model to appropriately capture the magnitude of the food effect. Thus, by using Simcyp® v20 software, the PBBM model accurately predicted the results of the food effect and predicted data were within a two-fold error with 70% being within 1.25-fold. The developed model strategy can be effectively adopted to increase the confidence of using PBBM models to predict the food effect of BCS class IV drugs.

Effect of methanol in controlling defunctionalization of the propyl side chain of phenolics from catalytic upstream biorefining.

In recent years, lignin valorization has gained upward momentum owing to advances in both plant bioengineering and catalytic processing of lignin. In this new horizon, catalysis is now applied to the 'pulping process' itself, creating efficient methods for lignocellulose fractionation or deconstruction (here referred to as Catalytic Upstream Biorefining or 'CUB'). These processes render, together with delignified pulps, lignin streams of low molecular weight (Mw) and low molecular diversity. Recently, we introduced a CUB process based on Early-stage Catalytic Conversion of Lignin (ECCL) through H-transfer reactions catalyzed by RANEY® Ni. This approach renders a lignin stream obtained as a viscous oil, comprising up to 60 wt% monophenolic compounds (Mw < 250 Da). The remaining oil fraction (40 wt%) is mainly composed of lignin oligomers, and as minor products, holocellulose-derived polyols and lignin-derived species of high Mw (0.25-2 kDa). Simultaneously, the process yields a holocellulose pulp with a low content of residual lignin (<5 wt%). Despite the efficiency of aqueous solutions of 2-propanol as a solvent for lignin fragments and an H-donor, there is scant information regarding the CUB process carried out in the presence of primary alcohols, which often inhibit the catalytic activity of RANEY® Ni, as revealed in model compound studies performed at low temperature. Considering the composition of the lignin oils obtained from CUB based on ECCL, the processes commonly render ortho-(di)methoxy-4-propylphenol derivatives with a varied degree of defunctionalization of the propyl side chain. In this contribution, we present the role of the alcohol solvent (methanol or 2-propanol) and Ni catalyst (Ni/C or RANEY® Ni) in control over selectivity of phenolic products. The current results indicate that solvent effects on the catalytic processes could hold the key for improving control over the degree of functionalization of the propyl side-chain in the lignin oil obtained from CUB, offering new avenues for lignin valorization at the extraction step.

Zeolites as sustainable catalysts for the selective synthesis of renewable bisphenols from lignin-derived monomers.

Alternative biobased bisphenols from lignocellulosic biomass are not only favorable to reduce the environmental impact of current petroleum-derived plastics, but they can be simultaneously beneficial for health issues related to bisphenol A (BPA). Additionally, conventional BPA synthesis entails a large excess of unrecoverable homogeneous acid catalyst (e.g., HCl) or unrecyclable thermolabile sulfonated resins. In this report, zeolites are proposed as recoverable and thermally stable solid acids for the Brønsted-acid-catalyzed condensation between 4-methylguaiacol and formaldehyde to selectively produce renewable bisphenols. It is found that the Brønsted-acid-site density plays a pivotal role for catalyst performance. In particular, the cheap and environmentally friendly FAU 40 exhibits outstanding activity (turnover frequency of 496 h-1 ) and selectivity (>95 %), outperforming even the best benchmark catalyst. Additionally, the zeolite can be easily recycled without activity loss after regeneration by coke burn-off. The catalytic zeolite system also seems very promising for other lignin-derived alkylphenols, alkylguaiacols, and alkylsyringols.

Catalytic Upstream Biorefining through Hydrogen Transfer Reactions: Understanding the Process from the Pulp Perspective.

Catalytic upstream biorefining (CUB) encompasses processes for plant biomass deconstruction through the early-stage conversion of lignin by the action of a hydrogenation catalyst. CUB processes produce lignin as an extensively depolymerised product (i.e., a viscous lignin oil) and render highly delignified pulps. In this report, we examine CUB from the pulp perspective. Notably, Raney Ni plays an indirect role in the processes that occur within the lignocellulose matrix. As there are negligible points of contact between the poplar wood chips and Raney Ni, the catalyst action is limited to the species leached from the matrix into the liquor. Nevertheless, the substantial changes in the liquor composition (through the decomposition of carboxylic acids and H-transfer reductive processes on the lignin fragments) have significant implications for the pulp composition, degree of polymerisation and morphology. Compared with organosolv pulps, CUB pulps show higher xylan retention, higher delignification, and higher polymerisation degree. Moreover, the correlation between these properties and the performance of the enzymatic hydrolyses of CUB and organosolv pulps reveals that the high susceptibility of CUB pulps is mostly caused by their lower residual lignin contents.

Catalytic biorefining of plant biomass to non-pyrolytic lignin bio-oil and carbohydrates through hydrogen transfer reactions.

Through catalytic hydrogen transfer reactions, a new biorefining method results in the isolation of depolymerized lignin--a non-pyrolytic lignin bio-oil--in addition to pulps that are amenable to enzymatic hydrolysis. Compared with organosolv lignin, the lignin bio-oil is highly susceptible to further hydrodeoxygenation under low-severity conditions and therefore establishes a unique platform for lignin valorization by heterogeneous catalysis. Overall, the potential of a catalytic biorefining method designed from the perspective of lignin utilization is reported.