Cocrystal solubility-pH and drug solubilization capacity of sodium dodecyl sulfate – mass action model for data analysis and simulation to improve design of experiments

This review discusses the disposition of the anionic surfactant, sodium dodecyl sulfate (SDS; i.e., sodium lauryl sulfate), to solubilize sparingly-soluble drugs above the surfactant critical micelle concentration (CMC), as quantitated by the solubilization capacity (k). A compilation of 101 published SDS k values of mostly poorly-soluble drug molecules was used to develop a prediction model as a function of the drug’s intrinsic solubility, S0, and its calculated H-bond acceptor/donor potential. In almost all cases, the surfactant was found to solubilize the neutral form of the drug. Using the mass action model, the k values were converted to drug-micelle stoichiometric binding constants, Kn, corresponding to drug-micelle equilibria in drug-saturated solutions. An in-depth case study (data from published sources) considered the micellization reactions as a function of pH of a weak base, B, (pKa 3.58, S0 52 μg/mL), where at pH 1 the BH.SDS salt was predicted to precipitate both below and above the CMC. At low SDS concentrations, two drug salts were predicted to co-precipitate: BH.Cl and BH.SDS. Solubility products of both were determined from the analysis of the reported solubility-surfactant data. Above the CMC, in a rare example, the charged form of the drug (BH+) appeared to be strongly solubilized by the surfactant. The constant for that reaction was also determined. At pH 7, the reactions were simpler, as only the neutral form of the drug was solubilized, to a significantly lesser extent than at pH 1. Case studies also featured examples of solubilization of solids in the form of cocrystals. For many cocrystal systems studied in aqueous solution, the anticipated supersaturated state is not long-lasting, as the drug component precipitates to a thermodynamically stable form, thus lowering the amount of the active ingredient available for intestinal absorption. Use of surfactant can prevent this. A recently-described method for predicting the solubility product of cocrystals (coupled with predicted k values described here) allowed for simulations of solubility-pH speciation profiles of cocrystal systems in the presence of SDS. Well in advance of any actual measurements, these simulations can be used to probe conditions favorable to the design of cocrystal experiments where SDS stabilizes cocrystal suspensions against drug precipitation over a predicted range of pH values.

Inferring gene regulatory networks using a time-delayed mass action model

This paper demonstrates a new time-delayed mass action model which applies a set of delay differential equations (DDEs) to represent the dynamics of gene regulatory networks (GRNs). The mass action model is a classical model which is often used to describe the kinetics of biochemical processes, so it is fit for GRN modeling. The ability to incorporate time-delayed parameters in this model enables different time delays of interaction between genes. Moreover, an efficient learning method which employs population-based incremental learning (PBIL) algorithm and trigonometric differential evolution (TDE) algorithm TDE is proposed to automatically evolve the structure of the network and infer the optimal parameters from observed time-series gene expression data. Experiments on three well-known motifs of GRN and a real budding yeast cell cycle network show that the proposal can not only successfully infer the network structure and parameters but also has a strong anti-noise ability. Compared with other works, this method also has a great improvement in performances.