Predictive Modeling of Micellar Solubilization by Single and Mixed Nonionic Surfactants.

Micellar solubilization is an important concept in the delivery of poorly water-soluble drugs. The rational selection of the type and the amount of surfactant to be incorporated in a formulation require comprehensive solubility studies. These studies are time and material demanding, both of which are scarce, especially during late discovery and early development stages. We hypothesized that, if the solubilization mechanism or molecular interaction is similar, the solubilization capacity ratio (a newly defined parameter) is dictated by micellar structures, independent of drugs. We tested this hypothesis by performing solubility studies using 8 commonly used nonionic surfactants and 17 insoluble compounds with diverse characteristics. The results show a striking constant solubilization capacity ratio among the 8 nonionic surfactants, which allow us to develop predictive solubility models for both single and mixed surfactant systems. The vast majority of the predicted solubility values, using our developed models, fall within 2-fold of the experimentally determined values with high correlation coefficients. As expected, systems involving ionic surfactant sodium dodecyl sulfate, used as a negative control, do not follow this trend. Deviations from the model, observed in this study or envisioned, were discussed. In conclusion, we have established predictive models that are capable of predicting solubility in a wide range of nonionic micellar solutions with only 1 experimental measurement. The application of such a model will significantly reduce resource and greatly enhance drug product development efficiency.

A novel intravenous vehicle for preclinical cardiovascular screening of small molecule drug candidates in rat.

Screening novel, poorly soluble small-molecule candidates for cardiovascular liabilities represents a key challenge in early drug discovery. This report describes a novel vehicle composed of 20% N,N-Dimethylacetamide (DMA)/40% Propylene glycol (PG)/40% Polyethylene Glycol (PEG-400) (DPP) for administration of new chemical entities (NCEs) by slow intravenous (i.v.) infusion in a preclinical anesthetized rat model. The vehicle was designed considering both available excipient safety information and solubilization potential for poorly soluble NCEs. DPP solubilized 11 drugs, 8 of which were insoluble in 5% dextrose in water (D5W), and 5 insoluble in PEG-400 to a target concentration of 30mg/mL. DPP elicits no adverse cardiovascular responses in the anesthetized rat model despite containing 40% PEG-400, a commonly used organic solvent which elicits hypertension and bradycardia that often confounds interpretation of drug effects. Three compounds demonstrating adequate solubility in both DPP and D5W were screened in the anesthetized rat model. When normalized to plasma exposure, atenolol, sotalol and enalaprilat exhibited comparable mean arterial pressure, heart rate, and cardiac contractility responses regardless of formulation. While the antihypertensive effect of nifedipine was evident with both DPP and PEG-400 formulations, pressor effects from PEG-400 confounded interpretation of the magnitude of nifedipine's response. Plasma concentrations of atenolol and enalaprilat were greater in D5W formulation whereas sotalol exposures were greater when using DPP as a vehicle. These results demonstrate the utility of DPP as an intravenous vehicle for formulating poorly soluble compounds in early preclinical screening for cardiovascular safety studies.

A pH-dilution method for estimation of biorelevant drug solubility along the gastrointestinal tract: application to physiologically based pharmacokinetic modeling.

Physiologically based pharmacokinetic (PBPK) modeling tools have become an integral part of the modern drug discovery-development process. However, accurate PK prediction of enabling formulations of poorly soluble compounds by applying PBPK modeling has been very limited. This is because current PBPK models rely only on thermodynamic drug solubility inputs (e.g., pH-solubility profile) and give little consideration to the dynamic changes in apparent drug solubility (e.g., supersaturation) that occur during gastrointestinal (GI) transit of an enabling formulation of a water insoluble drug. Moreover, biorepresentative and predictive in vitro tools to measure formulation dependent solubility changes during GI transit remain underdeveloped. In this work, we have developed an in vitro dual pH-dilution method based on rat physiology to estimate the apparent drug concentration in solution along the GI tract during release from solubility enabling formulations. This simple dual pH-dilution method was evaluated using various solubility enabling formulations (i.e., cosolvent solution, amorphous solid dispersions) made using a model early development drug candidate with poor aqueous solubility. The in vitro drug concentration-time profiles from the enabling formulations were used as solubility inputs for PBPK modeling using GastroPlus software. This resulted in excellent predictions of the in vivo oral plasma concentration-time profiles, as compared to using the traditional inputs of thermodynamic pH-solubility profiles. In summary, this work describes a novel in vitro method for facile estimation of formulation dependent GI drug concentration-time profiles and demonstrates the utility of PBPK modeling for oral PK prediction of enabling formulations of poorly soluble drugs.