Andrographolide Liquisolid using Porous-Starch as the Adsorbent with Enhanced Oral Bioavailability in Rats.

Andrographolide (AGL) is the major component of Andrographispaniculata. The poor water solubility and low dissolution strongly affect its oral absorption. Liquisolid technology has been used to improve its dissolution and oral bioavailability. Liquisolid powders of AGL (AGL-LS-PSG) were obtained by firstly dissolving AGL in the mixture of NMP, PEG 6000 and Soluplus®, and solidified by absorption of the blend in porous starch. Angle of repose, Carr index and Hauser ratio presented good powder fluidity and compressibility characteristics of AGL-LS-PSG. The results of optical microscopic observation, PXRD and DSC analysis indicated that AGL has been completely adsorbed in porous starch granules and existed in an amorphous or molecularly dispersing state. AGL-LS-PSG can obviously increase the drug dissolution rate compared to commercial guttate pills and raw drug. In vivo pharmacokinetic behavior of AGL-LS-PSG was investigated following a single oral administration to rats. The Cmax (0.37 ± 0.06 µg mL-1) and AUC0-2h (13.55 ± 2.67 µg h mL-1) of AGL-LS-PSG were evidently increased compared to commercial guttate pills (Cmax = 0.30 ± 0.21 µg mL-1, AUC0-2h = 9.88 ± 3.57 µg h mL-1). This study indicated great potential of liquisolid technology in effectively improving the dissolution and bioavailability of AGL.

[Data harmonization and sharing in study cohorts of respiratory diseases].

Objective: Chronic obstructive pulmonary disease, asthma, interstitial lung disease and pulmonary thromboembolism are the most common and severe respiratory diseases, which seriously jeopardizing the health of the Chinese citizens. Large-scale prospective cohort studies are needed to explore the relationships between potential risk factors and respiratory disease outcomes and to observe disease prognoses through long-term follow-ups. We aimed to develop a common data model (CDM) for cohort studies on respiratory diseases, in order to harmonize and facilitate the exchange, pooling, sharing, and storing of data from multiple sources to serve the purpose of reusing or uniforming those follow-up data appeared in the cohorts. Methods: The process of developing this CDM of respiratory diseases would follow the steps as: ①Reviewing the international standards, including the Clinical Data Interchange Standards Consortium (CDISC), Clinical Data Acquisition Standards Harmonization (CDASH) and the Observational Medical Outcomes Partnership (OMOP) CDM; ②Summarizing four cohort studies of respiratory diseases recruited in this research and assessing the data availability; ③Developing a CDM related to respiratory diseases. Results: Data on recruited cohorts shared a few similar domains but with various schema. The cohorts also shared homogeneous data collection purposes for future follow-up studies, making the harmonization of current and future data feasible. The derived CDM would include two parts: ①thirteen common domains for all the four cohorts and derived variables from disparate questions with a common schema, ②additional domains designed upon disease-specific research needs, as well as additional variables that were disease-specific but not initially included in the common domains. Conclusion: Data harmonization appeared essential for sharing, comparing and pooled analyses, both retrospectively and prospectively. CDM was needed to convert heterogeneous data from multiple studies into one harmonized dataset. The use of a CDM in multicenter respiratory cohort studies would make the constant collection of uniformed data possible, so to guarantee the data exchange and sharing in the future.