Correlating liposomal adjuvant characteristics to in-vivo cell-mediated immunity using a novel Mycobacterium tuberculosis fusion protein:a multivariate analysis study

Objective In this study, we have used a chemometrics-based method to correlate key liposomal adjuvant attributes with in-vivo immune responses based on multivariate analysis. Methods The liposomal adjuvant composed of the cationic lipid dimethyldioctadecylammonium bromide (DDA) and trehalose 6,6-dibehenate (TDB) was modified with 1,2-distearoyl-sn-glycero-3-phosphocholine at a range of mol% ratios, and the main liposomal characteristics (liposome size and zeta potential) was measured along with their immunological performance as an adjuvant for the novel, postexposure fusion tuberculosis vaccine, Ag85B-ESAT-6-Rv2660c (H56 vaccine). Partial least square regression analysis was applied to correlate and cluster liposomal adjuvants particle characteristics with in-vivo derived immunological performances (IgG, IgG1, IgG2b, spleen proliferation, IL-2, IL-5, IL-6, IL-10, IFN-γ). Key findings While a range of factors varied in the formulations, decreasing the 1,2-distearoyl-sn-glycero-3-phosphocholine content (and subsequent zeta potential) together built the strongest variables in the model. Enhanced DDA and TDB content (and subsequent zeta potential) stimulated a response skewed towards a cell mediated immunity, with the model identifying correlations with IFN-γ, IL-2 and IL-6. Conclusion This study demonstrates the application of chemometrics-based correlations and clustering, which can inform liposomal adjuvant design.

Development of a physiologically-based pharmacokinetic model of the rat central nervous system

Central nervous system (CNS) drug disposition is dictated by a drug’s physicochemical properties and its ability to permeate physiological barriers. The blood–brain barrier (BBB), blood-cerebrospinal fluid barrier and centrally located drug transporter proteins influence drug disposition within the central nervous system. Attainment of adequate brain-to-plasma and cerebrospinal fluid-to-plasma partitioning is important in determining the efficacy of centrally acting therapeutics. We have developed a physiologically-based pharmacokinetic model of the rat CNS which incorporates brain interstitial fluid (ISF), choroidal epithelial and total cerebrospinal fluid (CSF) compartments and accurately predicts CNS pharmacokinetics. The model yielded reasonable predictions of unbound brain-to-plasma partition ratio (Kpuu,brain) and CSF:plasma ratio (CSF:Plasmau) using a series of in vitro permeability and unbound fraction parameters. When using in vitro permeability data obtained from L-mdr1a cells to estimate rat in vivo permeability, the model successfully predicted, to within 4-fold, Kpuu,brain and CSF:Plasmau for 81.5% of compounds simulated. The model presented allows for simultaneous simulation and analysis of both brain biophase and CSF to accurately predict CNS pharmacokinetics from preclinical drug parameters routinely available during discovery and development pathways.