Research paper Non-destructive methods of characterization of risperidone solid lipid nanoparticles Ziyaur Rahman, Ahmed S. Zidan, Mansoor A. Khan * Division of Product Quality and Research, Center of Drug Evaluation and Research, Food and Drug Administration, Silver Springs, MD, USA article info Article history: Received 25 February 2010 Accepted in revised form 7 May 2010 Available online 12 May 2010 Keywords: Risperidone Compritol 888 ATO SLN NIR NIR-CI abstract The objective of this investigation is to evaluate compositional variations and their interaction of the solid lipid nanoparticle (SLN) formulation of risperidone using response surface methodology of design of experiment (DOE) and subsequently, characterize the SLN by non-destructive methods of analysis. Box–Behnken DOE was constructed using drug (X 1 ), lipid (X 2 ) and surfactant (X 3 ) level as independent factors. Compritol 888 ATO and sodium lauryl sulphate were used as lipid and surfactant, respectively. The SLN was prepared by solvent evaporation method and characterized by transmission electron microscopy (TEM), differential scanning calorimetry (DSC), X-ray powder diffraction (XRD), fourier infra- red spectroscopy (FTIR), near infrared spectroscopy (NIR) and NIR-chemical imaging (NIR-CI). Responses measured were entrapment efficiency (Y 1 ), D 90 (Y 2 ), zeta potential (Y 3 ), burst effect (Y 4 ) and cumulative release in 8 h (Y 5 ). Statistically significant (p < 0.05) effect of X 1 on the Y 1 , Y 2 , Y 3 and Y 4 were seen. FTIR revealed no interaction between risperidone and compritol 888 ATO. TEM showed spherical and smooth surface SLN. Compritol retained its crystalline nature in the SLN formulation revealed by DSC and XRD studies. Homogenous distribution of risperidone and compritol 888 ATO was revealed by NIR-CI. Princi- pal component analysis (PCA) and partial least square (PLS) were carried out on NIR data of SLN formu- lation. PLS showed correlation coefficient > 0.996 for prediction and calibration model of both risperidone and compritol 888 ATO. The accuracy of models in predicting risperidone and compritol 888 ATO were 1.60% and 11.27%, respectively. In conclusion, the DOE reveals significant effect of drug loading on SLN characteristics, and chemometric models based on NIR and NIR-CI data provided non-destructive method of estimation of components of SLN. Published by Elsevier B.V. 1. Introduction Delivering therapeutic agents directly to the diseased organ or tissue has been a challenge for formulation scientist. It is ex- pected that a good delivery strategy to a disease organ will im- prove the therapeutic index of a drug and reduce the side effects associated with it. One such organ is brain, and physicians have an acute need to deliver drugs directly to the brain to treat the conditions such as Parkinsonism, Alzheimer, stroke and glio- mas. The traditional methods with conventional dosage forms are ineffective or associated with severe side effects of a drug. Over the decades, many strategies have been devised to enhance delivery of drug to brain in order to improve therapeutic index of a drug. Both invasive and non-invasive techniques have been re- ported. Invasive methods include intraventricular [1] or intracere- bral [2] infusion and intracerebral implant for controlled drug release [3]. Non-invasive techniques are prodrugs [4], conjugation with antibodies [5], alternate route of administration (intranasal administration) [6] and colloidal drug delivery systems. Among the reported strategies, colloidal delivery system seems to be gaining momentum because of their ability to deliver drugs suc- cessfully to brain without altering the blood brain barrier prop- erty. Colloidal delivery systems reported for brain delivery systems are polymeric micelles [7], liposomes [8], polymeric nanoparticles [9] and solid lipid nanoparticles [10]. The SLN com- bines the advantages of polymeric nanoparticles, liposomes, fat emulsion while avoiding their disadvantages [10]. Some advanta- ges offered by SLN are stability of even up to three years [11], high drug payload, scalability, sterilizability [12,13] and feasibility of delivering both lipophilic and hydrophilic drugs. The carrier lipids are mostly GRAS (generally regarded as safe). The reasons for efficient delivery of drug SLN are due to enhanced retention in brain–blood capillaries resulting in an enhanced concentration gradient across the blood brain barrier that leads to opening of tight junction and transcytosis [10]. Traditional pharmaceutical development involves trial and er- ror method for the process and formulation optimization. Pharma- ceutical development is the process of design of quality product and understanding the process that consistently deliver the 0939-6411/$ - see front matter Published by Elsevier B.V. doi:10.1016/j.ejpb.2010.05.003 * Corresponding author. Address: FDA/CDER/DPQR, White Oak, LS Building 64, Room 1070, 10903 New Hampshire Ave., Silver Spring, MD 20993-002, USA. Tel.: +1 301 796 0016; fax: +1 301 796 9816. E-mail address: Mansoor.Khan@fda.hhs.gov (M.A. Khan). European Journal of Pharmaceutics and Biopharmaceutics 76 (2010) 127–137 Contents lists available at ScienceDirect European Journal of Pharmaceutics and Biopharmaceutics journal homepage: www.elsevier.com/locate/ejpb