Now days, green composite materials are now gaining popularity for the various industrial applications. It is a combination of naturally occurring reinforcement like jute, sisal, flax, hemp, and kenaf; and matrix materials like biopolymers or bio resins which have been derived from starch, and vegetable oils. It is becoming more desirable due to its properties like biodegradability, renewability and environment friendly. The present paper presents the various natural fibers and their combinations with biopolymers. The paper also reflects the key issue related to hydrophilic nature of natural fibers and their remedies for a good fiber and bio polymer adhesion. Furthermore the strategy used and major attributes of the green composite are also discussed.
The objective of the present study was to develop a robust, simple, economical and sensitive HPLC-UV method using the “quality-by-design” approach for the estimation of irinotecan (IRI) in marketed formulations. RP-HPLC method was developed by applying Box-Behnken design with Hyper-Clone (Phenomenex®) C18 column (250 × 4.6 mm id, particle size 5 µm, ODS 130 Å) as a stationary phase. Acetonitrile and 20 mmol L−1 potassium phosphate buffer (pH 2.5) containing 0.1 % triethylamine in a ratio of 45:55 % (V/V) was used as a mobile phase. The sample was injected in a volume of 20 µL into the HPLC system. UV detector at 254 nm was used to estimate and quantify IRI. Isocratic elution was opted while the flow rate was maintained at 0.75 mL min−1. The retention time of IRI was found to be 4.09 min. The responses were found to be linear for concentration range of 0.5 to 18.0 µg mL−1 and the coefficient of determination value was found to be 0.9993. Percent relative standard deviation for intra- and inter-day precisions was found in the range of 0.1 to 0.4 %. LOD and LOQ values were found to be 4.87 and 14.75 ng mL−1, resp. Robustness studies confirmed that the developed method is robust with RSD of a maximum 0.1 %. The method is simple, precise, sensitive, robust and economical making it applicable to the estimation of IRI in an injectable formulation.