Detection of Capsule Tampering by Near-Infrared Reflectance Analysis

The growing incidence of product tampering has brought to attention the need for a rapid, reliable, Inexpensive, noninva-sive, and nondestructive method of screening. Such a method, based on near-infrared reflectance analysis (NIRA), Is presented here for the detection of adulterated nonprescrlption drugs. The method relies upon a nonparametric clustering algorithm known as the BEAST (bootstrap error-adjusted single-sample technique). Specially designed sampling reflectors have been constructed to enable rapid and convenient measurement of capsules. A right-circular conical reflector has been found to be optimal for this purpose; the capsules fit directly into the reflector and need not be opened for analysis. A variety of foreign substances have been successfully detected in capsules by probing the capsule contents directly through the gelatin walls; these substances Include Fe₂0₃, Al shavings, NaF, As₂0₃, NaCN, and KCN. The NIRA response for KCN is linear down to a detection limit of 2.6 mg (0.4% of capsule weight). An incidental advantage in the use of the conical reflector is that the response is dependent upon not only the mass of adulterant but its location within the capsule. The ability to noninvasively determine the location of foreign substances within capsules might be Important in forensic applications of the method.