Predicting the biodegradability of active pharmaceutical ingredients using freely available in silico models: new application area or impossible?

The development of environmentally friendly alternatives to pharmaceuticals and active pharmaceutical ingredients (APIs) is increasingly necessary, because pharmaceutical agents can persist in the environment, cause ecotoxicological effects, and require high biodegradability due to increasing regulatory requirements. Experimental classification into biodegradable or non-biodegradable according to OECD Guideline 301 is reliable but very time- and resource-intensive, hindering efficient pharmaceutical development. In silico models offer a promising alternative by predicting environmental biodegradability computationally. However, their suitability for APIs remains uncertain. This study compares the performance of different in silico models for determining biodegradability of APIs. using a test data set of 50 different pharmaceuticals and APIs with experimentally validated biodegradability data (OECD 301D). The applicability domains (AD) of the models were examined, and the performance parameters - accuracy, sensitivity, and specificity - were calculated.