Pharmaceuticals are necessary products that have indubitable benefits for
people's health and way of life. Following their use, there is a corresponding increase in
the production of pharmaceutical waste. We need to figure out how to lessen the
production of pharmaceutical waste and prevent its release into the environment, which
could eventually pose major health risks to the rest of the living world. If handled
incorrectly, pharmaceutical waste increases the danger, which is inversely correlated
with the active concentration of chemical components in various environmental
compartments. As a result, when drugs and their unaltered metabolites are dispersed
into the environment through several sources and channels, they may influence both
animals and humans. Finding the sources and points of entry of pharmaceutical waste
into the ecosystem is the first step in understanding pharmaceutical ecotoxicity. Several
techniques, like the Structure-Activity Relationship (SAR) and Quantitative StructureActivity Relationship (QSAR) models, help assess and manage environmental risks
caused by pharmaceutical waste. The persistency, mobility, and toxicity (PMT) of
pharmaceutical compounds have been predicted computationally using QSAR models
from OPERA QSAR, VEGA QSAR, the EPI Suite, the ECOSAR, and the QSAR
toolbox. In silico predictions have been made for molecular weight, STP total removal,
sewage treatment plant, Octanol-water partition coefficient (KOW), ready
biodegradability, soil organic adsorption coefficient, short- and long-term ecological
assessments, carcinogenicity, mutagenicity, estrogen receptor binding, and Cramer
decision tree. The adverse effects of medications on the living world, as well as risk
assessment and management, have been covered in this chapter. Several computational
methods that are employed to counteract the negative consequences of pharmaceutical
waste have also been addressed. The goal is to better understand how to minimize the
concentration of pharmaceutical waste in our environment.
Keywords: Biodegradability, Computational, Environment, Pharmaceutical waste, Risk assessment, QSAR.
