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A smart linker is a crucial element throughout the creation of polymer-drug conjugates. It binds different portions or subunits altogether and may be freed by a suitable trigger, resulting in localized drug distribution and enhanced bioavailability. PEG (Polyethylene Glycol) linkers can be synthesized chemically by specifically adding functionalized groups with chemical reactivity at certain structural ends of PEG. Because they may integrate a diverse range of groups, PEG linkers are frequently utilized in molecular biology experiments due to increased water solubility, excellent biocompatibility, and non-immunogenicity. In present work, we have included various linkers which are incorporated in design of PDC’s (polymer drug conjugates) of pegylated NSAIDs (nonsteroidal anti-inflammatory drugs) through PEGylation. The main focus was to investigate the pharmacodynamic changes brought about by these linker’s conjugated to model drug Ibuprofen (IB1-IB7). The tools used for the analysis are Argus Lab 4.0 for molecular docking and pkCMS as ADMET prediction tool. The outcome of this work was, establishment of a method for choosing suitable linker for designing PDC’s for various NSAIDs and other bioactive agents.

Reaction optimization has been a tedious task for the research chemist for very long and many approaches has been employed to achieve the best reaction condition resulting in highest yield. As an answer to this problem the statistical optimization approach has better chances of providing most acceptable solution to it. Through, our present work we have found that among other statistical approaches the custom design approach is the best methodology to be adopted for optimizing any synthetic reaction. The oxidative transformation of polyethylene glycol into polyethylene carboxylate by the use of TEMPO, NaClO and KBr; has been optimized by identifying the key factors affecting the yield and exact ratios of them to achieve highest possible yield. Here, we have employed custom design approach to further limit the experimental runs and yet find a better possible combination of reagents and conditions to get highest yield with maximum purity. This method has reduced the number of runs to only 16, which was 1024 in case of the traditional OVAT approach and in full factorial approach it was 64 runs. Thus, custom design method of DoE has been satisfactorily utilized for optimizing the oxidative derivatization of polyethylene glycol to polyethylene carboxylate.