Maity, T and Balachandran, AK and Krishnamurthy, LP and Nagar, KL and Upadhyayula, RS and Sengupta, S and Maiti, PK (2024) Data-Driven Approaches to Predict Dendrimer Cytotoxicity. In: ACS Omega, 9 (23).
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Abstract
Dendrimers are employed as functional elements in contrast agents and are proposed as nontoxic vehicles for drug delivery. Toxicity is a property that is to be evaluated for this novel class of bionanomaterials for in vivo applications. The current research is hampered due to the lack of structured data sets for toxicity studies for dendrimers. In this work, we have built a data set by curating literature for toxicity data and augmented it with structural and physicochemical features. We present a comprehensive, feature-rich database of dendrimer toxicity measured across various cell lines for prediction, design, and optimization studies. We have also explored novel computational approaches for predicting dendrimer cytotoxicity. We demonstrate superior outcomes for toxicity prediction using essential regression in the space of small data sets. © 2024 The Authors. Published by American Chemical Society.
| Item Type: | Journal Article |
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| Publication: | ACS Omega |
| Publisher: | American Chemical Society |
| Additional Information: | The copyright for this article belongs to Authors. |
| Department/Centre: | Division of Physical & Mathematical Sciences > Physics |
| Date Deposited: | 12 Aug 2024 05:59 |
| Last Modified: | 12 Aug 2024 05:59 |
| URI: | http://eprints.iisc.ac.in/id/eprint/85264 |
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