9 Nanotoxicity prediction in nanotechnology-driven drugs using QSPR modeling
Pooja A. Chawla, Reyaz Hassan Mir, Apporva Chawla, Prince Ahad Mir, Md Sadique Hussain, Sameena Ramzan, Tooba Dedmari, Roohi Mohi-ud-din · 2024
The rapid expansion of nanotechnology in drug development has ushered in innovative therapeutic approaches while simultaneously raising concerns about potential nanotoxicity. This comprehensive review provides a thorough exploration of the evolving field of quantitative structure-property relationship (QSPR) modeling as a potent tool for predicting and mitigating nanotoxicity associated with nanotherapeutic agents. The review commences by underlining the transformative impact of nanotechnology on drug design, emphasizing the critical necessity of ensuring the safety and efficacy of nanomedicines. QSPR modeling emerges as an advanced computational approach harnessing physicochemical properties, structural descriptors, and toxicity endpoints to anticipate and comprehend nanotoxicity. The core of this review delves into the principles and methodologies of QSPR modeling, intricately describing the process of descriptor selection, dataset compilation, and model development. It scrutinizes the versatility of QSPR models in predicting a wide array of nanotoxicological endpoints, encompassing cellular responses, biodistribution patterns, and organ-specific toxicity profiles. Furthermore, the article underscores the significant clinical implications of QSPR modeling, discussing its potential for expediting nanotoxicity assessment during drug development, reducing reliance on animal testing, and facilitating regulatory approvals. It accentuates the pivotal role of QSPR modeling in optimizing nanotherapeutic formulations and minimizing adverse effects. Concluding on a forward-looking note, the review underscores the growing importance of QSPR modeling as an indispensable tool within the field of nanomedicine. It calls for sustained collaborative efforts to expand predictive models, address data gaps, and enhance our comprehension of nanotoxicity mechanisms. In summary, this review navigates the landscape of QSPR modeling for nanotoxicity prediction in the realm of nanotechnology- driven drugs, offering profound insights into its implications for advancing safe and efficacious nanotherapeutics.