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Quantitative Structure–Property Relationship Approach in Formulation Development: an Overview

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Abstract

Chemoinformatics is emerging as a new trend to set drug discovery which correlates the relationship between structure and biological functions. The main aim of chemoinformatics refers to analyzing the similarity among molecules, searching the molecules in the structural database, finding potential drug molecule and their property. One of the key fields in chemoinformatics is quantitative structure–property relationship (QSPR), which is an alternative process to predict the various physicochemical and biopharmaceutical properties. This methodology expresses molecules via various numerical values or properties (descriptors), which encodes the structural characteristics of molecules and further used to calculate physicochemical properties of the molecule. The established QSPR model could be used to predict the properties of compounds that have been measured or even have been unknown, which ultimately accelerates the development process of a new molecule or the product. The formulation characteristics (drug release, transportability, bioavailability) can be predicted with the integration of QSPR approach. Therefore, QSPR modeling is an emerging trend to skip conventional drug as well as formulation development process. The current review highlights the overall process involved in the application of the QSPR approach in formulation development.

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Abbreviations

1D:

One-dimensional

2D:

Two-dimensional

3D:

Three-dimensional

AHC:

Atomic hybrid component

AHP:

Atomic hybrid polarizability

ANN:

Artificial neural network

ASNN:

Associative neural network

MLR:

Multiple linear regression

PCA:

Principal component analysis

PLS:

Partial least square

QSAR:

Quantitative structure–activity relationship

QSPR:

Quantitative structure–property relationship

RMSE:

Root mean square error

SAR:

Structure–activity relationships

SMILES:

Simplified molecular input line entry specification

vdW:

van der Waals

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Acknowledgments

There was no funding received from any agency for the preparation of this article.

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Authors and Affiliations

  1. Department of Pharmaceutics, Satara College of Pharmacy, Satara, Maharashtra, 415004, India

    Ajit S. Kulkarni

  2. Department of Pharmaceutics, PDEA’s Shankarrao Ursal College of Pharmaceutical Sciences and Research Center, Kharadi, Pune, Maharashtra, 411014, India

    Amit J. Kasabe

  3. Research Scholar, Shivaji University, Vidyanagar, Kolhapur, Maharashtra, 416004, India

    Amit J. Kasabe

  4. Department of Pharmaceutical Chemistry, Bharati Vidyapeeth College of Pharmacy, Kolhapur, Maharashtra, 416013, India

    Manish S. Bhatia & Neela M. Bhatia

  5. Department of Pharmaceutics, BVDU Poona College of Pharmacy, Pune, Maharashtra, 411038, India

    Vinod L. Gaikwad

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  1. Ajit S. Kulkarni
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Correspondence to Ajit S. Kulkarni.

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Kulkarni, A.S., Kasabe, A.J., Bhatia, M.S. et al. Quantitative Structure–Property Relationship Approach in Formulation Development: an Overview. AAPS PharmSciTech 20, 268 (2019). https://doi.org/10.1208/s12249-019-1480-2

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