**3. Computational models for drug development**

Every patient and disease are different. The personalized treatment approach can be better for each patient requires. The development of individual mechanistic models of the disease process offers the possibility of attaining truly personalized drug-based therapy and diagnosis. At this point, computational methods have provided exciting contributions to pharmaceutical research and development. The need for individual drug design enhances the importance of computational models. Infrared (IR), ultraviolet (UV) and nuclear magnetic resonance (NMR) spectra of the molecule to be predicted, are important and generated by computational approaches in order to characterize molecular structure. The compatibility of the target protein active site with the small molecule (or ligand) is examined, so more effective molecules could be designed by this way [6].

Computer-aided drug design has been established as a valuable tool for the design of new molecules, with many success stories since the 1980s. Pharmaceutical companies have invested substantially in bioinformatics approaches, and it has been predicted that such methodologies will have an important role in pharmacogenomics and personalized medicine. The American Food and Drug Administration (FDA) accepted and expressed the importance of new biomarkers and radiopharmaceuticals for personalizing treatments [7].

Mathematical models of drug design are used to guide drug research and development. Computational models provide the identification of the factors involved in the absorption, distribution, metabolism, elimination and access to the target region of the chemical components. It also exposes the dynamics involved in the interaction of the compounds with the target (receptor, enzyme, etc.,). These models are effective in analyzing the fate of drugs that have undergone biotransformation. It helps us to comment on the undesirable effects or toxic effects of drugs and to help us explain drug-drug interactions. The concept of virtual clinical trials and the integrated use of *in silico*, *in vitro* and *in vivo* models in preclinical development could lead to significant gains in efficiency and order of magnitude increases in the cost effectiveness of drug development and approval [8].

The targeting agent is used as a starting point for the design of computerassisted drug active substance. Examples of targeting agents include receptors, enzymes, nucleic acids etc. Natural endogenous substances or drugs may be effectors that occupy the effective surface of the targeting agent and affect the target positively or negatively. Computer aided drug molecule design and development studies are examined in two groups:

	- Quantitative structure-activity relationships analysis (QSAR)
	- Pharmacophore analysis
	- Molecular docking
	- Based drug design

It is aimed to interpret the structure of receptors by using the structure of molecules and acting on ligand structure. In method based on the target structure, it is aimed to design molecules that can act on the basis of the known receptor structure [6].

In summary, computational models can be used to simulate complex situations prior to testing in reality, allowing us to make these inevitable mistakes and helping us to successfully avoid their deleterious impacts of new proposed drugs.
