Computational Model of Human Body Based Upon the Genetic Analysis for Drug Development and Treatment

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The proposed computational model of the human body is going to revolutionize the field of medicine. It would be deux ex machina of medicine. From now on, instead of treatment based upon trial and error, we would be developing the precise treatment using the model derived from the genome of the given patient.
The following steps would be followed:
1. A sample of the nucleated cells is taken from the patient.
2. The patient's DNA is sequenced using one of the modern fast sequencing methods.
3. All the known genes are identified.
5. The models of the differentiated cells are developed on the basis of the known differentiation patterns. Hence, we would know what set of proteins is expressed for each differentiated cell.
6. Further epigenetic analysis of the identified genes is done on the basis of methylation and alkylation of the identified genes. At the initial development stages, it might be necessary to take a biopsy of the organ cells to identify the actual gene expression using mRNA. With improvement of the model and collection of correlation data between the the epigenetic / a priori cell differentiation model with the actual gene expression, biopsies would become increasingly rare. There is another path of the virtual biopsies, where the proteins and nucleic acids assembling into a biological computer are introduced into the patient's body, giving us non-invasively the genetic and biochemical information of interest.
7. The primary, secondary, tertiary and quaternary structures of the proteins expressed in the patient's cells are computed. The functionally important proteins and protein-based compounds, such as the cell surface receptors, are identified. Hence, we accomplish a set of models of the functionally differentiated cells.
8. Computational chemistry models are compiled for all of the identified cell surface receptors, to find out what substances they would interact with.
8. Next, from the cell models we create the organ models.
9. The organ models are connected via endocrine and paracrine virtual pathways. The foregoing computational chemistry models of the receptors show what cells are sensitive to the chemical signals produced by other cells.
10. Now, we correct the model for all the cellular pathologies identified by the biochemical analyses of the patient.
11. We are at the point where we can use the model to device the treatment and to identify the side effects. Let's say the patient is sick because of bacterial infection. We input the chemical representation of bacterial toxins into the model, and almost instantly see how the patient's cells are affected and what physiological pathways are impacted. We also input the proposed treatment, and see all the side effects. The model can even compute the optimal treatment.

The beauty of this system is that it does not need to rely on any identified physiological pathways; it relies instead on computational chemistry. It is even able to identify the new pathways. Also, it could be used for automatic development of the new drugs, and for design of the highly individualized drugs targeting a particular patient.


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  • Name:
    Gregory Steshenko
  • Type of entry:
  • Profession:
  • Number of times previously entering contest:
  • Gregory's favorite design and analysis tools:
    Matlab, Mathematica, MathCAD, PCSpice
  • Gregory's hobbies and activities:
    Hiking, bicycling
  • Gregory is inspired by:
    Scientific exploration of the world we live in, and desire to decrease suffering
  • Patent status: