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Recommendations for developing predictive and systems medicine for drug discovery in India


Affiliations
1 Centre for Predictive Human Model Systems, Atal Incubation Centre, Centre for Cellular and Molecular Biology, Hyderabad 500 039, India, India
 

Biological phenomena often emerge based on the inter­action between pathways, cells and tissues, rather than a single set of genes or proteins. This has led to the emergence of systems medicine. Predictive medicine is another emerging field that aims to predict the disease onset, progression, deterioration, risk and treatment strategies. In this article, we review how systems and computational tools are being used globally in the drug discovery pipeline. With increase in the amount of biological data being generated, data integration is also a critical aspect in systems biology. Towards this, we describe the use of various data integration frameworks. We also analyse the global and local funding patterns, regulations and challenges and propose recommendations to enable India as a key player in this area

Keywords

Adverse outcome pathways, computational tools, drug discovery, predictive medicine, systems biology.
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  • Recommendations for developing predictive and systems medicine for drug discovery in India

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Authors

Surat Parvatam
Centre for Predictive Human Model Systems, Atal Incubation Centre, Centre for Cellular and Molecular Biology, Hyderabad 500 039, India, India
Sham Bharadwaj
Centre for Predictive Human Model Systems, Atal Incubation Centre, Centre for Cellular and Molecular Biology, Hyderabad 500 039, India, India

Abstract


Biological phenomena often emerge based on the inter­action between pathways, cells and tissues, rather than a single set of genes or proteins. This has led to the emergence of systems medicine. Predictive medicine is another emerging field that aims to predict the disease onset, progression, deterioration, risk and treatment strategies. In this article, we review how systems and computational tools are being used globally in the drug discovery pipeline. With increase in the amount of biological data being generated, data integration is also a critical aspect in systems biology. Towards this, we describe the use of various data integration frameworks. We also analyse the global and local funding patterns, regulations and challenges and propose recommendations to enable India as a key player in this area

Keywords


Adverse outcome pathways, computational tools, drug discovery, predictive medicine, systems biology.

References





DOI: https://doi.org/10.18520/cs%2Fv123%2Fi11%2F1317-1326