We envisage the potential of Digital Twins for Drug Discovery and Development.
Concept of Digital Twins to increase the speed and efficiency of Drug Discovery has started to gain traction [1,2,3,4,5].The concept of Digital Twins involves mimicking the real world conditions on a computer. Say, for example, we want to test new drugs on cell lines, organs or whole humans, usually on giving the drug, some phenotypes are measured such as protein inhibition, cell death, organ functioning etc. Imagine giving such large amount of drugs, one by one, and measuring such phenotypes. Such an experiment can be time consuming as well as cost intensive. Typically a High Throughput Screening campaign of 1 million compounds will cost anywhere from $500000 to $1000000 [6].
Here, the concept of Digital Twins comes where such an experiment can be done insilico, at the same time measuring lots of phenotypic readouts. Such Digital Twins models can reduce the cost of screening as well as time. Hits found from such insilico screening methodologies can then be tested in experiments etc.
With the rapid use of AI technologies combined with high throughput datasets available for various phenotypes[7,8,9,10], such models can be made very easily and deployed as websites.
Link to our such efforts is below [11] where our endeavors are to add more and more phenotypes to ultimately make the complete Digital Twin.
Would love to hear you inputs on this.
Parts of the image Adapted from Source: N. Cary/Science, starline/freepik
References: [1]https://www.forbes.com/sites/ganeskesari/2021/09/29/meet-your-digital-twin-the-coming-revolution-in-drug-development/?sh=4c43846c745f
[3]https://www.nature.com/articles/d43747-022-00108-3
[4]Laubenbacher, R., Niarakis, A., Helikar, T. et al. Building digital twins of the human immune system: toward a roadmap. npj Digit. Med. 5, 64 (2022). https://doi.org/10.1038/s41746-022-00610-z
[5] Laubenbacher, R., Sluka, J. P., and Glazier, J. A., “Using digital twins in viral infection”, <i>Science</i>, vol. 371, no. 6534, pp. 1105–1106, 2021. doi:10.1126/science.abf3370.
[6]https://www.sciencedirect.com/science/article/abs/pii/S136759310600086X?via%3Dihub [7]https://elifesciences.org/articles/47381#:~:text=Big%20data%20enable%20biologists%20to,2015%3B%20Canali%2C%202019).
[8]https://www.nature.com/articles/498255a
[9]https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-3225-3
[10]https://www.nature.com/articles/d41586-018-02174-z
[11]http://drugdiscoverer.datadiscover.co.in/
[12]Parts of the image Adapted from Source: N. Cary/Science, starline/freepik
Rajat Anand (wrote on 6th July 2022): Great Article pointing towards potential of BIG Data in Drug Discovery
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