It involves various processes such as target identification, validation, hit generation, hit to lead and lead optimization. Whereas development include optimization and formulation, clinical trials and final approval by authorized regulatory. However, despite of the advances in technology drug discovery process is still considered to be complex, expensive and lengthy. In order to address such concerns, drug developers are shifting their focus from traditional techniques to the use of novel discovery techniques. Presently, Quantum Computing has emerged as one of the prominent technologies. The use of quantum computing has shown to help the drug developers in selecting potential lead candidates, having the desired physiochemical and pharmacokinetic properties, without having to conduct extensive screening procedures.
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Quantum computing is a process, using law of quantum mechanics to solve large and complex problems in short span as compared to the computer aided drug discovery. Currently, there are several quantum computing related approaches that are being used in the drug discovery process alone, such as structure-based drug design, fragment-based drug discovery and ligand-based drug discovery. The predictive power of quantum computing has proven to reduce the complexity, cost and time investment in drug discovery procedure by allowing researchers to bypass the random screening of billions of molecules in a short span of time
Advantages of Quantum Computing in Drug Discovery:
- Faster Computation: It has a potential to perform computation at much higher rate. It is useful in target identification by enabling its deeper exploration of complex therapeutic area
- Cost Benefits: It has capability to allow cost effective analysis. It reduces the expensive lab testing by enhancing the screening accuracy of the targeted molecules.
- Facilitate the design of Clinical Trials: Quantum computing accelerate the design of clinical trial which. further helps in building virtual patients for clinical trials. This potentially reduces time of trials and increasing quality.
- Reduce discovery timeline: It accelerates the high throughput screening of multiple targeted molecules at a given time hence reducing the discovery timeline of drugs.
- Possible modeling of complex molecules: It helps molecular modelers to achieve new level of accuracy by modeling complex molecule interaction. It focuses on different target area and increases the affinity towards the targeted molecules.
Majority of the quantum computing software providers (45%) engaged in this domain were established post-2016. This is indicative of the growing interest of stakeholders in this domain. Examples of recently established companies include (post-2019, in alphabetical order) Algorithmiq (2020), Kuano (2020), Polaris Quantum Biotech (2020), Qubit Pharmaceuticals (2020) and Qunova Computing (2021). Hence, it can be concluded that players offering quantum computing services in drug discovery have now become an integral part of the pharmaceutical industry. Furthermore, considering the various active initiatives being undertaken by players based in this domain, we are led to believe that the opportunity for stakeholders in this niche, upcoming, industry is likely to grow at an exponential pace in the foreseen future.
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