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Quantum Computing In Drug Discovery: Key Highlights and Future Opportunities

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.

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.

Drug discovery has always been a time-consuming process. On an average, it takes 10-15 years and capital investments worth USD 4-10 billion to commercially launch a drug. 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.

According to the Roots Analysis market research firm, the global quantum computing market size is estimated to grow from USD 0.36 billion in 2023 to USD 1.63 billion by 2035, representing a CAGR of 13% during the forecast period 2023-2035.

The term quantum computing refers to the technology that uses laws of quantum mechanics to solve large and complex problems in a short span as compared to the computer aided drug discovery. During our research, we were able to identify the presence of about 50 software providers that are engaged in offering services across drug discovery.

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). Additionally, 16% companies have entered this domain before 2000, indicating that the market is driven by efforts of well-established players as well.

Further, it was observed that majority of players offer platform / software (98%) as a business capability followed by Quantum as a Service (69%). In addition to this 10% of the players offer platform capabilities for Drug Discovery and Drug Design.

As it is evident from the figure below, majority (86%) of the players offer target discovery / identification as a drug discovery service followed by lead optimization (63%); examples of players offering all types of drug discovery service(s) include (in alphabetic order) Allesh Biosciences Lab, Hafnium Labs, Profacgen, Qsimulate and Roviant Discovery.

In addition, the maximum number (19) of players are located in the US, followed by UK (5). Further, within the Asia-Pacific region, India emerged as the leading country, with the presence of four companies, including (in alphabetical order) Allesh Biosciences Lab, QpiAI, Qulab and Xanadu.