Janifha Evangeline | Sunday, 22 May 2022
The development of molecular formulations which become drugs for treating diseases is at the center of the pharmaceutical industry.
Development is so significant and fundamental that the pharma spends a total of fifteen percent of its sales on Research & Development. This is a large amount of money which accounts for more than twenty percent of total Research & Development spending across industries in the global economy.
This investment goes in tandem with innovation. It needs to improve the Research & Development process. Furthermore, pharma companies for more than a decade have been early adopters of computational chemistry’s digital tools. These include density functional theory and molecular dynamics simulations. Most recently, pharma Research & Development has taken advantage of advanced technologies such as artificial intelligence, quantum computing, and VR.
Quantum Computing in Drug Discovery Although technologists have been talking about the promise of quantum computing for decades, it has always looked just beyond the grip of real-time applications. However, since the list of companies operating quantum computers continue to grow, this has changed significantly over the last few years. We are observing an exponential jump in the number of qubits in each system, and the kinds of applications in which they can be utilized, as these enterprises build quantum systems. Polaris Quantum Computing has built the first-ever drug discovery platform using a quantum computer, making the discovery process 10x faster.
While keeping costs efficient, the company’s platform & technology allows them to scan a billion molecules from a large chemical space. Without the need for multiple optimization cycles, the company finds the same or better molecules faster by utilizing ML, AI & Quantum computing.
Implementing quantum computing at the vanguard of computer-aided drug design, Polaris, for performing protein targeting simulations which are much faster than the present solutions, which are available to pharmaceutical companies & biotech researchers. "The world of drug discovery is on the cusp of a revolution that will be driven by vanguard technologies," said POLARISqb, CEO, Shahar Keinan. "At POLARISqb we have built our Tachyon platform that utilizes quantum computing to shorten drug design timelines by orders of magnitude, targeting a variety of diseases, disease modalities, and protein families. By using the increased ability of quantum annealers to shorten optimization timelines, we are able to address chemical libraries that number in the billions and target molecules with specific properties in a matter of minutes, rather than a matter of months."
The company is building a vast portfolio of lead molecules as well as scaling chemical space to scan billions of molecules while running multiple concurrent drug discovery projects.
Artificial Intelligence in drug discovery Over the last decade, Artificial Intelligence has been making inroads in drug discovery for a good part. Pharma companies have to plan for a future in which AI is routinely used in drug discovery, given the transformative potential of AI. Also, new players are scaling up fast as well as creating significant value but the applications are diverse & pharma companies need to find out
where and how AI can most add value for them. “The improved ability to analyze, understand and apply a wealth of critical data in the drug design and implementation process is made possible by AI,” says Anton Dolgikh, Head of AI, Healthcare and Life Sciences at DataArt. Artificial Intelligence can deliver value in small-molecule drug discovery in 4 ways mainly. These include access to new biology, better success rates, and improved/novel chemistry. While the pharma sector has only recently acknowledged the potential of Artificial Intelligence, projects still routinely need 2000-3000 molecules to be made over years prior to a single compound suitable for clinical testing being trialed.
AI for designing & optimizing molecular properties in parallel One such full-stack AI drug discovery company that focuses on implementing AI design & precision data generation is Exscientia. Incepted in 2012, Exscientia is leading the development of a new discipline; pharmatech which is at the interface of advanced AI application and complex drug discovery.
Exscientia AI directly challenges the aforementioned metric by needing every newly designed molecule for adding the maximum information and at the same time shortening the path to a clinical molecule. Implementing Artificial Intelligence for designing & optimizing molecular properties in parallel, rather than sequentially, raises the likelihood of discovering a candidate with exclusively balanced pharmacology which will offer therapeutic benefit in the clinic.
Virtual Reality in drug discovery For decades, to help visualize molecular structures, scientists have been implementing computer systems with projector screens, software, and computer monitors which required the use of 3D glasses.These methods were not only complex, tedious, & expensive, but they lacked the immersive and intuitive quality of Virtual Reality, which can also help scientists collaborate.Some scientists expect Virtual Reality would become a widespread tool, that would help to shorten the years-long drug design as well as the discovery process and potentially get drugs to market faster. In virtual reality, drug molecules & proteins that are color-coded by scientists loom large.
Scientists could grab the structures of drug molecules and proteins and enlarge them as well as get a closer positioning by using hand controllers. “It allows us to democratize the process of structural biology and drug design, which certainly will speed up the ability to get lead molecules that we can test,” says Glen Spraggon, director of structural biology at the Genomics Institute of the Novartis Research Foundation, part of the innovation arm of Swiss drug company Novartis International AG.
Observing structures as real 3D objects with VR The team at NIBR uses computational tools for understanding how drug candidates would interact with critical protein structures in the human body, while the drug discovery process is expensive as well as lengthy as it takes around a decade to get a drug to the market. Owing to advances in structural biology, more complex as well as bigger biomolecular structures are being solved. While these 3D structures are hard to analyze on flat 2D monitors, the team states that with the use of Virtual Reality, one can observe these structures as real 3D objects. The immersion is amazing through which someone can even step into the molecule, and look at it from the inside. And this was not possible using the older 3D visualization technologies.
The road ahead According to recent research, the market is going to witness rapid growth in the near future. Major factors bolstering the market drivers include the high cost of in-house drug development, increasing Research & Development expenditure in the biopharma and pharma industry & a surge in demand for outsourcing analytical testing services.
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