The goal of technological advancement is to produce more with fewer resources. Even if technology has progressed from a room-sized computer to a cell phone, there are still many challenges that the world’s powerful computers can help with. We’ll soon need to accomplish our computing in a whole different method when smaller, more potent computers become necessary. Quantum theory, a subfield of Physics, studies the universe of atoms and the smaller (subatomic) particles that reside inside of them. But the laws of classical physics don’t apply in that little universe of atoms. “I think I can safely say that nobody understands quantum mechanics,” said Richard Feynman. Therefore, the most popular but also most challenging field nowadays is quantum computing.

Today’s computers are made of silicon transistors and use bits of computation. These bits take either of the two values 0 or 1. Instead of bits, a quantum computer has qubits. Qubits can exist in a multidimensional state. Qubits use superpositions to represent multiple states. As a result, a quantum computer can perform multiple operations in parallel, which makes it significantly faster than a traditional computer.

Quantum Computing Advantages

Although designing, building, and programming a quantum computer can be challenging, there are certain advantages as well when compared with the supercomputer. So, what can it be used for?

• Molecular Modelling: Quantum computing uses a variety of computerized techniques to predict the chemical and biological properties of molecules using theoretical chemistry methodologies and experimental data. These techniques are utilized in computational chemistry, drug design, computational biology, and materials science.
• Database Searching: Quantum computers are used to store and search through massive amounts of data in a much quicker time than traditional computers.
• Data Security: In the future, quantum computing may play a significant role in network and cyber security.
• Weather Forecast: Quantum computing will assist in improving local and global weather forecasting for more advanced and precise warnings of extreme weather occurrences, potentially saving lives and lowering annual property damage.

Quantum Computing: Metamorphosis in Drug Discovery

The drug development process is complicated, costly, and time-consuming, with several stages and regulatory approval. To identify and validate drugs, research must adhere to the strictest safety and quality standards. While technology has advanced at a breakneck pace, the discovery and design of novel therapies is an increasingly difficult endeavor. But identifying previously unknown molecules and drugs has become more difficult, and every avenue that could speed up or improve the process must be explored. Quantum computers could outperform any supercomputer and it is emerging as the next frontier in pharmaceutical research.

Quantum computers use qubits, which can either be on or off, or both – known as the super-position. This superposition enables quantum computers to execute multiple calculations simultaneously, far more effectively than conventional technology. In the drug discovery process, quantum computing ensures accurate data projections while taking into account a wide range of biological parameters at the same time.

According to the experts in drug development, quantum computational tools may add value for designing and developing antibodies, by creating a novel antibody structure. Integrating the quantum algorithms with the classical tools available today may happen naturally while building the expertise and strategizing to solve the problem. By taking the advantage of various algorithms, hybrid algorithms, and approaches the best quantum tool can be decided to best suit the purpose.

There are numerous potential quantum applications on the horizon. It is expected to play a significant role in drug discovery, speeding up processes for testing and synthesizing chemicals for use in medicine, among other applications. Revolution in the bio-medical imaging sector can transform the detection and diagnosis in the advancement of new drug development.

Biogen, an American biotechnology firm, is testing quantum to help with the treatment of neurological diseases. To accelerate drug discovery, quantum-enabled optimization, sampling, and machine learning algorithms can be used, a report from The Quantum Insider. Boehringer Ingelheim, a Google Quantum AI partner for the past three years, is another pharmaceutical company pioneering quantum computing to accelerate and optimize the healthcare services and solutions. Their goal is to develop innovative and cutting-edge new medicines in the future.

Harnessing the power of quantum mechanics is a difficult and delicate task, and there are still many obstacles to overcome. Qubits are delicate and to maintain them in superposition and entanglement, a secure environment is required. If the qubits are not maintained in extreme conditions, then the entire quantum operation is futile. With growing interest and innovations, new applications and products will inevitably emerge. The quantum upheaval could introduce a period of new explorations that surpasses existing perspectives. It’s evident that quantum computing has the possibility to change the way medicine is discovered.

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Over time, it became clear that the spatial geometry of the molecules is of more relevance than their chemical composition, opening the floodgates of the vast world of synthetic drug design. The role of computers began here, as digital techniques like Computer Assisted Drug Discovery (CADD) enabled us to expedite laborious database searches to identify possible matches in 3D structures, helping us discover much smaller molecules of comparable geometry. With the surfeit of organic molecules growing steadily every day, we need computing tools that can rummage through databases to find appropriate candidates in drug design.

Pharma’s dependency on database searching makes it a prime candidate for the implementation of quantum computing, owing to its ability to catalyze CADD. But before we delve into that, let us take a closer look into the labyrinthine world of QC, hoping to accrue a working knowledge of its method.

QC: The rudiments

The rise of quantum mechanics is arguably the greatest development in science for the better part of the last century. It has been key in solving some of the great challenges of modern physics, but its application in IT comes as a surprise to many. Simply put, the quantum mechanical innovations, both theoretical and practical, have helped reimagine the smallest unit of information in computing- the ‘bit’.

To better understand this, we need to look at story of computers and the transistors that form their core. Around the turn of the 21st century, scientists at the Silicon Valley were working towards reconceptualizing the transistors through a drastic reduction of their size, with 14nm transistors being the norm today. At this level, transistors may begin to prove ineffective as electrons start exhibiting quantum mechanical behavior via quantum tunneling, marking a technological dead-end for computational progress, which in turn reflects as the end of technological progress.

However, scientists were able to nullify this roadblock (or here the lack of one) through the revolutionary quantum computer model. Here, the binary bits are replaced by qubits, which, while remaining binary in theory, exist in a superposition of various quantum states. The values of a qubit can be of any level 2 quantum system, like a spin or magnetic quantum number, or a single photon in its state of horizontal or vertical polarization taking values 0 or 1, mirroring their classical binary counterparts. Courtesy of the bizarre rules of the quantum realm, the qubits do not need to be in either states independently; they can exist in various proportions of both these states simultaneously until observed(illustrated in the Schrodinger’s cat thought experiment), owing to the property of superposition as mentioned above. It may be looked at just like when the binary photon passes through a polarizer (the observation); it can only have one orientation. As a result, the superposed qubits can store vast data points as compared to classical bits; consider a combination of 20 qubits in superposition: this would give us 1,048,576 values, all of which can be used for computation once the superpositions are collapsed.

The computational process must be juxtaposed with its classical colleague to understand what we’re dealing with: while a normal logic gate works with various inputs to give a single output, the quantum gates can now use superposed qubits to entangle them, and simply measure the values to collapse them to their binary values. The sheer speed that this method promises is self-explanatory. This means an exponential acceleration in computation, reflecting in various aspects of pharmacology, from discovery to clearance and marketing.

The R&D ramifications of QC
The scope of QC in pharma is not limited to, but lies predominantly in drug discovery, namely the understanding of structure-property relationships and identification of stereoisomers to create matching proteins that are smaller in molecular weight and helping identify the spatial structures of target molecules. One key area where this may have a pivotal impact may be in the assessment of how proteins fold, a phenomenon that may happen in a plethora of permutations and combinations. The quantum simulations can predict molecular structures with unprecedented speeds, but also provide us with highly accurate models. Some of the most intense research in this area happens now in creating QC models for target identification and hit generation, with mixed results. And while converting some of these real-world problems into quantum mechanical ones are onerous, it is as clear as day that quantum computers, in the right hands, are a handful in powering technology to its next stage.

For now, it may suffice to say that the future of QC in pharma reposes in a superposed state of probabilities, and only time can open the box to reveal what the true nature of its reality holds for the progress of medicine

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Quantum computing has a variety of applications in revolutionizing the automobile industry such as improving battery performance, avoiding traffic congestions, preventing car accidents and mishaps by machine learning and analysis etc. that can greatly benefit the sector when they come to fruition. Machines in quantum computing work with physical properties of matter, such as superposition or entanglement, which means that calculations can be performed on multiple states of matter at the same time, drastically reducing computation time.

Advantage of Quantum Computing The brainchild of Nobel laureate Dr Richard Feynman, quantum computing has progressed to enormous levels of growth, finding a variety of applications in different fields and sectors. Quantum computing involves simulation of the physical nature of objects at subatomic sizes while allowing them to exist in more than one state. This allows rapid simulation and processing of data than conventional systems, making quantum computers much more powerful, efficient, and faster. It has been applied in fields like Cryptography, Medicine, and material sciences to accommodate multiple variables or molecules in simulations to reach the desired end product or solution. Various automobile companies like BMW (CNET) and Hyundai (Eetasia) have started working with quantum computing systems to solve various issues like cost optimization, development of new batteries, optimization of components to improve cost-effectiveness etc.

Quantum Computing in Battery Technology

Quantum computing has been applied to develop effective solutions in improving the battery technology in cars and automobile systems as it can simulate multiple molecules of compounds simultaneously in different states, conditions, and environments to help identify the ideal combination of variables. Hyundai Motor Co. has partnered up with quantum computing experts to develop a robust battery that can function with improved capabilities and durability when used in electric vehicles. They aim at reducing the cost of battery development and production to reduce the overall cost of the vehicles, improve affordability and progress towards sustainability. A quantum computer of sufficient complexity—for example, enough quantum bits or “qubits”—could theoretically achieve a quantum advantage, allowing it to solve problems that no classical computer could ever solve. In theory, a quantum computer with 300 qubits fully dedicated to computation could perform more calculations in an instant than the visible universe’s atoms Quantum computing has also been applied in the development of novel technologies that can improvise the functioning of EV batteries by incorporating advanced technologies to cool them. It is applied by compartmentalizing big issues into individual parameters that are simulated using quantum computing to be later integrated into the conventional systems as a hybrid model or to fashion a completely new model by combining the solutions offered by quantum computing(EENewsEurope).

Quantum Computing in Autonomous Driving Quantum computing can facilitate the design and development of powerful operating systems to produce self-driving cars, simplifying transportation and reducing the chances of human errors in road traffic accidents. Artificial intelligence and machine learning require the real-time analysis of vast amounts of data to produce optimal responses to changing environmental conditions and quantum computing with its excellent computational features

can lend a hand in facilitating the requirements. Volkswagen(Prescouter) has experimented in the design and development of computational systems to optimize traffic control and regulation in the city of Beijing and has found great success in this venture. It also has applications in improving vehicle to vehicle and vehicle to cloud communications in next-generation cars that are expected to have the ability to communicate with cloud computing systems to regulate driving data. This will help in traffic and fuel optimization in cloud-connected cars while providing a safe environment for decentralized communication between them.

Conclusion

Quantum computing has unlimited potential and practical applications across different fields and sectors and can make a path for enormous progress in the automobile sector. Companies and enterprises in the automobile sectors would greatly benefit by working with quantum computing as it is a leap towards greater sales and a greener environment. Recently, quantum computing has gained a lot of traction in both general society and the private sector. Companies have been pouring huge sums of money into quantum computing research, with the last few years being the busiest for this innovation.

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