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Quantum Computing: A game-changer for pharma innovation

By Lionel Alva

Pharma companies have constantly been on the lookout for the next miracle pill. The problem is that current approaches towards drug discovery carry limitations, despite advances in artificial intelligence, machine-learning, and raw computing prowess.Today, many companies in the pharma space, who are on the cutting-edge of technology, are looking at the possibilities that quantum computing can open up when it comes to pharma innovation.

Based on the laws of quantum mechanics, quantum computing is a significantly different computing approach that can lead to numerous possibilities for the pharma industry: Specific computations are performed significantly faster and with greater efficacy than conventional computing approaches would allow.  

As per insights from McKinsey, quantum computing can accelerate pharma innovation in the following ways. 

Role of Quantum Computing

Traditional drug delivery is usually carried out via clinical studies, which are a process of trial and error.  The approaches used today are resource intensive and lack accuracy. Quantum Computing can help remedy and bring down the time needed for pharma innovation. 

Quantum task forces have been set up by leading pharma companies to assess the application of quantum computing approaches to chemistry and biology.  Conventional computing approaches that employ the use of computer-aided drug-design (CADD) process to enhance the efficacy of molecular simulations, incur a significant increase in computational costs. These scaling challenges in conventional computing have often been a hindrance. Quantum Computing could bring a paradigm shift in the simulation of subatomic particles, molecules, solids, and atoms: Without incurring the scaling limitations of conventional computing. Potentially, it could even allow mathematically exact solutions to the Schrödinger equation for larger and more complex molecular systems.

With further advancements in quantum hardware, quantum volume, count, and quality, it is expected that all phases of the drug development pipeline can receive a boost via quantum computing. Today quantum devices that are fault-tolerant are at least 10 years away, but variational algorithms and NISQ1 devices are paving the way for the quick adoption of quantum chemistry and QML. Consequently , pharma stands to benefit greatly from advancements in quantum computing. It could lead to alternate treatments, more rapid and accurate drug delivery, and better overall healthcare outcomes. QC would also be relevant to quantum chemistry, QSAR3 models, and molecule docking. 

Market disruption

Presently, the technological gap is quite significant when it comes to quantum computing and conventional approaches. The biggest challenge in the pharma industry is to make a mindset shift, wherein problems are viewed from the prism of quantum computing. Many in the pharma industry are relegated to using classical methods and tools and this assumption needs to change. 

Even when it comes to drug discovery, the development process takes a long time and is known to be expensive. For instance, a brand new chemical compound, can take approximately $2 billion and a decade to get into the market. AI and ML have helped reduce this timeline but quantum computing can truly bring a paradigm shift. 

The biggest value drivers for quantum computing exist in clinical and preclinical stages, where failure rates can be as high as 90 percent.

Future landscape

Presently, quantum computing is not ready for commercial use. However, the potential it holds to dramatically alter the pharma landscape has significant merit. It will take at least 10 years before quantum computing is widely accessible.

Once it is, the long-winded clinical trials, methods of trial and error for drug delivery, and other areas of pharma innovation could receive a significant boost. Pharma companies will have to decide if they are going to take a partner or build their own QC capabilities. Many would prefer having an external QC specialist, as in-house development could be a significant challenge.

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