Quantum computing > Life sciences and biotech
‘Quantum computing… can aid in understanding how drugs interact with target proteins or enzymes, predicting their efficacy and potential side effects’
Dr Shahar Keinan, CEO and co-founder at PolarisQB
Understanding disease to determine a biological target that can be modified by an external compound is an essential phase that can demand several years. Identifying a lead compound that can effectively modulate the molecule or protein involved in such disease, ensuring it can be safe, and understanding its metabolisation and interactions, is not as simple as just getting a name. It requires a long list of candidates and many tests to choose the most suitable one, and then several years to optimise it to reach its most effective and safe version. Given this complexity, scientists have
been researching ways to accelerate the drug discovery process. By leveraging quantum annealing mechanisms, they have managed to create algorithms capable of finding the best lead compound candidates in just a few minutes by binding prospects to biological targets among billions of molecules.
That is the case of the American Polaris Quantum Biotech[5]
(PolarisQB),
who have developed QuADD, a software as a service which leverages quantum annealing and distributed cloud computing for molecular library generation. In dialogue with Dr Anna Petroff[6]
and Dr Santiago Vilar[7] ,
computational chemists at PolarisQB, Dr Petroff explains that finding a small molecule that matches a protein target is challenging because the number of them is enormous. She notes that with QuADD, they can build a custom library of billions and “find a lead compound in less than a minute”. Meanwhile, Dr Vilar remarks on the potential of quantum computing
in optimising results by improving data quality and speed. Other companies, such as River Lane
coupled with AstraZeneca, in the UK, are advancing in harnessing the potential of quantum computing to calculate the solubility of lead compounds to estimate their effectiveness in the human body. It is clear that quantum computing has a big potential in helping to identify and optimise lead compounds and could also help in the pre-clinical phase, where the current methods notoriously fail. In this respect, Dr Aysha Akhtar[8]
, renowned
neurologist and public health specialist, US veteran and Founder and CEO of the Center for Contemporary Sciences, emphasises that “Up to 95% of all drugs and vaccines that are tried end up failing at the human clinical trial phase because they don’t work or are too toxic and unsafe”. She adds, “This shows that animal testing is very bad at telling us which drugs and vaccines are actually going to work in humans and be safe for humans to use.” Thankfully, scientists are making
computational progress in predicting the toxicity of chemical compounds currently tested on animal models. An example is the work of Dr Teppei Suzuki[9]
and Dr
Michio Katouda, who developed a quantum machine learning model to predict the toxicity of over 200 phenols used in various drugs and antiseptics. Another example is the quantum machine learning
model developed by Dr Saad Darwish, using genetic programming to predict the toxicity level of different chemical compounds. Advancements like these are driving
drug regulatory agencies – such as the FDA in the US, under the Modernization Act 2.0 – to support more humane requirements for approving drug releases to the market. Even so, many pharmaceutical companies sustain that the efficacy and side effects of new drugs can only be tested on animal models. Fortunately, quantum computing is shedding some light here. Indeed, Dr Shahar Keinan[10]
, CEO
and co-founder at Polaris QB, bets on the future of quantum computing for pharma. “Quantum computing has the potential to revolutionise drug design and development. It can aid in understanding how drugs interact with target proteins or enzymes, predicting their efficacy and potential side effects,” she says.
Cancer detection and treatment: another potential area for quantum computing According to official statistics, cancer is responsible for over a quarter of deaths in England, and the survival time after diagnosis is too low. WHO reports 10 million deaths worldwide from cancer just in 2020. Cancer kills, and scientists are not yet able to find a cure. Understanding the development and progression of cancer is
For more info about quantum computing visit:
www.scientific-computing.com/quantum
SCIENTIFIC COMPUTING WORLD
Summer 2023 Scientific Computing World 7
g
Gorodenkoff/
Shutterstock.com
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42
