Quantum for Sustainability in Healthcare
QCentroid is fostering a stakeholder ecosystem where sustainable transformation and prosperity are incentivized and aligned. We believe that science, data, and exponential technologies will be quintessential in realizing sustainable new ways of working, living, and driving sustainable industry transformation forward.
One of the focus areas of QCentroid is quantum computing for sustainability. In the previous article Quantum Against Climate change, we explored how quantum computing, a Fourth Industrial Revolution (4IR) technology that we believe will form the base layer of the future technology stack, can have an exponential impact on the fight against climate change. Please refer back to that article for an introduction to quantum computing and sustainability.
In this article, we explore how quantum computing can bring about sustainable transformation in healthcare.
We hope to inspire collaboration on individual, academic, and industrial scales in this effort. Please reach out to us to inquire about how we can join forces.
Healthcare:
Improving health is an SDG in itself and quantum computing is poised to transform this industry via several touchpoints:
Drug discovery
As with chemical engineering and material science, time consuming lab experiments have hitherto been a staple part of the drug discovery process, taking years to release and incurring R&D costs of billions of dollars. The use of quantum simulations to do these experiments virtually in a matter of hours and at negligible material cost opens up an entirely new paradigm. Many pharmaceutical companies are stepping up to the promise of quantum. In January 2021, Boehringer Ingelheim, a pharmaceutical company, announced their partnership with Google Quantum AI which will empower them to do molecular simulations using Google’s quantum computers. Accenture, 1 Qbit (a QC company) and Biogen are also collaborating to design drug indications such as Alzheimer’s, Parkinson’s and multiple sclerosis.
Faster drug interaction prediction and drug testing could be possible with quantum computing thanks to the ability to simulate drug-drug and drug-human interactions in-silico instead of in-vivo.
Enzymes
Enzymes play an essential role in catalysing almost all kinds of biological processes by precisely acting on their designated target molecule. Being able to reverse engineer enzymes and create new ones may have a profound impact on being able to alleviate major diseases. Classical computers are limited in their ability to model enzymes – quantum computers, however, could come up with an accurate model of the properties, structure and reactively of such enzymes in a matter of hours.
Diagnostic and decision Assistance
Early and accurate diagnoses lead to better treatment outcomes and lower costs. In the case of colon cancer for example, early diagnosis leads to a 9x increase in survival rates and a 4x decrease in treatment costs. Diagnostics, however, is currently complex and costly, and comes with a 5-20% error rate.
The success of chemotherapy is often not known for months after undergoing the treatment. Quantum computing is changing that. Researchers from Case Western Reserve University together with Microsoft have developed a magnetic resonance fingerprinting (MRF) based technique with which the efficacy of chemotherapy can be known after a single dose. MRF involves processing massive amounts of data that is only possible in a practical manner thanks to exponentially faster data crushing powers of quantum computers.
Protein folding and Biologics:
Biological drugs, or biologics, refer to drugs that are composed of proteins or other macromolecules. Antibodies, insulin and many vaccines are classic examples of biologics. Modelling such drugs on classical computers is usually not possible.
Modelling proteins, for example, entails understanding how the amino acid chains that make up the protein would fold onto itself. The possible configurations that exist for a given chain length scales exponentially with the length of the chain. For example, chains with 20 and 100 amino acids can have 10^9 and 10^47 conformations . The FDA defines a protein-based drug has one that has at least 40 amino acids – an insurmountable task for classical computers.
Quantum computers can address these computational challenges by scoring the multitude of different possible structures and identifying the most likely configuration.
Let’s collaborate!
This article is the third in a series on quantum computing for sustainability. Here we have briefly covered the application of quantum computing to drive sustainable transformation in the mobility and aviation industry forward.
We look forward to feedback regarding this article and learn about further high impact applications of quantum computing in healthcare.
We hope this article inspires collaboration to leverage quantum computing to drive the sustainable transformation of industries. Please reach out to us if you're interested in joining forces.
To learn more about QCentroid, please visit us at www.qcentriod.xyz or by email at info@qcentroid.xyz