AI, Quantum Computing And Disruption In The Pharmaceutical Industry

AI, Quantum Computing And Disruption In The Pharmaceutical Industry
In a world of relentless progress and development, an era of medicine and healthcare transformation is on the horizon. The pace of population growth seems unstoppable. Current infrastructure demands superior performance and affordability. So we are on the cusp of a deluge of new innovations. The magic lies in a troika on the frontiers of science: synthetic biology, the engineering of biological systems; AI, the precursor behind computational intelligence; and quantum computing, the untapped remarkable power of computing technology. Together, in these emerging fields, we can navigate the complexities in genomic data, decode life-supporting biological mysteries, predict the behaviors of complex metabolic pathways, and revolutionize the pharmaceutical industry and healthcare system with unprecedented speed and accuracy.

Synthetic biology combines biology, engineering, and computer science to build artificial systems that can perform your desired functions. Can we make synthetic life? In 2010, Craig Venter, bought this news through his groundbreaking achievement of creating the first synthetic organism with a completely artificial genome. The “Synthia,” a synthetic bacterium was constructed by assembling the genetic code of the bacterium from scratch using laboratory conditions. The underlying mechanism involved three main steps; design, build and test. This marked a remarkable milestone in synthetic biology, demonstrating the ability to design new life forms.

The global market for synthetic biology was $12.70 billion in 2022, and is estimated to increase to a value of $85.97 billion by 2030. Biocomputing, therapeutic genome editing, cloning, third-generation, bio refineries, electrical interfacing cellular recording, and multiplexed diagnostics all have benefited from synthetic biology in recent years. Moreover, agriculture, pharmaceutical, and biotechnologies industries have successfully designed gene circuits, synthetic clones, and automated engineering in different strains of bacteria including sitagliptin, leghemoglobin, and diamines. Synthetic biology will transform the food we eat and want to grow, and the materials required for medicines. The products already in the markets are; “Burger that bleeds’ with less sodium and saturated fat by Impossible Foods. Januvia is a diabetes drug derived from Merck. Januvia increases insulin secretion. It is the 95th most prescribed drug with a revenue of $1.35 billion annually. Pivot Bio turned on the off gene required for nitrogen fixation, thus creating the first synthetic biological fertilizers.

How does AI help synthetic biology? One of the major challenges in synthetic biology is the sheer complexity of the biological system; thousands of genes, proteins, and their delicate interactions. To disrupt such an intricate system, we need tools that can predict the possible outcomes. This is where AI comes in, with its ability to predict the behavior of complex life systems and optimize the design of new biological systems including drug design, genetic circuit validation, and making sense of life processes and large amounts of data by using machine learning algorithms. For example, MIT researchers have successfully developed a machine learning algorithm that can predict the behavior of genetically engineered new circuits inside the cell allowing them to design more efficient and optimize systems.

Another application of AI in synthetic biology is deep learning; which recognizes a pattern in a large amount of data. The understanding and predictions of cell behavior based on microscopic images of the cells help the scientist to gain the desired outcomes. It allows the researcher to know the inner workings of cells and design new biological systems. Finally, this led to the creation of an automated system that can analyze a large amount of data quickly. Based on these principles a team of scientists at the University of California, San Francisco created a robot that can design, conduct and analyze its experiments to refine and improve the production of biofuels in yeast cells. Imagine if the limitation of humans to predict complex behavior is overcome by AI, then how it can benefit the world?

Recently, Insilico Medicine, an AI-based drug discovery company, conducted a series of studies combining quantum computing and generative AI to explore desired results in drug development. The trained Quantum Generative Adversarial Network GANs out performed classical GANs in generating the desired compounds with specific drug properties. This research paves the way for Insilico’s foray into quantum computing and demonstrates their integration of AI and quantum technologies in a molecular generation.

On 19 May 2023, the company announced that it combined two emerging technologies; generative AI, and quantum computing to explore the desired candidate discovery in drug development and successfully presented the significant advantages over conventional way of drug discoveries. However, the molecules generated by GANs are virtual representations or computer models. Experimental validation is required to determine the viable molecules for drug development. Recently, Bayer, a German pharmaceutical company announced a partnership with Google Cloud to operate their large-scale quantum chemistry operations. The company wants to accelerate drug discovery. Using quantum computing strategies, Biogen collaborated with Accenture Lab to develop a quantum-based drug for Alzheimer's disease. There is a challenge – which is that quantum computing is not cost effective and still in its infancy. The justification of such expensive technology is yet to be addressed by the drug companies.

The misuse of knowledge is the dark side of innovation and can be detrimental to humanity. There have been studies on human pathogens; the poliovirus and the 1918 Spanish influenza virus were created from scratch. This raises concerns about the potential use of these pathogens as biological weapons. For instance, mousepox was accidentally created by scientists, resulting in the death of all infected mice. If the same applies to smallpox, it can create a resistant strain against vaccinations in humans. Many conventions, protocols and laws related to biosafety are in place but they are general guidelines, and have no specifics focusing on symbol. The US synthetic biology regime is majorly controlled by the private sector and academia, determining self-governing and industry specific best practices.

The integration of AI intelligence into warfare poses a serious threat; if it decides when and how to make war strategy based on available data. Misreading of a rival's intentions will have far reaching repercussions. As of today, AI has nothing to do with emotions, humanity and mass destruction. It only knows the language of algorithms. Moreover, AI systems require a lot of data for their training, but adversarial AI carries unpredictable escalation risks with synthetic or incomplete information. The best known example of this, albeit non-fatal, was the “flash crash” of the stock market, where an adversarial algorithm wiped trillions of dollars in one hour. The military equivalent of this seems like hyperbole, but it would be catastrophic. Above all, it must be ensured that humans alone hold the power to control AI based weapons.

The nightmare scenario for the development of the drug against complex diseases is unfolding. Healthcare transformation is the need of the time. Synthetic biology has the potential to unlock the natural system from scratch. Quantum computing is the future. AI waves have reached every sphere of life. Science enthusiast school-going children should deep dive into the nuances of these emerging fields. Understanding the frontiers of science is the only way to find gaps in human knowledge and come up with innovations. Just a fully functional quantum computer poses a challenge to current encrypted devices. What we are witnessing today might just be the tip of the iceberg.

The author is a PhD candidate at the Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology (NUST) in Islamabad