Revolutionising Drug Discovery: The Impact of AI and Patient-on-Chip Technology

Revolutionising Drug Discovery: How AI and Patient-on-Chip Technology are Transforming the Pharma Industry

As 90% of new drugs fail in clinical trials, pharmaceutical companies face tremendous financial losses, amounting to over $30 billion annually. More importantly, the development and delivery of potentially life-saving treatments are woefully delayed. However, the integration of AI into drug discovery is changing the landscape. According to industry reports, the generative AI drug discovery market has seen a growth rate of 30.6% in 2024 alone. This revolution is spearheaded by innovative approaches, such as those employed by Quris-AI, founded by Dr. Isaac Bentwich, MD.

Current Inefficiencies in Drug Development

The traditional methods of drug development, which rely heavily on tissue culture and animal testing, are fraught with limitations. These methods often fail to accurately predict how drugs will behave in humans. As Dr. Bentwich explains, "Drug development is basically a funnel. It starts with discovery...but 92% will fail in clinical trials." This inefficiency not only leads to financial losses but also raises ethical concerns regarding the use of animals in testing.

Advancing Techniques in AI and Patient-on-Chip Technology

A key innovation driving change is the use of patient-on-chip technology. This approach involves creating miniaturised versions of human organs on microfluidic chips, which can simulate the biological functions of these organs. Dr. Bentwich describes this technique as "creating miniaturised versions of the human organs of an individual and putting them into a microfluidic chip." This method provides a more accurate representation of human physiology compared to traditional methods, allowing for better predictions of how drugs will interact with human organs.

Patient-on-chip technology, combined with AI, allows researchers to run thousands to millions of experiments simultaneously. This high-throughput data generation trains AI models, making them more effective in predicting drug safety and efficacy. "The combination of AI and patient-on-chip technology becomes very powerful," says Dr. Bentwich.

Real-World Applications and Success Stories

The effectiveness of patient-on-chip technology and AI has been demonstrated in several real-world applications. For instance, Quris-AI's platform has shown a 94% accuracy in predicting liver toxicity, a significant improvement over traditional methods. "We have shown 94% accuracy in being able to weed out or guess looking at history cases," highlights Dr. Bentwich.

In the realm of rare diseases, Quris-AI has made strides with conditions like Fragile X syndrome, a congenital cause of cognitive impairment. The company has developed disease models that do not exist in animals, allowing for more effective drug development. "We were able to recreate a model of this disease, which does not exist in animals," notes Dr. Bentwich.

Ethical and Societal Impacts of AI in Drug Development

Reducing reliance on animal testing and improving trial diversity are significant ethical considerations in modern drug development. Dr. Bentwich emphasises the importance of "reducing the reliance on ineffective animal testing" and developing more representative clinical trials. This approach not only speeds up the process but also ensures that treatments are safe and effective for a broader range of patients.

Women and minorities are often underrepresented in clinical trials, leading to drugs that may not be effective for these groups. Dr. Bentwich points out that "women are represented less than 50% in clinical trials; minorities are represented in less than 11%." AI and patient-on-chip technology can help address these disparities by providing more inclusive and accurate predictions of drug efficacy and safety.

The Future of Personalised Medicine

Looking ahead, Dr. Bentwich envisions a future where AI-driven personalised medicine becomes the norm. "The ability to test these drugs and develop them on clinical trials on the chip that have a much broader reflection of the population" will significantly reduce failures in clinical trials and lower the costs of drug development.

Emerging trends, such as the democratisation of drug development, where patient communities actively participate in the process, are also on the horizon. This approach empowers patients and their families to have a more significant role in the development of treatments for rare diseases, fostering a more patient-centric healthcare system.

Conclusion

The integration of AI and patient-on-chip technology marks a significant advancement in the pharmaceutical industry. By providing more accurate predictions of drug safety and efficacy, reducing costs, and addressing ethical concerns, these innovations are paving the way for a new era in drug discovery and development. As these technologies continue to evolve, they promise to deliver safer, more affordable, and more personalised treatments, ultimately transforming the landscape of healthcare.

Further Reading 

For more insights on how AI is maximising ROI in Drug Discovery and Development, download Pharma IQ's Report. 

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