Rounak Dubey, MBBS, MD
Assistant Professor, Transfusion Medicine
All India Institute of Medical Sciences, Nagpur
" I know this world is ruled by Infinite Intelligence. It required Infinite Intelligence to create it and it requires Infinite Intelligence to keep it on its course."
— Thomas A. Edison
As we stand on the brink of a biotechnological revolution, every field, including biotherapy and biomanufacturing, is eager to harness the transformative power of Artificial Intelligence (AI). The tech giants are tirelessly working towards faster drug discovery, using AI to unravel the mysteries of medicine. Earlier this year, Nvidia's CEO, Jensen Huang, highlighted a future dominated by digitized biology through advanced computing and AI. While these innovations promise unprecedented advancements, they also stir fear and fascination among the public and professionals alike. AI has long been portrayed in popular culture and science fiction as the doorway to the doomsday and a dystopian future. Perhaps it's time to rewrite this narrative.
Bioengineering and cell/gene therapies have also faced dystopian narratives in the past. However, public perception shifted dramatically as their potential to cure a wide range of diseases became evident. AI might soon undergo a similar transformation. Though the journey is still long, the destination seems promising.
The progress of AI in healthcare lags behind its achievements in other sectors. In my previous editorial in Telegraft, I touched upon this very topic. My own views on AI have evolved, influenced by my collaboration with data scientists over the past eight months. With robust regulatory and ethical frameworks guiding its development, "cautiously optimistic" might be the best way to envision a future where biotherapies evolve with AI's help. We can reimagine AI as an extraordinary tool with boundless potential, much like the internet and email revolutionized communication. While the internet connected humanity globally, AI might allow us to tap into a greater intelligence at work.
Answering questions with unknown, dynamic variables is inherently challenging. Dr. Eric Topol, in his book Deep Medicine, argues that AI's real power lies in augmenting, not replacing, human intelligence. Given our inherent biases and the inevitable human errors across fields, whether in manufacturing, laboratories, or at the bedside; AI offers a much-needed "intelligent" assist.
By the end of 2024, AI-driven tools are poised to tailor gene therapy treatments to each patient's unique genetic profile, particularly for rare diseases. This precision promises more effective therapies and improved outcomes. Predictive modelling will optimize various stages of cell therapy development, enhancing efficiency and minimizing risks associated with early-stage vector designs. AI is refining targeted nanoparticles and viral vectors, while better-designed clinical trials and real-time patient monitoring emerge as areas of immense potential.
Despite these promising advancements, AI's journey in healthcare is still in its infancy. Only time will reveal whether it lives up to its hype. In March 2024, a study published in Nature Biotechnology detailed the discovery and development of a first-in-class TNIK inhibitor, designed through generative AI from algorithms to Phase II clinical trials. Patient enrolment for its Phase IIa study to treat Idiopathic Pulmonary Fibrosis (IPF) has been completed in China. The results could mark a watershed moment in AI led drug discovery.
The AI narrative has just begun to gain momentum. It must navigate seemingly troubled waters, but the potential rewards are immense. We should shift from the "AI vs. humans" mindset to "AI with humans." Until that happens, let us consider AI as another technological marvel at our disposal, reflecting a greater force at work, often referred to as Infinite Intelligence.
References:
1. https://www.cnbc.com/2024/03/24/nvidias-ai-ambitions-in-medicine-and-health-care-are-becoming-clear.html
2. https://www.forbes.com/sites/forbestechcouncil/2024/02/14/a-new-era-of-drug-discovery-with-biology-driven-ai/
3. Topol, E. (2019). Deep medicine: how artificial intelligence can make healthcare human again. Hachette UK.
4. Ren, F., Aliper, A., Chen, J. et al. A small-molecule TNIK inhibitor targets fibrosis in preclinical and clinical models. Nat Biotechnol (2024).
#CommunityFeature#feature4