By Devanshi Dewan and Rashmi Mabiyan
Mumbai: the transformative role played Artificial intelligence assumed during the recent past, has completely changed our understanding of the traditional and conventional models in place in the pharmaceutical industry. AI/ML is increasingly used at the beginning drug discovery for predictions of specific, unwanted interactions from something as simple as a chemical structure, informed a panel of speakers at the 4th edition of the REPharma Summit.
The summit featured an informative panel discussion titled “Deploying AI/ML for Drug Discovery and Biotechnology Innovations,” where experts highlighted the changes driven by AI/ML in the pharmaceutical industry.
The panel consisted of industry leaders who have seen developments in the pharmaceutical industry up close. The panel included Dr. Anil Kukreja, Vice President, Medical matters and regulatory, AstraZeneca Pharma India Limited; Narendra Saini, Director of Digital and Data, Lupine; Dr. Shubhadeep Sinha, Senior Vice President, Head of Clinical Development and Medical Affairs (CD&MA), Hetero Labs Limited; Dr. Baskar Viswanathan, Life Science – Business Consulting Officer Agilisium and the panel discussion was moderated by Dr. Mukesh Kumar, Senior Vice President and Head of Clinical R&D, Cipla.
Opening the discussion, Dr. Sinha said, “While clinical trials are being conducted, predictions about the patient with recruitment, better recruitment of patients, predictions about possible adverse reactions that might occur and prediction or even on sites which can be taken on the basis of the available data.”
He highlighted the growing prevalence and current importance of AI/ML in the drug discovery process as well as the enormous capacity of AI/ML to accelerate the drug discovery process.
AI/ML has its role throughout the cycle. And so it will grow further, not that it will make you lose jobs, but it will only help in improving and speeding up the drug discovery process, Dr Sinha added.
Speaking about the role of AI/ML in drug discovery and development, Dr. Kukreja said, “We see the role of AI and ML throughout the life cycle, from drug discovery, drug development and, more importantly, patient care. I think it’s very important to see the evolution that’s happening. And particularly, I think we are on the cusp of the moment where India can take a leap forward and transform the way we have traveled our journey in our digital payments interface.
Confirming experts’ views on putting the patient first when it comes to using AI/ML, Dr Kukreja added the importance of early diagnosis in preventing life-threatening diseases.
He said: “From streamlining, but also ensuring that we are able to identify the right patient profiles and the right sites for clinical trials. In fact, taking the clinical aspect, AI and ML can help us identify the right size where clinical trials can be conducted. Help the investigator identify the right patients for clinical trials. Above all, speed up the diagnosis.
Talking about the huge potential of AI/ML on the manufacturing and supply chain process in the pharmaceutical industry, Dr. Kukreja added, “It has the potential to transform the entire value system, especially in the pharmaceutical and healthcare industry I would say. it’s phenomenal. I think it has huge potential.
Speaking about the challenges related to the data privacy aspect of technology, especially in terms of deploying AI/ML technologies, Dr. Viswanathan said, “A single data leak can end up becoming a ransom of a million dollars for a million dollar supplier. . Privacy and security, stability and correctness of the model are also equally important.
Continuing the discussion on the use of AI/ML technology in the diagnostic industry, Dr. Kukreja said that these technologies can prove to be very useful and patient-centric in the diagnostic sector.
He said: “It’s possible that this ECG could travel through cloud computing to an AI-trained technology, and then you can get the diagnosis. And patients’ lives can be saved. There are use cases where we have deployed these technologies, where we have been able to save the patient’s life using the hub-and-spoke model. There are many use cases where we have seen AI and ML save lives in our own healthcare ecosystems. Today, I’m happy to say that when we started working with them, they were only working with one or two states. And today, more and more states are integrating this technology into their health ecosystem. I am confident that with all these transformative and future technologies, we will potentially be able to provide equitable care, more sustainable care, and of course, our health systems will become more resilient and more patient-centered.
Saini, highlighting the quality parameters involved in AI/ML functions of drug discovery, said, “The amount of data we have is much greater than what we have in the discovery space. The AI or ML model can only tell you based on the data you have. The gold standard that you will have to maintain, the best robustness of the product, the process with what you can do to obtain both the best yield and the best quality. This is also important in manufacturing processes and quality. The new use cases we’re seeing are being able to look at process quality metrics and critical quality process metrics.
Concluding the panel discussion, Dr. Sinha spoke about the regulations on AI generation and informed about the highly versatile and effective nature of AI/ML technologies.
