Rejith P R, Correspondent, India Pharma Outlook
EY Parthenon published a report titled 'From Volume to Value: Indian Pharma's Transformation with Data and AI' in partnership with the Government of Telangana at the BioAsia 2024. The report stressed the potential of how Generative AI can redefine the drug discovery process, research and development (R&D) and how Indian pharmaceutical firms use AI technology to transform their R&D activities and improve operational efficiencies. According to EY, 28% of life science companies have integrated AI technology into their business operations, and 48% of firms are yet to implement this within one year.
Presently, the Indian pharmaceutical industry is witnessing mounting pressure to innovate and decrease the time to market for new drugs, so it is imperative to integrate AI and ML into pharmaceutical research and development. Let us look into how these technologies can benefit the pharmaceutical segment and propel.
The Pharma industry has transformed a lot after the arrival of cutting-edge technologies and has significantly benefitted Indian research and development activities. However, traditional methodologies in discovering drugs took ample time and a massive amount to introduce a new drug to the market. More importantly, with the utilization of artificial intelligence (AI) and machine learning (ML), these technologies can substantially reduce the timeline by forecasting how different compounds will react and find potential drug candidates more effectively. Machine learning plays a vital role in examining biological data to predict compounds' efficacy and safety, which can eventually lower the candidate count that needs to be checked in the lab. Moreover, technologies help Indian pharmaceutical firms address different challenges, promoting innovation and dynamism.
For instance, GlaxoSmithKline (GSK) streamlined its drug discovery process by collaborating with AI firm Exscientia. Their platform assists in developing and improving new molecules, lessening the time and cost involved in drug discovery.
Shripad Joshi, President, India & South Asia, Revvity says "Artificial intelligence-integrated drug discovery and development has the potential to accelerate the growth of the pharmaceutical sector and can drive a revolutionary change in the pharma industry"
Clinical trials are essential for pharmaceutical firms as they are imperative in deciding the efficacy and safety of potential drugs. Advanced Artificial intelligence and Machine learning technologies have the capability to enhance clinical trials in the research and development of Indian pharmaceutical firms by improving patient recruitment and trial design. The technologies can increase enrollment efficiency by inspecting genetic data and electronic health records and finding appropriate participants. Moreover, MI learning algorithms play a vital role in monitoring patient data in real-time, which can detect abnormalities and ensure protocol adherence. At the same time, AI assists in processing numerous data from clinical trials, taking out only the valuable data and contributing to enhanced decision-making. Hence, by harnessing AI and MI, Indian companies can perform more effective and precise trials, leading to quick drug approvals.
Novartis, the pharmaceutical giant, utilized AI technology to improve the progress of clinical trials through its SENSE platform. This platform examines data from several sources to offer real-time insights into future trials. It also helps find trends and issues well in advance, leading to decision-making.
Dheeraj Jain, Founder, Redcliffe Labs says "By analyzing vast datasets of patient records, medical imaging, and other clinical data, these technologies can identify patterns and risk factors associated with NCDs, enabling early detection and risk stratification"
The implementation of AI and MI can add value to the emerging field of personalized medicine by evaluating a huge number of datasets to find trends in patients and treatment responses. Both technologies have a significant impact on the development of customized therapies, considering environmental and genetic factors, which can, in turn, improve the efficacy of drugs and lower adverse effects. The role of AI is paramount as it advances clinical trials and drug discovery and even forecasts the progression of ailments. At the same time, ML's learning algorithms can find how patients respond to treatments, enabling personalized medication plans and dosages. Eventually, these approaches can help the pharmaceutical sector by improving patient care, lowering costs and resource allocation.
For example, Merck uses AI to personalize cancer immunotherapy; they have partnered with AI firm Tempus, which helped them inspect genetic and clinical data to identify biomarkers that forecast patients' responses to immunotherapy. With this, they develop customized treatment strategies that increase the efficacy of immunotherapy’s for individual patients.
Saji Mathew, Chief Operating Officer, Baby Memorial Hospital Ltd says "AI revolutionizes personalized medicine by leveraging machine learning to analyze vast genetic and clinical data, revealing hidden patterns and correlations"
In a nutshell, Both AI and ML technologies have created a benchmark in all the major sectors, including pharmaceutical, and are continuing their progress proactively. In the pharma domain, these technologies add value in accelerating drug discovery, improving clinical trials and personalizing medicine. However, several challenges may occur in these advanced technologies, which can be effectively handled by specialized talent and adequate funding, ultimately opening the way for an era of innovation in the Indian pharmaceutical landscape. By integrating AI and ML into Indian pharmaceutical companies, they can streamline their crucial processes and unleash their full potential, which will help them stay competent in the world market and contribute to advancing healthcare across the globe.
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