Turbocharging Drug Manufacturing with AI: Speeding Up the Journey from Lab to Patient
AI-driven pharmaceutical production revolutionizes drug creation landscape
In the drug discovery landscape, companies navigate mountainous timelines and sky-high costs to obtain drug approvals. The odds of making it to market are dismal, with success rates hovering below 10% - as per a 2022 study. However, even minor advancements in time-to-lead optimization and clinical success probabilities have the potential to revolutionize the way we tackle the thousands of diseases currently without a known cure.
According to Anthony Costa, NVIDIA's director of digital biology, these improvements are crucial for the pharmaceutical industry. In an article for HealthTech, Costa emphasized that advancing time-to-lead and enhancing the chances of clinical success are vital for combating a multitude of diseases that currently remain treatment-less.
Artificial intelligence (AI) plays a pivotal role in drug production process control, with the ability to expedite time-to-market. AI applications extend across the entirety of the pharmaceutical sector, encompassing drug discovery and manufacturing - otherwise known as pharma AI.
Take Pfizer, for example, who leverages AI to detect anomalies and offer real-time suggestions to its operators. Their objective is to increase product yield by a substantial 10% while decreasing cycle time by 25%, as announced by Albert Bourla, Pfizer's Chairman and CEO, in the company's 2023 annual review. The pharmaceutical powerhouse introduced its generative AI platform in 2023, with Bourla himself claiming that AI-powered manufacturing processes have boosted throughput by a stunning 20%, making it possible to deliver medicines to patients quicker than ever.
Healthcare heavyweight Amazon Web Services (AWS) played an instrumental role in Pfizer's speedy development and distribution of the COVID-19 vaccine, aiding Pfizer in manufacturing the vaccine in just 269 days instead of the typical 8-10 years. It was Lidia Fonseca, Pfizer's chief digital and technology officer, who highlighted this development during the AWS Summit in Los Angeles on Nov. 22, 2024. Pfizer's mRNA prediction algorithm, powered by AI, delivered an impressive 20,000 more vaccine doses per batch. Moreover, Pfizer's internal generative AI platform, Vox, running on AWS cloud services, granted Pfizer access to large language models on Amazon Bedrock and SageMaker.
remarkable strides in AI development have also benefited industry giants like Moderna and Novartis. Moderna employed AI to expedite the development of its COVID-19 vaccine, while AWS enabled intelligent biopharmaceutical manufacturing and supply chain processes that incorporated AI, IoT, AI/ML, and data analytics services. AI algorithms also facilitated automation of quality control analyses, ultimately saving hours spent on manual review and streamlining production processes and logistics.
Similarly, Novartis utilizes machine learning (ML) to develop smart manufacturing processes, with Merck boasting a Manufacturing and Analytics Intelligence platform powered by AI on AWS.
The potential of AI in the pharmaceutical and life sciences sector is garnering attention, with the UCSF School of Pharmacy receiving funding as part of the Advanced Research Projects Agency for Health initiative. This project aims to expedite drug development using AI, with open-source data sets and models designed for biotech companies using the project's outputs. The UCSF School of Pharmacy intends to employ AI to map undesirable molecules and pathways, bypassing issues that surface later in the drug development process. Researchers are also using ML to predict how molecules interact with anti-targets, with the hope that improved accuracy will speed up drug discovery and lower costs.
AI has revolutionized drug discovery and manufacturing, fostering the development of new treatments and vaccines at faster pace, and pushing companies to deliver more medicines to patients sooner. Organizations must ensure they have the necessary data infrastructure to store, collect, and analyze the large data sets needed for AI, and implement a clear strategy for integrating AI into drug manufacturing workflows. Studies show that AI could lead to increased throughput, faster production times, lower costs, higher-quality products, reduced waste, and the acceleration of life-saving medications to patients.
Sources:1. Amazon Web Services (2024)2. Chodera, J. (2024)3. Deloitte Consulting LLP (2023)4. Gronowitz, E. (2023)5. McCann, T., & Monkhouse, A. (2023)
Data-and-cloud-computing technologies have been instrumental in facilitating AI advancements in the pharmaceutical industry. For instance, Amazon Web Services (AWS) played a substantial role in Pfizer's rapid development and distribution of the COVID-19 vaccine. Moreover, life sciences companies like Moderna and Novartis are leveraging AI and machine learning to expedite their processes and produce treatments more efficiently.
