Drug discovery trends: From regulation to embracing AI
Nov 23, 2023
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This podcast explores the post-COVID industry landscape, legal challenges faced by Moderna and BioNTech SE, the use of AI in streamlining drug discovery, challenges in AI for drug discovery and data privacy laws, and the evolving relationship between biotech and AI companies in drug discovery.
The controversy around intellectual property (IP) protection in COVID-19 vaccines could have significant implications for the pharmaceutical industry.
Despite facing challenges such as limited access to clinical data and the unpredictability of biological systems, artificial intelligence (AI) shows promise in drug discovery and could benefit from better data access and collaborations.
Deep dives
The importance of protecting intellectual property in the pharmaceutical industry
The first article discussed the importance of intellectual property (IP) in the pharmaceutical industry, particularly in relation to COVID-19 vaccines. Moderna filed a patent infringement lawsuit against Pfizer and BioNTech, claiming that their vaccines infringed on Moderna's patents for messenger RNA (mRNA) technology. The article highlighted the controversy around IP protection in vaccines, which are seen as vital for public health. The World Trade Organization's TRIPS Agreement allows developing countries to authorize the use of patented materials for COVID-19 vaccines without the rights holders' consent. The outcome of these lawsuits could have far-reaching implications for the industry.
The potential of AI in revolutionizing drug discovery
The second article explored the application of artificial intelligence (AI) in pharmaceuticals, specifically in drug discovery. While AI has shown success in areas such as target validation and predicting compound properties, it still faces significant challenges. Limited access to clinical data and the unpredictability of biological systems hinder its full potential. However, AI's ability to analyze vast amounts of data and generate novel compound ideas, as well as its potential cost savings, make it an attractive tool. The article highlighted the growing investments in health tech and the need for better access to clinical data for AI-driven drug discovery.
The role of swarm learning in overcoming data privacy challenges
The article also discussed swarm learning as a potential solution to data privacy challenges in accessing private data sets for AI. Swarm learning is a decentralized machine learning approach that allows multiple data sets to be analyzed on the blockchain without changing ownership. It aims to protect data privacy while providing accurate results. Although swarm learning is still in the early stages, it has shown promise in medical imaging analysis without releasing data from hospitals. The article emphasized the need for better data access and collaborations between tech and pharma companies to further advance AI-driven drug discovery.
This is the latest episode of the free DDW narrated podcast, “Drug discovery trends: From regulation to embracing AI", which covers two articles written for Volume 23 – Issue 4, Fall 2022 of DDW. They are called: From the Editor: Law and order and How AI in pharma can live up to the hype.
In the first article, DDW Editor Reece Armstrong comments on the post-Covid industry landscape. In the second article, Ben Folwell, Principal Consultant at Citeline, maps out how AI, swarm learning and open access to clinical data could revolutionise drug discovery.
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