AI, Regulation and Compliance Challenges In Life Sciences

by PQE Group and Genaiz

Although Artificial Intelligence (AI) has exploded in popularity in the last couple of years with more applications traversing sectors, concerns about pre-existing biases, ethical issues, and lack of transparency—particularly when working with Artificial and Machine Learning (AI/ML)—have impeded its full adoption in heavily regulated industries like pharmaceuticals due to the stringent regulatory requirements that demand thorough validation, reproducibility, and transparent documentation.

Although regulatory bodies like the FDA and EMA have been observant of the radical growth and adoption of AI technologies by the life sciences industry, a comprehensive regulatory framework specifically targeting AI and its industry-wide applications has yet to materialize. While the exact timeline for introducing such a framework remains unclear, there is no doubt that the new regulation will prioritize enhancing current AI standards, mitigating bias, ensuring explainability and reproducibility, and enhancing overall safety measures.  

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Regulatory Bodies’ Current Perspective on AI in Drug Development and Manufacturing 

Despite the potential challenges associated with industry-wide adoption of AI and Machine Learning in spheres such as drug development and manufacturing, regulatory bodies like the FDA have embraced the benefits that accompany the employment of such innovative technologies to advance the quality and safety of pharmaceutical products. To ensure the correct application of this revolutionary technology and safeguard its integration in the life sciences industry, the FDA’s Center for Drug Evaluation and Research (CDER), in collaboration with the Center for Biologics Evaluation and Research (CBER) and the Center for Devices and Radiological Health (CDRH), has published a paper to solicit feedback from key players and explore relevant considerations for the use of AI/ML in the development of drugs and biological products. While the paper itself should not be treated as a guideline or policy advocating for a specific course of action, it serves as a foundational discussion document that invites feedback and insights on three critical areas in the use of AI/ML in drug production, namely: human-led governance, accountability, and transparency; quality, reliability, and representativeness of data; and model development, performance, monitoring, and validation. 

AI and Advanced Manufacturing

Even before COVID-19 crippled the world’s critical supply chains, there were already calls within the pharmaceutical industry to switch to advanced manufacturing, a more robust manufacturing process that makes use of technology to enhance efficiency and improve the adaptability of production lines. With advanced manufacturing, pharmaceutical companies can leverage automation and machine learning to streamline operations and respond swiftly to changes in real-time, making the supply chain more resilient. According to the National Academies of Sciences, Engineering, and Medicine 2021 report on pharmaceutical manufacturing and technology, AI has the potential to assist in the monitoring and controlling of advanced manufacturing processes, ensuring minimal supply chain disruptions and enhanced overall efficiency. 

AI Companies in Life Sciences and the Race Towards Revolutionizing Healthcare

Although several AI-focused startups and businesses have sprung up in the last decade to serve the industry's needs, very few have been able to address most of the major issues faced by pharmaceutical companies in their day-to-day operations. Launched in 2016, Canada-based GenAIz has emerged as a strong contender, distinguishing itself by offering an all-in-one, AI-powered platform that helps pharmaceutical and health organizations overcome the hurdles of running a successful and compliant business. The life sciences industry is constantly evolving, in connection with the updated and new regulations being frequently introduced to improve product quality and protect consumers, AI platforms like GenAIz become fundamental. GenAIz closely monitors regulatory changes and guidelines in the industry for AI, helping to speed up decision-making and execution by offering quicker and better insights into business operations. This is achieved through digitizing existing data from previous quality, manufacturing, or laboratory activities, for instance, and then detecting anomalies and exceptions, generating the knowledge required to help management and teams drive businesses forward. 

GenAIz and PQE Group’s Mission 

PQE Group’s focus has always been on finding newer and better ways of doing this in one of the world’s most dynamic and delicate industries to help clients stay ahead and remain compliant as the industry evolves. GenAIz’s partnership with PQE Group is a clear testament to this commitment as we will be bringing innovation to the industry to increase collective well-being by helping our clients develop better solutions, quality products that save and improve the lives of millions of patients around the globe.  Moving forward through this unique partnership, we are continuing our pursuit of improving lives through technology by aiding researchers and manufacturers in the production of new drugs and medical devices for a better and healthier tomorrow.  

 

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