From Shortages to Solutions: Enhancing Drug Manufacturing Through Innovation

Commentary
Article

Technology and regulations can revolutionize drug manufacturing and ensure a stable supply of medications.

The pharmaceutical industry is facing an onslaught of drug shortages. Simply understanding the causes and consequences is not the goal. There is an urgent need to examine strategies, technologies, and regulations to help mitigate—and potentially eliminate—this issue.

Image credit: onizu3d - stock.adobe.com

Image credit: onizu3d - stock.adobe.com

Manufacturers need to consider cutting-edge technologies and explore proactive measures to counteract drug shortages. The pharmaceutical industry should strive for innovation that revolutionizes drug manufacturing and ensures a stable supply of essential medications for patients worldwide.

Emerging Technologies in Life Sciences Manufacturing

Scalability in medication production involves optimizing manufacturing processes while maintaining quality, consistency, and regulatory compliance. Process optimization, continuous manufacturing, supply chain management, robotic process automation (RPA), modular manufacturing, and lean manufacturing principles are common solutions; however, emerging technologies are well-suited to address scalability.

For example:

Digital twins: This proactive approach helps to reduce production disruptions that often contribute to drug shortages. A digital twin—a virtual representation of a real-world entity or process—provides real-time insights into manufacturing processes by continuously collecting and analyzing data from sensors and other sources. Manufacturers are able to understand process behavior, identify anomalies, and optimize operations, with deviations from optimal conditions able to be quickly detected and rectified.

A standout advantage of digital twin technology is predictive maintenance to ensure minimal downtime and continuous production. By closely monitoring the real-world equipment and assessing the digital twin’s performance, manufacturers can predict when maintenance is required and prevent breakdowns.

Using digital twins, manufacturers can test various operational parameters, process changes and configurations, scale strategies, and detect potential disruptions in a controlled virtual environment. This simulation-driven approach helps identify vulnerabilities in the manufacturing process and devise strategies to mitigate risks.

AI in supply chain management. AI is able to analyze historical sales patterns, real-time data, market trends, and external events to forecast demands more precisely and adapt to dynamic changes in the market. Other AI analytical capabilities in supply chain management include continuous monitoring of supplier data, transportation, and distribution channels. AI helps to identify potential disruptions or delays and enables manufacturers to take proactive measures to find alternative sources or routes and minimize the impact on the medication supply.

VR/AR in manufacturing: While not a direct solution, virtual and augmented reality (VR/AR) addresses drug shortages by contributing to improved efficiency, enhanced training, and streamlined processes. It provides immersive and interactive training environments that enable workers to practice complex procedures and operate equipment in a safe setting. VR/AR provides step-by-step guidance for real-world scenarios to guide operators when precision and attention to detail are of great consequence.

Regulators as Inhibitors and Enablers

Regulations help to ensure product quality and patient safety while maintaining ethical standards. However, stringent regulations and rigid enforcement by regulators may hinder innovation in the life sciences industry.

The complexity of regulatory requirements and the lengthy approval process can deter companies—particularly smaller ones with limited resources—from pursuing novel drug development or manufacturing approaches. Furthermore, the fear of regulatory scrutiny and potential delays could steer companies toward safer, more established paths that limit the exploration of groundbreaking technologies and methodologies to address issues such as drug shortages.

On the other hand, regulatory agencies play a significant role in encouraging innovation when they embrace adaptive regulatory pathways and accommodate emerging technologies. For instance, AI and advanced manufacturing techniques have the potential to streamline production processes, reduce the likelihood of shortages, and improve overall quality.

Regulatory agencies can seek input from technology experts to develop guidelines for compliance and innovation. Additionally, incentives such as priority review for innovative products may encourage manufacturers to invest in novel approaches that have the potential to alleviate shortages.

Dialogue on AI and Advanced Manufacturing

In March 2023, the FDA solicited feedback on artificial intelligence in drug manufacturing. The FDA’s willingness to engage in this dialogue demonstrates that regulations need to accommodate advancements and transformative change while ensuring patient safety and product quality.

There are many challenges to consider. For example, it’s important to explain AI algorithms used in critical manufacturing processes and AI-driven decisions, especially when patient care is at stake.

Additionally, determining accountability for cases in which AI-driven decisions result in adverse outcomes can be complex. Clear guidelines for liability and responsibility are necessary to ensure patient safety and consumer confidence.

AI algorithms can inherit biases contained in the training data, introduce ethical concerns, and result in biased decisions. For example, when determining inclusion or exclusion criteria for clinical trials, AI-based selection could perpetuate unequal representation in clinical trials if the biases reflect existing health disparities. This could lead to inadequate representation of certain demographic groups, potentially resulting in drugs and treatments that are less effective or safe for underrepresented populations.

The FDA's role in AI regulation is pivotal for successfully integrating AI technologies in the life sciences industry. Balancing innovation and safety, addressing ethical concerns, and collaborating with experts are essential. As AI continues to reshape health care, the FDA's guidance and oversight will help determine the benefits of AI-driven advancements while upholding ethical standards and patient safety.

Conclusion

Amid persistent drug shortages, the life sciences industry is poised for innovation, collaboration, and adaptive regulations. A path toward fortified drug manufacturing and supply stability may emerge with the synergy of drug manufacturers, emerging technologies, and regulatory bodies.

About the Author

Hovsep Kirikian is the vice president of strategy and operations, driving cross-division alignment and operational enablement across USDM. He has nearly 20 years of experience managing projects and programs in the life sciences industry, with a specific focus on the implementation and optimization of enterprise SaaS systems, strategic consulting for C-suite and executive leadership, and business & digital transformation in the life sciences industry.

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