FDA Grants Support Research in Modernizing Pharmaceutical Manufacturing

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FDA grants support US research in continuous manufacturing monitoring and control techniques for bio/pharmaceutical manufacturing at Rutgers, MIT, and Georgia Tech.

FDA awarded three grants, using its authority under the 21st Century Cures Act, to institutions of higher education and non-profit organizations to study and recommend improvements for the continuous manufacturing of drugs and biological products, as well as similar innovative monitoring and control techniques, the agency announced on Aug. 1, 2018. The grant awardees are:

  • Rutgers University (Piscataway, NJ), Industry 4.0 Implementation in Continuous Pharmaceutical Manufacturing-$2,004,790 

  • The Massachusetts Institute of Technology (Cambridge, MA), Smart Data Analytics for Risk Based Regulatory Science and Bioprocessing Decisions-$2,996,875 

  • Georgia Institute of Technology (Atlanta, GA), Continuous Synthesis, Crystallization, and Isolation (CSCI) of an API: Process Model-Controlled Enzymatic Synthesis of Beta-Lactam Antibiotics-$982,869.

“We know that novel manufacturing technologies for both small-molecule drugs and biological products have great potential to accelerate the development of new therapies and reduce the cost of critical medicines,” said FDA Commissioner Scott Gottlieb, in the press release. “Continuous manufacturing utilizes technologies that offer clear benefits for both patients and industry. The approach has the potential to shorten production times and improve the efficiency of manufacturing processes. These benefits translate to lower cost of production and thus the cost of medicine. It also allows for more nimble monitoring and control that can help reduce the likelihood of manufacturing failures, which in turn can reduce the risk of drug shortages. Moreover, it has the potential to create more modern, domestically-based manufacturing by making it more feasible to manufacture these products on American soil. We recognize that FDA has an important role to play in advancing these opportunities. The agency is uniquely stationed to support the development of this technology to help improve patient care and facilitate greater access.” 

Gottlieb noted that FDA is committed to helping reduce the cost and uncertainty of adopting new manufacturing platforms, and that the nearly $6 million in grants are one element in FDA’s approach to encourage wider adoption of these technologies. “FDA will continue to lead efforts to develop the standards, policy, and guidance needed to support the effective and efficient adoption of these new manufacturing platforms,” added Gottlieb.

According to Doug Hausner, associate director of the Center for Structured Organic Particulate Systems (C-SOPS) at Rutgers University: “The main goal of the Rutgers/Purdue program is to investigate and assess the role of process and product informatics and knowledge management in achieving smart manufacturing in continuous pharmaceutical processes. The infrastructure to be investigated will be comprised of real-time sensing, advanced control, and data and knowledge management. The infrastructure will be assessed and demonstrated for applicability and use in continuous process improvement and in supporting risk mitigation. We are extremely pleased to be able to continue to work with the FDA and support their development of a modern regulatory framework to support advanced pharmaceutical manufacturing.” 

An MIT team, led by Professor Richard Braatz (Department of Chemical Engineering), Professor Retsef Levi (Sloan School of Management), Professor Anthony Sinskey (Department of Biology), and Dr. Stacy Springs (Center for Biomedical Innovation) will study how advanced data analytics can be used to improve decision-making in biomanufacturing operations. Their first aim is to develop a framework for the risk-based assessment of bioprocess data analytical tools and process control strategies and their impact on product quality in batch and continuous manufacturing operations. A second aim is to use text analytics to incorporate plant-wide non-numeric data, such as operator notes, deviation reports, and inspection records into manufacturing models. This project will investigate how integration of plant-wide data into process analytical strategies can improve biomanufacturing operations and will further aid regulators in evaluating manufacturing processes. MIT’s third aim is to use advanced data analytics, including machine learning and artificial intelligence, to link diverse sets of publicly-available information about biological products, including clinical experience, to biomanufacturing operations. The goal of this overall approach is to allow manufacturers to use all of the product and process information available to them to increase process understanding and control and to aid regulators and biomanufacturers in understanding how manufacturing conditions ultimately impact patient health outcomes. Each of these aims offers opportunities for innovation in machine learning, artificial intelligence, and automation to improve regulatory science and biomanufacturing.

In the Georgia Tech project, researchers aim to enable beta-lactam API production in dedicated, compact, less capital-intensive plants. Cephalexin and amoxicillin (representative for cephalosporins and penicillins, respectively) are the target products. Project leaders note that, due to precautions regarding cross-contamination for both penicillins and cephalosporins, “redesign of beta-lactam manufacturing plants towards dedicated facilities will be pertinent and advantageous. Key features of our process include employment of an established biocatalyst, Pen G acylase; a recently developed improved kinetic model; and reactive crystallization to enhance selectivity and reduce cycle time. We propose to develop novel integrated reactors and separators as well as an overall process model to support process analytical technology and process control around a chosen operating point.”

Sources: FDA, Rutgers, MIT, Georgia Tech