When I go to a therapeutic protein meeting, it’s very hard for me to hear these products referred to as “drugs.” But since they are being regulated by CDER, it’s a little easier to swallow. However, calling viral gene vectors and cellular therapies “drugs” is a bridge too far. My advice to my good friends at CBER is to keep calling their products “biologics,” or they may lose all of their regulatory responsibilities to CDER…
Tag: <span>FDA</span>
As an industry, we need to do far more to implement technologies and work with FDA, not only to keep them informed, but to make sure they are aware of industry trends and newer technologies. Remember that CBER and
CDER have their own labs, and in many cases, they will want to bring in the technologies you want to use and see how they work in their own experiments…
“But why are they calling these products ‘drugs?’” I asked at the recent CMC Strategy meeting that CaSSS hosted in Gaithersburg. “Well it’s because they aren’t vaccines or blood products” said an old friend, who is an authority in the field. “But,” I said, “we’re really talking about therapeutic glyco-proteins produced by living organisms.” And just to make sure I was remembering things correctly, I searched Google and reviewed the definitions for a “biologic” and “biological” in several of the top technical references. Truly, a biologic or biological is a substance produced by a living organism, which would include glyco-proteins, non-glycosylated proteins, enzymes, viruses, and broken up proteins which could be used as poly-peptides or simple antigens…
The United States Food and Drug Administration (FDA) considers antibodies and recombinant proteins as “well-characterized products.” This is based on FDA’s comfort level with reviewing multiple products over an extended period of time. This designation relates to the product, not necessarily to the system that is used to manufacture the product nor to the facility where the product is manufactured. The initial guidance document was published in 1995, prior to the use of other systems and when the majority of products were still based on mouse hybridoma technology that was 20 years old…
Government policies affecting intellectual property rights and the review of food and health care products dramatically influence investments in research leading to the development and sale of products that serve unmet medical needs or provide consumers with safe sources of food and drug products at a low cost. When statutes that affect several regulatory agencies are revised within a short time period, institutions that rely on exclusive rights offered by those agencies in exchange for obligations of disclosure and compliance must alter their business plans to adjust to new rules leading to the benefit conferred by the government. In 2011, the Leahy-Smith America Invents Act (AIA) was passed, changing many aspects of the federal statutes relating to the United States Patent and Trademark Office (PTO), and in 2010, the Patient Protection and Affordable Care Act (PPACA) was passed, which included the Biologics Price Competition and Innovation Act (BPCIA), requiring the United States Food and Drug Administration (FDA) to establish an abbreviated regulatory approval pathway for complex macromolecules produced in living cells or organisms. This series of articles briefly reviews key aspects of the AIA and the BPCIA, plus recent court cases relating to complementary periods of exclusivity offered by the FDA and the PTO, which should be of great interest to academic and corporate institutions having an interest in the life sciences. Important aspects of the AIA will be discussed in the first article in this series…
Traditionally, the Six Sigma framework has underpinned quality improvement and assurance in biopharmaceutical manufacturing process management. This paper proposes a neural network (NN) approach to vaccine yield classification and compares it to an existing multiple linear regression approach. As part of the Six Sigma process, this paper shows how a data mining framework can be used to extract further value and insight from the data gathered during the manufacturing process, and how insights into yield classification can be used in the quality improvement process.
