The propagation of the yeast Saccharomyces cerevisiae was optimized using a Taguchi parameter design (TPD) L9(3 4) to produce bioethanol from an amylaceous material. The response factor selected was the specific growth rate of the yeast as calculated from the slope of the linear portion of its growth curve (neperian log cell concentration versus time). The reason is that the greater this rate, the higher the number of viable cells in the fermentation broth capable of ethanol production. The control factors selected were the initial amount of inoculum in the medium, the amount of glucose, the temperature, and the shaking speed which are the chemical and physical variables that most affect the growth behavior of this yeast. The noise factor selected was the initial peptone concentration in the medium. Statistical analysis and factorial split-plots indicate that the factor that most affected the response was the inoculum concentration (50.79% contribution), followed by the glucose concentration (25.22%), and shaking speed (14.79%). The contribution of temperature to the response variable was small (2.85%). This result was independent of the uncontrolled variation in the percentage of peptone in the sample…
Tag: <span>biopharmaceutical</span>
With the strong growth in biologics, large molecules, and biopharmaceutical therapeutics in recent years, the pharmaceutical and biotech industries are increasingly turning toward peptides and proteins in the search for drug discovery targets. While both possess numerous properties that offer significant therapeutic potential, there are fundamental differences between the two compounds. This article examines some similarities and differences between proteins and peptides in light of potential market applications, manufacturing techniques, and the regulatory environment…
Back on March 13, 2009, this discussion question was posted to the Biotech and Pharma Professionals Network on LinkedIn: “What can industry do to encourage middle and high school students to pursue careers in biotech and pharmacology?” The response to this question was overwhelming. As of this writing, there are 1,467 comments posted. I have not read all of them yet. However, as a teacher of science at the high school level, I have been impressed by how involved network members have been by offering constructive suggestions to the industry intended to help encourage young students…
The FDA’s ICH Q9 quality risk management (QRM) guidance material is the foundation for understanding and evaluating patient risks associated with developing and manufacturing pharmaceuticals. This three-part paper describes approaches a team of subject matter experts (SMEs) can use for implementing two important applications of QRM. Part I provides a method for identifying and remediating threat risks that may affect the product’s quality or other important aspects of a manufacturing enterprise’s lifecycle, from product research and development to commercial manufacturing. The second QRM application covered in Part II manages patient risks by identifying, evaluating, and managing risks associated with process parameters (PP) on the product’s critical quality attributes (CQAs). The final paper, Part III, describes an approach for accepting or further mitigating the risks evaluated by the QRM exercise…