DCT Case Studies

c1Fermentation and Cell Culture Process Development

CASE STUDY: DCT dramatically increases the yield of a commercial fungus by optimizing the fermentation process.

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    Objectives and Challenges: Our client was exploring new liquid fermentation processes of Armillariella tabescens, a type of fungus with great nutritional and medical value.  The objective was an increased yield rate, since the widely-used solid fermentation process had limitations on a small scale, including a long production period and low production rate.  These limit its larger scale applications.

    Solution and Results: Apply DCT to develop and optimize the liquid fermentation process.  In total, 8 experiments were designed and performed and the results analyzed.  The analysis allowed the client to reduce the number of parameters from 28 to 12. The dry cell yield rate was increased by 68%, from 2.36/100ml to 3.83g/100ml.


c2Process Development for Vaccine Production

CASE STUDY: DCT helps to increase production of typhoid Vi polysaccharide vaccine.

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    Objective and Challenges: Improve low production at 100Kg scale level.

    Solutions and Results:  Using DCT, only 7 experiments were required to develop and optimize a vaccine production process with 13 parameters at 100kg level,  increasing production by 300%, reducing the requirement for purification runs from 8 to 3,  cutting production costs by 37.5% and saving  the client $400K a year by excluding two expensive components.


c3Process Development for Enzyme Activity

CASE STUDY: DCT substantially increases the enzyme activity for Bacillus sp.

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    Objective and Challenges: To find an agent that can stabilize the fibrinolytic enzyme from bacillus for a client dealing with a brand new system.

    Solution and Results: DCT was applied to optimize 16 parameters including pH, temperature, and the concentrations of metal ions and some organic materials.  In all, 4 rounds were conducted during which a total of 10 experiments were carried out.  Eleven parameters were excluded and only 5 essential parameters selected in the system.  Enzyme activity was increased by 51%.


c5Process Development for Extraction

CASE STUDY: Extraction technology of Type II collagen significantly improved using DCT.

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    Objectives and Challenges: To improve the yield rate of Type II collagen, which was then at 4%, as well as raise the temperature of extraction, which at the time could only be conducted at 4° C.

    Solutions and Results: DCT was applied to optimize this complex system consisting of 14 factors. Only 7 experiments were needed. And the yield rate nearly doubled to 7.7%.  The temperature of extraction was increased to 20-25° C, making the process easier to carry out.


c6Process Development for Formulation

CASE STUDY: Technology of enteric-coated micro-sphere Daunorubicin.

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    Objective and Challenges: To improve encapsulation efficiency and drug loading capacity.

    Solutions and Results: To meet these two objectives, only 3 experiments were needed to optimize this 25-parameter system. After the DCT was applied, packaging efficiency increased from 26% to 95% and drug capacity from 72% to 95%.


c7Process Development for Bacterial Breeding

CASE STUDY: DCT leads to greatly improved bacterial breeding of lovastatin.

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    Objective and Challenges: In this case, the bacteria required very particular breeding conditions.  The client had exclusively adopted the orthogonal design test method for the optimization of the breeding condition, which necessitates tests dealing with many complicated and interrelated factors. In an attempt to address this complexity, the client had conducted numerous experiments, but their sheer complexity led to a great deal of difficulty in the interpretation of the results.  Despite all their efforts, the bacterial fermentation activity still remained at a low level of about 20 mg/ml.

    Solution and Results: The optimization of the system consisting of 15 parameters was realized with only 6 experiments.    The fermentation rate rose to 710 mg/ml, some 35 times greater than the results before DCT was applied.


* very complex systems may require more than 10 experiments