Optimized recovery of monoclonal antibodies from transgenic goat milk by microfiltration

The Predictive Aggregate Transport Model for microfiltration is used in combination with optimum fluid mechanics and electrostatics to maximize recovery of a heterologous immunoglobulin (IgG) from transgenic goat milk. The optimization algorithm involved varying pH (6.8-9), transmembrane pressure (2-4.5 psi), milk feed concentration (1-2X), membrane module type (linear vs. helical design), and axial velocity (Reynolds number: 830-1170). Operation in the pressure-dependent regime at low uniform transmembrane pressures (approximately 2 psi) using permeate circulation in co-flow, at the pI of the protein (9 in this case) was used to increase IgG recovery from less than 1% to over 95%. Sodium dodecyl sulfate polyacrylamide gel electrophoresis and attenuated total reflection Fourier transform infrared spectroscopy of the microfiltration permeate samples confirmed that all the fat globules and most of the casein micelles were retained in the MF membrane whereas a large amount of the target IgG was transported through the membrane. Transmembrane pressure and hence permeation flux was kept low (approximately 15 lmh) to maximize IgG membrane transport and thus recovery, due to a sparse deposit on the membrane which facilitated high solute transport. Next, an analytical method was used to optimize the diafiltration process using the aggregate transport model, experimental target protein sieving coefficients and permeation flux (Baruah and Belfort, 2003). The methodology reported here should be generalizable to the recovery of target proteins found in other complex suspensions of biological origin using the microfiltration process.