Nicholas Luksha

In-silico prediction of concentration-dependent viscosity curves for monoclonal antibody solutions

ABSTRACT Early stage developability assessments of monoclonal antibody (mAb) candidates can help reduce risks and costs associated with their product development. Forecasting viscosity of highly concentrated mAb solutions is an important aspect of such developability assessments. Reliable predictions of concentration-dependent viscosity behaviors for mAb solutions in platform formulations can help screen or optimize drug candidates for flexible manufacturing and drug delivery options. Here, we present a computational method to predict concentration-dependent viscosity curves for mAbs solely from their sequence—structural attributes. This method was developed using experimental data on 16 different mAbs whose concentration-dependent viscosity curves were experimentally obtained under standardized conditions. Each concentration-dependent viscosity curve was fitted with a straight line, via logarithmic manipulations, and the values for intercept and slope were obtained. Intercept, which relates to antibody diffusivity, was found to be nearly constant. In contrast, slope, the rate of increase in solution viscosity with solute concentration, varied significantly across different mAbs, demonstrating the importance of intermolecular interactions toward viscosity. Next, several molecular descriptors for electrostatic and hydrophobic properties of the 16 mAbs derived using their full-length homology models were examined for potential correlations with the slope. An equation consisting of hydrophobic surface area of full-length antibody and charges on VH, VL, and hinge regions was found to be capable of predicting the concentration-dependent viscosity curves of the antibody solutions. Availability of this computational tool may facilitate material-free high-throughput screening of antibody candidates during early stages of drug discovery and development.

Rational optimization of a monoclonal antibody for simultaneous improvements in its solution properties and biological activity

Developability considerations should be integrated with lead engineering of antibody drug candidates in interest of their cost effective translations into medicines. To explore feasibility of this imperative, we have performed rational mutagenesis studies on a monoclonal antibody (MAB1) whose development was discontinued owing to manufacturability hurdles. Seven computationally designed variants of MAB1 containing single point (V44K, E59S, E59T and E59Y) and double (V44KE59S, V44KE59T and V44KE59Y) mutations in its light chain were produced in Chinese Hamster Ovary (CHO) cells and purified by using platform processes employed during commercial scale production of monoclonal antibodies. MAB1 and its variants were formulated in the same platform buffer and subjected to a battery of experiments to assess their solution behaviors, and biological activities. Five of the seven (71%) variants of MAB1 demonstrated improved biophysical attributes in multiple experimental testings. Contrary to the commonly expressed reservations about potential biological activity loss upon developability optimizations, the improvements in solution behavior of MAB1 also increased its biological activity up to ~180%. In particular, concentrate-ability and apparent solubility of V44KE59S improved to ~150% and ~160%, respectively. Its diffusion interaction parameter (kD) reduced to 28% and viscosity at ~100 mg/ml decreased to less than half of the corresponding values for MAB1. V44KE59S is also slightly more active and its transfections in CHO cells were more productive. It also degraded slower than MAB1 in three month long 25°C and 40°C formulation stability studies. These results open doors to an exciting realm of structure-based biologic drug design where developability and biological activity can be simultaneously optimized at the molecular engineering stages.