Send us two tubes, each with a frozen pellet of ~500,000 hybridoma cells. We'll prepare mRNA and make cDNA corresponding to the heavy and light chain by RACE. We clone and sequence independent clones to get you the sequence of the variable region, native secretion signal and the antibody isotype subclass.
Whatever your discovery platform, we can take the sequence of the variable regions and turn them into real molecules. Variable regions can be combined with the original constant regions, or with new constant regions to generate humanized or isotype-switched antibodies. We apply our GeneGPS® and VectorGPS® design platforms to optimize expression and balance chain ratios, thereby maximizing yield of your functional antibody.
ATUM has a range of analytical services to characterize the identity, affinity, purity, quantity and quality of your antibody. We can design the full analytical package appropriate for your molecule and subsequent applications including IND filing and GLP toxicology studies.
ATUM has extensive in-house capabilities including bio-layer interferometry for titer and affinity measurements using a pair of ForteBio Octets, aggregation detection by size exclusion chromatography, melting temperature and antibody stability measured using qPCR machines, glycan analysis by HPLC, and molecular mass determination using mass spectroscopy.
ATUM's HuAbGPS design tool begins by grafting heavy and light chain CDRs onto human germline frameworks (step 1 below). We then identify amino acid differences between the original (murine) framework and the new human framework. To find the murine framework amino acids essential for proper presentation of the CDRs within the human framework context, we create a DoE matrix where murine framework amino acids are systematically tested in different combinations. The result is a functional antibody containing the minimal number of murine framework amino acids whose heavy and light chain sequences are closer to human than to any other species.
ATUM's AntibodyGPS® design platform enables the simultaneous optimization of different critical antibody attributes including affinity, aggregation, stability and expression.
First, potential amino acid changes within the CDRs are ranked based on evolutionary conservation and physico-chemical properties. Up to 96 variant antibodies are then designed to incorporate the most highly ranked substitutions so that each substitution is represented in multiple variants.
The antibody variants are then expressed, and their properties are measured. Machine learning is used to analyze the data and determine the effect of each amino acid substitution on each of the measured properties as well as quantifying the epistatic effect on each residue. The graph below shows the effect of 72 different changes in the affinity, thermostability and expression level (titer). Very few changes have a positive effect on all three desirable antibody attributes, which is a severe limitation in traditional library screening approaches. Because ATUM's GPS technology allows us to identify changes that separately improve affinity, titer and thermostability, we are able to combine amino acid substitutions to produce an antibody that is improved for all three, as shown in the graph below.