The mass spectra were deconvoluted using a research version PeakView (version number: 1.2.2.0) with a sliding window method (Figure ). This approach converts every 3 spectra within m/ztime domain to deconvoluted spectra in mass-time domain. This preserves chromatographic features such as retention time. The automated method treated all data in a consistent manner, eliminating the analyst bias in peak selection. This deconvolution method also eliminated the potential impact from neighboring main peak with high signal intensity on the smaller biotransformed peaks with lesser signal intensity. The mass-time information was then used to manually identify the biotransformed species structures. To quantify the relative abundance of the various biotransformed species, the mass-time chromatograms were analyzed with MultiQuant software using automatic peak integration (MQ4) at the theoretical mass with +/-50 ppm as the extraction range. Pre-spiked cytochrome C was used to monitor run performance. Extracted peak area of each species was normalized with injected ADC mass for comparison between timepoints. For relative quantification of biotransformation species (% species) at each timepoint, the percentage was calculated by dividing the sum peak area of a class of species that shared a common feature (e.g. all heavy chain species with G0F) by the sum peak area of all biotransformation species in that class, including parent species (e.g. all heavy chain species).