Pharmacokinetics Of Drug Candidates Research Articles

Structural and Functional Analysis of CEX Fractions Collected from a Novel Avastin® Biosimilar Candidate and Its Innovator: A Comparative Study.

Avastin® is a humanized recombinant monoclonal antibody used to treat cancer by targeting VEGF-A to inhibit angiogenesis. SIMAB054, an Avastin® biosimilar candidate developed in this study, showed a different charge variant profile than its innovator. Thus, it is fractionated into acidic, main, and basic isoforms and collected physically by Cation Exchange Chromatography (CEX) for a comprehensive structural and functional analysis. The innovator product, fractionated into the same species and collected by the same method, is used as a reference for comparative analysis. Ultra-Performance Liquid Chromatography (UPLC) ESI-QToF was used to analyze the modifications leading to charge heterogeneities at intact protein and peptide levels. The C-terminal lysine clipping and glycosylation profiles of the samples were monitored by intact mAb analysis. The post-translational modifications, including oxidation, deamidation, and N-terminal pyroglutamic acid formation, were determined by peptide mapping analysis in the selected signal peptides. The relative binding affinities of the fractionated charge isoforms against the antigen, VEGF-A, and the neonatal receptor, FcRn, were revealed by Surface Plasmon Resonance (SPR) studies. The results show that all CEX fractions from the innovator product and the SIMAB054 shared the same structural variants, albeit in different ratios. Common glycoforms and post-translational modifications were the same, but at different percentages for some samples. The dissimilarities were mostly originating from the presence of extra C-term Lysin residues, which are prone to enzymatic degradation in the body, and thus they were previously assessed as clinically irrelevant. Another critical finding was the presence of different glyco proteoforms in different charge species, such as increased galactosylation in the acidic and afucosylation in the basic species. SPR characterization of the isolated charge variants further confirmed that basic species found in the CEX analyses of the biosimilar candidate were also present in the innovator product, although at lower amounts. The charge variants’ in vitro antigen- and neonatal receptor-binding activities varied amongst the samples, which could be further investigated in vivo with a larger sample set to reveal the impact on the pharmacokinetics of drug candidates. Minor structural differences may explain antigen-binding differences in the isolated charge variants, which is a key parameter in a comparability exercise. Consequently, such a biosimilar candidate may not comply with high regulatory standards unless the binding differences observed are justified and demonstrated not to have any clinical impact.

Comparison between lab variability and in silico prediction errors for the unbound fraction of drugs in human plasma

Variability of the unbound fraction in plasma (fu) between labs, methods and conditions is known to exist. Variability and uncertainty of this parameter influence predictions of the overall pharmacokinetics of drug candidates and might jeopardise safety in early clinical trials. Objectives of this study were to evaluate the variability of human in vitro fu-estimates between labs for a range of different drugs, and to develop and validate an in silico fu-prediction method and compare the results to the lab variability. A new in silico method with prediction accuracy (Q2) of 0.69 for log fu was developed. The median and maximum prediction errors were 1.9- and 92-fold, respectively. Corresponding estimates for lab variability (ratio between max and min fu for each compound) were 2.0- and 185-fold, respectively. Greater than 10-fold lab variability was found for 14 of 117 selected compounds. Comparisons demonstrate that in silico predictions were about as reliable as lab estimates when these have been generated during different conditions. Results propose that the new validated in silico prediction method is valuable not only for predictions at the drug design stage, but also for reducing uncertainties of fu-estimations and improving safety of drug candidates entering the clinical phase.