Evaluating the Use of Antibody Variable Region (Fv) Charge as a Risk Assessment Tool for Predicting Typical Cynomolgus Monkey Pharmacokinetics

Abstract

The pharmacokinetic (PK) behavior of monoclonal antibodies in cynomolgus monkeys (cynos) is generally translatable to that in humans. Unfortunately, about 39% of the antibodies evaluated for PKs in cynos have fast nonspecific (or non-targetmediated) clearance (in-house data). An empirical model relating variable region (Fv) charge and hydrophobicity to cyno nonspecific clearance was developed to gauge the risk an antibody would have for fast nonspecific clearance in the monkey. The purpose of this study was to evaluate the predictability of this empirical model on cyno nonspecific clearance with antibodies specifically engineered to have either high or low Fv charge. These amino acid changes were made in the Fv region of two test antibodies, humAb4D5-8 and anti-lymphotoxin ␣. The humAb4D5-8 has a typical nonspecific clearance in cynos, and by making it more positively charged, the antibody acquires fast nonspecific clearance, and making it less positively charged did not impact its clearance. Anti-lymphotoxin ␣ has fast nonspecific clearance in cynos, and making it more positively charged caused it to clear even faster, whereas making it less positively charged caused it to clear slower and within the typical range. These trends in clearance were also observed in two other preclinical species, mice and rats. The effect of modifying Fv charge on subcutaneous bioavailability was also examined, and in general bioavailability was inversely related to the direction of the Fv charge change. Thus, modifying Fv charge appears to impact antibody PKs, and the changes tended to correlate with those predicted by the empirical model.Hundreds of monoclonal antibody (mAb) therapeutics have been evaluated in clinical trials as potential life-saving therapeutics, yet only about 30 are approved for use in the United States and/or Europe, and they span therapeutic areas such as oncology, ophthalmology, viral infections, and autoimmune disease (1). These therapeutics fail for four main reasons, including lack of efficacy, safety, business, and others (2). As such, there is an effort to conduct appropriate preclinical studies to reduce the chances of failure as much as possible in the clinic. The focus of this paper is on efforts to lower the risk of fast antibody pharmacokinetics.Factors that affect antibody pharmacokinetics (PK) 2 include antibody-specific properties (charge, hydrophobicity, target affinity, FcRn affinity, Fc␥ receptor interactions, and glycosylation) (3), target properties (expression level, turnover rate, and soluble versus membrane-associated) (4, 5), drug administration (dose and route) (3, 6), anti-therapeutic antibody formation (6, 7), off-target/nonspecific binding (8 -12), and disease state (healthy volunteers versus patients) (13). Given the many factors that could affect the PK of therapeutic antibodies, finding a representative preclinical species in which to assess PK is imperative. An in-depth analysis of 23 monoclonal antibodies with linear PK and six with non-linear PK from three preclinical species...

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“…Impressively, the optimized antibody displayed high specificity and excellent pharmacokinetic properties without reductions in affinity. These and related findings [46–49] provide valuable insights for overcoming affinity/specificity trade-offs by engineering antibody CDRs and frameworks to achieve high specificity while maintaining high antibody affinity.…”

“…The fact that measurements of antibody specificity (non-specific binding and self-association) are the best biophysical descriptors of the likelihood of antibody success in the clinic [67] highlights the importance of developing computational and bioinformatics methods for predicting antibody specificity. Some of the key factors that determine antibody specificity are becoming clearer, including the numbers of charged, hydrophobic and hydrophilic residues in CDRs [26, 27, 39, 41, 42, 44, 68–70] as well as the net charge of the variable regions [46, 47, 49]. However, methods are needed to collectively describe these disparate findings and provide guidelines for identifying antibody variants with high specificity based only on their amino acid sequences or their combined sequences and structures.…”

Tutorial on Monoclonal Antibody Pharmacokinetics and Its Considerations in Early Development

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