Optimizing Monoclonal Antibodies for Biochemical Defense

Monoclonal antibodies (mAbs) are one of the fastest growing classes of therapeutics in medicine. Because they target specific pathogens, take effect quickly, and may be administered before exposure as a protective measure or after exposure as a treatment, mAbs are an ideal countermeasure against biological and chemical warfare agents. Unfortunately, many mAbs carry amino acid sequence motifs that trigger adverse immune responses in patients. Furthermore, mAbs are prone to premature elimination from the body through pinocytosis. The issues of immunogenicity and non-specific clearance by pinocytosis combine to negatively affect mAb pharmacokinetic behavior—the way the body absorbs, distributes, and gets rid of the drug.

Matthew P. DeLisa, Chemical and Biomolecular Engineering, is developing an integrated computational and experimental platform for controllably editing and masking specific amino acid sequences in a mAb. With the ability to camouflage specific sequences that are known or predicted to promote immunogenicity or pinocytosis, DeLisa’s team anticipates that they can significantly improve mAb pharmacokinetic properties.

This research will leverage fundamental principles of immune surveillance, regulation, and evasion for the purpose of generating pharmacokinetic-optimized mAb variants—with a particular focus on mAb candidates that neutralize the biological threat agents Burkholderia pseudomallei and Francisella tularensis. More broadly, basic science and biotechnological tools developed through this research will support future efforts to optimize the pharmacokinetic behavior of protein countermeasures that are critically important to biochemical defense.

Cornell Researchers

Funding Received

$2.25 Million spanning 5 years

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