Synopsis

• Bioinformatics tools to help us profile and understand the effect of multi-mutations in recombinant protein sequencing
• Codon usage tables of all species, human tissues and cancer primary cells to assist with various techniques, such as gene therapy or cancer vaccines
• Examples for future considerations

Synopsis

• Physical stability is a key determinant of the clinical and commercial success of biological therapeutics
• Experimental techniques for measuring the impact of amino acid residue mutation on the stability of proteins can be time-consuming and costly
• We demonstrate the success of a rigorous physics-based computational method, Free Energy Perturbation (FEP), at quantitatively evaluating the relative thermodynamic stability of a diverse set of proteins mutants

Synopsis

• Exploring rationale and initial successes
• Delving into lessons learned and hurdles to initial implementation, such as data format and quality

Synopsis

• Where are we with data capture, regarding availability and accessibility?
• Looking at the barriers to data sharing and collaboration
• Discussing how future developments could increase collaboration
• The emergence of approaches and efforts to minimize dataset size requirements

Synopsis

• Exploring paratope states in solution
• Determining antibody-antigen recognition – docking

Synopsis

• Affinity maturation often produces a panel of prospective lead candidates
• These candidates have a diverse range of drug-like properties
• Utilizing QSPR and machine Learning we are able to identify residues that drive an unwanted drug-like property
• In this talk, we validate this approach by mitigating off-target interactions of high-affinity binders

Synopsis

• Appreciating amyloid aggregation spans timescales from nanoseconds to decades
• Theory mechanisms and timescales associated with secondary structure formation, template search, and nucleation
• Using insights from theory, multi-scale simulations are used to target events at each timescale

Synopsis

This session will focus on how advanced single cell multi-omics technologies and translational informatics will play a critical role in cell therapy drug development.