Next Gen MIC - concurrent selection for affinity and developability of evolved candidates

The aggregation of antibody-based therapeutics during manufacture can be problematic, jeopardising their successful development. Importantly, while our ability to rapidly generate effective mAb candidates allows platform manufacturing, our fundamental lack of understanding of the relationship between sequence and aggregation (in its broadest sense) is presenting a significant hurdle to the manufacture of more complex, synthetic modalities.

To address this unmet need, the team at Leeds, together with Astra Zeneca, have developed an in vivo bacterial aggregation screen (Ebo et al. Nature Commun, 2020) to efficiently re-design problematic candidate sequences. We have shown that our tripartite beta-lactamase assay (TPBLA) is able to (i) identify candidate scFvs (ii) improve aggregation prone sequences using directed evolution and (iii) identify the precise residues that lead to aggregation.

In this studentship we will increase the applicability of the TPBLA to biopharmaceutical development pipeline and fundamental research.
Aim 1: we will adapt the TPBLA to allow selection of aggregation resistant sequences while maintaining target binding affinity by using orthogonal screens of ampicillin resistance and fluorescence sorting.
Aim 2: the ability to probe the effects of sequence on target affinity and protein aggregation/stability opens the door to exploration of the relationship between specificity and avidity and stability/affinity trade-offs. To do this we will generate a large dataset by a deep mutational sequencing approach to the TPBLA whereby the "fitness" of each of thousands of individual variants is quantified.

The project builds on strong on-going collaborations between the academic supervisors and their industrial collaborators. The breadth of techniques involved and the excellent facilities and opportunities at Astra Zeneca provide a superb training environment for the student.