Clearance prediction according to antibody property analysis
OwnerParisa MAZROOEI, Daniel Saldinger O'NEIL +1inventors
InventorsParisa MAZROOEI, Daniel Saldinger O'NEIL, Saroja RAMANUJAN
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Abstract
Disclosed are various embodiments for antibody clearance prediction using antibody sequence properties and machine learning techniques. In particular, an antibody clearance can be predicted using physicochemical features (e.g., structure, charge, moment, etc.) derived from biophysical molecular models and protein language model (pLM) embeddings derived from trained deep-learning protein language models (pLMs). A trained clearance prediction model predicts nonspecific clearance of a given antibody sequence according to the physicochemical features and the embeddings.
Claims20
A system, comprising:
- a computing device comprising a processor and a memory;
- and
- machine-readable instructions stored in the memory that, when executed by the processor, cause the computing device to at least:
- identify an antibody sequence;
- determine antibody properties associated with the antibody sequence based at least in part on an analysis of the antibody sequence, the antibody properties comprising at least one of:
- physicochemical features or feature embeddings;
- and
- determine a clearance prediction for the antibody sequence by applying the antibody properties as inputs to a trained clearance prediction model.
A method, comprising:
- identifying an antibody sequence;
- determining antibody properties associated with the antibody sequence based at least in part on an analysis of the antibody sequence, the antibody properties comprising at least one of:
- physicochemical features or feature embeddings;
- and
- determining a clearance prediction for the antibody sequence by applying the antibody properties as inputs to a trained clearance prediction model.
A non-transitory, computer-readable medium, comprising machine-readable instructions that, when executed by a processor of a computing device, cause the computing device to at least:
- identify an antibody sequence;
- determine antibody properties associated with the antibody sequence based at least in part on an analysis of the antibody sequence, the antibody properties comprising at least one of:
- physicochemical features or feature embeddings;
- and
- determine a clearance prediction for the antibody sequence by applying the antibody properties as inputs to a trained clearance prediction model.
Dependencies are inferred from the claim text.