Protein research often requires the production and evaluation of many constructs or variants before the most promising candidates can be selected for further study. For each candidate, protein must be expressed, recovered or prepared for analysis, and assessed for relevant attributes such as yield, solubility, stability, and activity.
When these steps depend heavily on manual or sequential workflows, evaluating hundreds to thousands of candidates can become slow and resource-intensive on costs, turnaround time, or shared capacity for testing. Increasing throughput across protein production, recovery, analytical assessment, and sample preparation for downstream assessment, could allow more candidates to be evaluated in parallel while improving quality and reducing turnaround time.
Faster, more integrated workflows could enable screening of more candidates or reduce effort spent on lower-performing variants, enabling earlier identification of promising candidates and accelerating their progression into downstream studies and development.
We are looking for technologies, platforms, and workflows that increase the throughput and quality of protein production workflows, enabling larger numbers of constructs or protein candidates to be processed and relevant attributes to be compared efficiently. Solutions may address one or more steps, including rapid assessment of expression, soluble yield, aggregation, stability, or purity. Approaches do not need to provide a fully integrated end-to-end workflow, but should help reduce hands-on effort, turnaround time, or other practical limitations that constrain the number of candidates that can be evaluated in parallel.
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