Research Project
8313598
DESCRIPTION (provided by applicant): Due to the complexity of proteins and their biological production, characterization of protein pharmaceuticals (biologics) poses much more demanding analytical challenges than do small-molecule drugs. Consequently, many disparate biochemical analytical techniques are needed to characterize biologics. Because of the rapidly increasing power of mass spectrometry (MS), many of the measurements to characterize therapeutic proteins are now handled by MS, and that trend can be expected to continue owing to the accuracy and precision provided by state-of-the-art instrumentation. However, biotech companies currently make do with a patchwork of inefficient or ineffective software and manual data analysis for peptide identification, amino-acid-substitution evaluation, glycosylation characterization, disulfide-bond evaluation, and so forth. Current data analysis significantly lags behind the information content inherent in the complex data sets produced. We propose commercial development of software, named Byologic, which will make major improvements in the characterization of biologics via a range of mass spectrometric assays. Protein Metrics Inc. is a spin-off of Palo Alto Research Center where a variety of algorithms have been developed in recent years to address these analytical challenges. The proposed Phase I feasibility study will allow us to perform controlled studies to determine if MS- based assays and our algorithms are robust enough to satisfy the exacting standards of the biotech industry. If so, we will then build robust and GMP-compliant Byologic in Phase II. Both generic (biosimilar) and innovator drug companies stand to gain from Byologic. Public health, and regulatory agencies like the FDA charged with protecting the public, stand to gain too because better characterization will improve quality control, safety, and increase the efficiency of drug development, leading to consumer and Government savings. PUBLIC HEALTH RELEVANCE: The proposed project will lead to commercial software for improved characterization of the detailed composition of therapeutic proteins. Better characterized protein drugs will lead to better quality assurance, enhanced public safety, more informed regulatory decisions, and lower overall costs.
