SBIR Phase II: Novel, Accurate and Reproducible Platform for the Developability Assessment of Protein Therapeutics
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will address ALL of the factors attributing to protein aggregation by determining the: size, identity, extent, mechanism of aggregation and stability, thus addressing Biopharma industry needs. This information is critical to the development of drug pipeline contributing to a $190 BN biologic's market where $87BN in first generation biologics face patent expiration before 2020. A successful technical approach for its implementation will provide essential information for decision making towards which candidates will enter the market, thus increasing the Biopharma valuation and ensuring supply of drugs to patients. In the end, improving the quality of life of patients with chronic diseases.The proposed project will address the need for a multivariate high-throughput technology to address the risk of protein aggregation, that when adopted in R&D, will increase pipeline approvals, reduce late stage withdrawals and total costs of drug development. Average R&D development costs for the mere 1% of candidates reaching FDA approval have risen to $2.6 BN per product. Protein therapeutic development needs to be guided by a full understanding of protein stability and aggregation. Research objectives are to: develop our innovative First-in-Class high throughput platform for screening protein therapeutics; develop original software capable of deciphering protein aggregation mechanism, size, identity and extent of aggregated protein and product stability; commercialize the innovative technology platform. Fully automated evaluation of protein candidates during early R&D phase will be conducted. Best-in-class image acquisition technology will be employed towards this end, using a label free chemical mapping technology, dedicated software using auto recognition algorithms, and correlations to decipher protein aggregation. We through the use of its breakthrough technology will determine: the aggregate free candidate under various stressor conditions, optimum formulation conditions for the protein therapeutic, the most stable candidate, and electronic data reporting that establishes accuracy, reproducibility, critical quality attributes of the protein product. less The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will address ALL of the factors attributing to protein aggregation by determining the: size, identity, extent, mechanism of aggregation and stability, thus addressing Biopharma industry needs. This information is critical to the development of drug pipeline contributing to a $190 BN biologic's market where $87BN in first generation biologics face patent expiration before 2020. A successful technical approach for its ... more
Title: Post-doctorate opportunity to aid in the development of a Best-in-Class HT-DCA platform for the screening and selection of therapeutic protein candidates.
Proteins are complex macromolecules that often encounter aggregation. The current available technology does not address this problem in all of its dimensions. We have developed a method and are currently developing a Best-in-Class High Throughput-Developability and Comparability Assessment (HT-DCA) platform for the screening of protein therapeutics. The need for such a technology is based on the needs of the patients and the Biopharma industry to address the concern of protein aggregation which may be related to immunogenicity and antibody-drug-antibody response. We have performed comparative analysis of several proteins and mAbs under varying formulation conditions using Quantum Cascade Laser (QCL) microscope, DOE statistical analysis, 2D IR correlation and Co-distribution spectroscopies. Further details of our company are at http://www.pdsbio.com.
Protein Dynamic Solutions, LLC. is currently recruiting a post-doctoral fellow into position funded by the NSF SBIR Post-doctoral diversity fellowship program.
Applicants must possess a Ph.D. degree in biophysics, biochemistry, bioinformatics, chemistry or computational engineering. Expertise in applying various techniques to understand protein stability and protein aggregation and molecular biophysical characterization. Specifically, knowledge of CD, vibrational spectroscopy and thermodynamics of proteins. The candidate must have lean-six-sigma training and have a strong programming background. The candidate will perform image analysis of proteins under varying formulation conditions and step-wise DOE statistical analysis for the evaluation of spectral results obtained. Expertise in big data and analytics to establish correlations are required. Also desired is experience in upstream (bioprocess) and downstream processing such as protein isolation, purification and characterization would be advantageous.
Minorities and women are strongly encouraged to apply. US citizen or permanent residency required.
Please submit your application profile.
