Job Details
PR Research Associate (LNP Platforms)
Cambridge MA
Position Overview
In this role, the individual will work closely with the Discovery, Technical Development, Manufacturing and Analytical groups to advance our early pipeline into development. The candidate will work on formulation and scale up of lipid nanoparticles (LNPs) targeting different organs and cell types. They will work as part of a team to develop drug products with the goal of bringing in vivo base editing to patients. An ideal candidate would have good understanding of drug product process development, fluid dynamics, and nanoparticle formulation. We are looking for an ambitious candidate who wants to grow within in the process and formulation development group. This candidate will help shape the LNP platform and would grow with the aspirations of the organization as we advance into later stages of development.
Primary Responsibilities
Design and execute experiments to enable a robust formulation and reproducible process for manufacture of clinical trial materials.
Support development of an automated process with active analytics and process feedback for lipid nanoparticle production across mixing geometries, scales, components, and payloads.
Provide support with tech transfer activities for manufacturing of drug product.
Design and execute experiments to evaluate and optimize stability of RNA and LNP.
Characterize formulations using assays such as DLS, fluorescence, pH , osmolarity, etc.
Communicate scientifically rigorous findings via verbal and written communications, and presentations both internally and externally.
Generate high quality documentation as per SOPs and in support of regulatory filings.
Qualifications
BS/MS degree in Bio /Chemical engineering, Pharmaceutical Sciences, Chemistry, Biology or related discipline
4-8 years of relevant experience.
Prior industry research experience especially in nucleic acids and nanoparticle drug delivery is preferred.
Familiarity with ultrafiltration and aseptic unit operations for sterile drug product manufacture
Intermediate/advanced knowledge of Design of Experiments (DoE) for nonclinical applications, multivariate statistics, Bayesian statistics, and mixed models is essential.
A successful candidate will have excellent computational, written, and verbal communication skills, strong organizational abilities, and an ability to work with a diverse group of scientists and engineers.
Passion for science and strong work ethic.