岗位描述
Job Responsibilities
1) Lead cross-functional assessments for the introduction of new molecular modalities into GMP drug product (DP) facilities, ensuring regulatory compliance and alignment with site-specific quality and compliance requirements.
2) Lead or participate in drug product technology transfer, process validation, and other project-related activities for prefilled syringe (PFS) products.
3) Prepare DP-MSAT related technical documentation (e.g., gap analysis and risk assessments, TTP, PFD); review and analyze development and manufacturing data to ensure data integrity and support regulatory submissions and inspections.
4) Lead DP process investigations and provide technical expertise to support sterile drug product manufacturing; support project-related studies and ensure experimental records and data are maintained in compliance with company standards and GMP requirements.
5) Manage DP process materials, including technical evaluation, qualification, and lifecycle support of manufacturing materials and components.
6) Support digitalization projects through the development and deployment of digital tools and platforms to enhance project execution, process management, and collaboration across the DP network.
7) Engage in the client/ authority audit support as needed.
Qualification Education
Ph.D. degree in Pharmaceutical Engineering, Bio/chemical/process Engineering, Biotechnology, Toxicology, Biostatistics, Life science or related field. Graduates from 211/985 Project universities and those with oversea study experience are preferred.
Experience
1. 0-3 years of relevant experience in MSAT, process development or production; prior experience with PFS and/or combination product in a GMP facility is preferred. Experience in digitalization projects, programming, data analytics, or digital tool development is a plus.
2. Be familiar in GMP and other related regulations/guidance.
Skills
1. Good verbal and written communication skills in both English and Chinese.
2. Good experience and knowledge on data processing and statistical analysis is preferred.