Associate Principal Scientist, Mammalian Cell Line Engineering and Expression Optimization for ADCs and Bispecifics, with Focus on Non Natural Amino Acid Expression Systems

AstraZeneca • Gaithersburg, MD

2d

About The Position

Associate Principal Scientist As an Associate Principal Scientist in Oncology Bioscience, you will provide scientific and strategic leadership for mammalian cell line engineering and expression optimization to accelerate discovery of antibody–drug conjugates (ADCs) and bispecific antibodies. A central focus is advancing our in‑house non‑natural amino acid (nnAA) expression system, driving step-change improvements in productivity, stability, and product quality through host, vector, and process innovations. You will architect and integrate modern vector designs, site‑specific genomic integration, and process‑aware molecular engineering in CHO and HEK platforms, partnering closely with protein engineering, conjugation chemistry, analytics, and translational teams to deliver differentiated biologics for oncology. Accountabilities Scientific leadership and strategy: Define and execute the roadmap for cell line engineering and expression optimization for ADCs and bispecifics across CHO and HEK platforms, spanning stable pools and clonal lines, host adaptation, and process‑compatible expression. Platform ownership—nnAA expression: Own the evolution of our nnAA expression system, driving enhancements in vector architecture, genomic context, secretory pathway tuning, and process parameters to improve titer, consistency, and cell‑line stability; champion adoption across oncology programs. Vector and construct design: Design and refine expression constructs using advanced elements (e.g., UCOE, MARs/STARs, insulators, enhanced promoters, optimized signal peptides, introns) to strengthen transcriptional robustness, secretion efficiency, and product quality. Targeted genomic integration: Implement site‑specific integration and scalable stable expression using transposon systems (e.g., PiggyBac, Sleeping Beauty); evaluate and deploy landing‑pad/CRISPR approaches to reduce clone‑to-clone variability and enhance long-term stability. Expression optimization: Lead transient and stable optimization using media/feed screening, temperature and pH shifts, chemical chaperones/additives, and DoE‑driven experiments to improve titer, viability, and critical quality attributes (CQAs). Clonal selection strategies: Establish and harmonize clonal selection workflows (limiting dilution, FACS, imaging‑based screening) aligned with CQAs for bispecifics and ADC‑ready antibodies. Analytics partnership and workflows: Set robust protein quantitation and purification workflows (ELISA/Octet, HPLC/UPLC; affinity, IEX, SEC) and partner with analytics to profile aggregation, glycosylation, charge variants, and stability, feeding insights back into design. Cross‑functional influence: Collaborate with antibody engineering on bispecific format selection (e.g., knob‑in‑hole) and with chemistry on ADC conjugation readiness (site‑specific tags, engineered cysteines, glycan‑based strategies) to ensure expression suitability and DAR control. Automation and scale‑out: Deploy and scale automation and high-throughput screening (liquid handlers, plate readers, mini‑bioreactors) to accelerate construct/condition evaluation and enable data‑driven decisions. Data integrity and decision packages: Maintain meticulous records, ensure data integrity, and deliver concise decision packages on expression performance, stability, and CQAs to guide portfolio progression. People leadership and mentoring: Provide day‑to-day technical mentorship for junior scientists and contribute to capability‑building, best‑practice dissemination, and continuous improvement of platform and nnAA workflows. Focus on non‑natural expression system (impact and expectations) Translate the unique capabilities of our nnAA expression system into higher titers, improved product consistency, and reduced cell‑line attrition. Define platform KPIs (e.g., transient and stable titer targets, stability windows, clone passaging limits, CQAs for ADC readiness) and implement dashboards for routine monitoring. Establish comparability frameworks versus standard CHO/HEK to demonstrate value (e.g., productivity, glycan profiles, aggregation, charge variants) and guide adoption across oncology programs. Build and validate platform SOPs and training for broader deployment; partner with digital/data teams to capture parameters and model performance across campaigns. Why AstraZeneca? AstraZeneca offers an environment where your expertise has tangible impact. Our culture of curiosity, courage, and collaboration enables us to tackle complex challenges and deliver life‑changing medicines. Join us to shape the future of oncology biologics through innovation in expression systems and modality‑enabling platforms. At AstraZeneca, we seize opportunities to innovate and redefine what’s possible in biopharmaceuticals. Our mission to deliver transformative medicines is underpinned by a culture of collaboration, inclusivity, and ambition. Join us in a role where your work directly gives to breakthroughs in oncology, empowering patients and changing lives. Ready to take the next step in your career? Apply now and be part of something extraordinary!

Requirements

• PhD with 3+ years, or Master’s with 6+ years, or Bachelor’s with 8+ years of substantial, relevant industry experience in Cell Biology, Molecular Biology, Biochemistry, Bioengineering, or a related field.
• Proven expertise in mammalian cell line engineering and protein expression, with hands‑on experience in CHO and/or HEK systems.
• Track record of leading projects and mentoring scientists to milestones in a multidisciplinary R&D environment.
• Demonstrated ability to collaborate cross‑functionally with protein engineering, chemistry, analytics, and process development.

Nice To Haves

• Depth in molecular cloning and expression optimization: vector architecture, promoter/enhancer selection, codon and signal peptide optimization, intron/UCOE utilization.
• Experience building stable expression systems, including transposons, UCOE elements, and evaluation of CRISPR‑based landing pads; familiarity with engineering relevant to nnAA expression (e.g., orthogonal promoters, engineered tRNAs/aaRS, noncanonical secretion tags/trafficking signals).
• Proven track record in antibody expression and purification; familiarity with bispecific formats and ADC design principles (linker/payload strategies, site-specific conjugation readiness).
• Strong background in protein quantitation and purification (ELISA/Octet, spectrophotometry, HPLC/UPLC; affinity, IEX, SEC) with attention to aggregation, glycosylation, charge heterogeneity, and stability.
• Demonstrated experience optimizing and troubleshooting using DoE and statistical approaches; ability to interpret data from mini‑bioreactors and fed‑batch systems, including scalability assessments for novel expression modalities.
• Familiarity with automation and high‑throughput screening; experience with FACS‑based clone selection or imaging‑enabled screening is a plus.
• Willingness to engage with conjugation methods and chemistry to ensure expression products are suitable for ADC payload attachment and downstream characterization.
• Excellent organizational skills, rigorous record keeping, and compelling data presentation tailored to portfolio decision‑making.
• Ability to multitask and manage shifting priorities in a fast‑paced oncology research environment.

Responsibilities

• Define and execute the roadmap for cell line engineering and expression optimization for ADCs and bispecifics across CHO and HEK platforms, spanning stable pools and clonal lines, host adaptation, and process‑compatible expression.
• Own the evolution of our nnAA expression system, driving enhancements in vector architecture, genomic context, secretory pathway tuning, and process parameters to improve titer, consistency, and cell‑line stability; champion adoption across oncology programs.
• Design and refine expression constructs using advanced elements (e.g., UCOE, MARs/STARs, insulators, enhanced promoters, optimized signal peptides, introns) to strengthen transcriptional robustness, secretion efficiency, and product quality.
• Implement site‑specific integration and scalable stable expression using transposon systems (e.g., PiggyBac, Sleeping Beauty); evaluate and deploy landing‑pad/CRISPR approaches to reduce clone-to-clone variability and enhance long-term stability.
• Lead transient and stable optimization using media/feed screening, temperature and pH shifts, chemical chaperones/additives, and DoE‑driven experiments to improve titer, viability, and critical quality attributes (CQAs).
• Establish and harmonize clonal selection workflows (limiting dilution, FACS, imaging‑based screening) aligned with CQAs for bispecifics and ADC‑ready antibodies.
• Set robust protein quantitation and purification workflows (ELISA/Octet, HPLC/UPLC; affinity, IEX, SEC) and partner with analytics to profile aggregation, glycosylation, charge variants, and stability, feeding insights back into design.
• Collaborate with antibody engineering on bispecific format selection (e.g., knob‑in‑hole) and with chemistry on ADC conjugation readiness (site‑specific tags, engineered cysteines, glycan‑based strategies) to ensure expression suitability and DAR control.
• Deploy and scale automation and high-throughput screening (liquid handlers, plate readers, mini‑bioreactors) to accelerate construct/condition evaluation and enable data‑driven decisions.
• Maintain meticulous records, ensure data integrity, and deliver concise decision packages on expression performance, stability, and CQAs to guide portfolio progression.
• Provide day‑to-day technical mentorship for junior scientists and contribute to capability‑building, best‑practice dissemination, and continuous improvement of platform and nnAA workflows.
• Translate the unique capabilities of our nnAA expression system into higher titers, improved product consistency, and reduced cell‑line attrition.
• Define platform KPIs (e.g., transient and stable titer targets, stability windows, clone passaging limits, CQAs for ADC readiness) and implement dashboards for routine monitoring.
• Establish comparability frameworks versus standard CHO/HEK to demonstrate value (e.g., productivity, glycan profiles, aggregation, charge variants) and guide adoption across oncology programs.
• Build and validate platform SOPs and training for broader deployment; partner with digital/data teams to capture parameters and model performance across campaigns.

Benefits

• qualified retirement programs
• paid time off (i.e., vacation, holiday, and leaves)
• health, dental, and vision coverage in accordance with the terms of the applicable plans

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree