Stephanie Gets the Whole Stability Profile of Therapeutic Molecules During Formulation Development with MFI
Delivering stable and safe disease therapeutics
MedImmune is the biologics Research and Development arm of AstraZeneca, which is focused on delivering therapeutics in the core areas of oncology, respiratory, inflammation and autoimmune, cardiovascular, and metabolic diseases. Stephanie Davies is a scientist in the Formulation Sciences group at the Cambridge UK site, which forms part of a larger global group based in Gaithersburg, MD.
The group formulates MedImmune’s pipeline molecules which include monoclonal antibodies, bi-specifics and fusion proteins, so the company can keep delivering world-class drugs to patients who need them.
Stephanie currently develops high-concentration liquid formulations that can be administered by patients at home to treat respiratory and autoimmune diseases. She looks at the impact solution conditions and container components have on molecule stability, and does this by monitoring how different conditions impact protein self-association, aggregation, fragmentation and/or chemical degradation. Understanding the conditions proteins are sensitive to helps Stephanie mitigate any potential stability issues in advance, ensuring product stability and safety.
On the lookout for the latest characterization technology
Analysis of sub-visible particles (SVP) in pharmaceutical preparations has typically been assessed using light obscuration (LO) methods like HIAC. Because it was vital to get the most comprehensive particle profile during formulation, the group always kept an eye out for the latest technologies. Once they learned about MFI®, they started using it as an orthogonal method for SVP characterization.
MFI differentiates more than standard techniques
The formulation group soon found there were lots of advantages to using MFI. They got quantitative data when looking at particles <10 μm, and for the first time could differentiate between air bubbles, contaminants including glass and silicon oil, and proteinaceous particles. MFI also detected translucent particles and let scientists analyze samples without prior dilution steps.
Stephanie recently had a project where standard assays didn’t give her definitive answers on whether one formulation was more stable than another, but MFI data clearly showed differences between SVP levels across the different formulations (Figure 1). This data helped her choose the most appropriate formulations to continue down through subsequent development stages.
Next step: On to automated analysis
The formulation group has had a manual MFI system for many years and find it’s a robust and really user-friendly system. They’re now in the process of evaluating the Bot1 Autosampler so they can move to an automated system. MFI is being used more and more at MedImmune — and not just in the Formulation Sciences group — it’s also being used by the Analytical and Quality groups too.
Some selected publications1. Evaluation of aggregate and silicone-oil counts in pre-filled siliconized syringes: An orthogonal study characterising the entire subvisible size range, M Shah, Z Rattray, K Day, S Uddin, R Curtis, CF van der Walle, and A Pluen, Int J Pharm, 2017; 519(1-2):58-66.
2. Characterisation of stress-induced aggregate size distributions and morphological changes of a bispecific antibody using orthogonal techniques, Z Hamrang, M Hussain, K Tingey, M Tracka, JR Casas- Finet, S Uddin, CF van der Walle, and A Pluen, J. Pharm. Sci., 2015; 104:2473–2481.
3. Gelation of a monoclonal antibody at the silicone oil–water interface and subsequent rupture of the interfacial gel results in aggregation and particle formation, SB Mehta, R Lewus, JS Bee, TW Randolph, and JF Carpenter, J. Pharm. Sci., 2015; 104:1282–1290.
4. Cross-linked silicone coating: A novel prefilled syringe technology that reduces subvisible particles and maintains compatibility with biologics, RA Depaz, T Chevolleau, S Jouffray, R Narwal, and MN Dimitrova, J. Pharm. Sci., 2014; 103:1384–1393.