Nisreen Chahid is undertaking a collaborative PhD project with Fujifilm Diosynth Biotechnologies, looking at Novel Strategies to Improve Yeast as an Expression Platform. For this case study, Nisreen shares her career aspirations and how Artificial Intelligence (AI) could lead us into exciting new directions.

Why did you decide to undertake this project?

I decided to undertake this project because of my strong interest in using our understanding of biology to make a tangible impact in the world. This project offers the invaluable opportunity to work at the interface of academia and industry and develop innovative approaches towards solving real-world problems in the manufacturing of biologics.

What are your ambitions for the future?

I aspire to continue working in precision fermentation, using microbial species as cellular factories to produce valuable proteins and other biomolecules. I am particularly interested in its applications in the food industry as it offers a more efficient, sustainable and cruelty-free alternative to the meat and dairy industries.  Reducing our reliance on animal agriculture is a key step in moving society towards becoming more ethical and environmentally conscious.

What excites you about your research? 

What excites me about my research is that it provides an opportunity to push the boundaries of knowledge by challenging assumptions that are prevalent in the literature. My work focuses on extrapolating findings from other eukaryotic systems all along the protein production pipeline to be applied in yeast production systems. By studying conserved mechanisms affecting the regulation of protein production at multiple stages, we are taking a whole-cell approach towards addressing our industry partner’s challenge of improving their yeast expression platforms.

Where/what do you think the next innovation in IB will be?

With recent advances in the world of artificial intelligence (AI), I think the next innovations in IB would involve utilising this technology to direct further advances in recombinant protein production processes. Within a matter of minutes, AI could evaluate and identify patterns in the ever-growing wealth of data we are producing and recommend optimal conditions for the production of a protein, including any combinations of strain, vector and protein engineering which might not have otherwise been explored before.

What is an interesting fact about you / what do you enjoy doing away from your studies?

I enjoy actively engaging in initiatives which strive for positive social change. From joining my department’s equality, diversity and inclusion committee to supporting the foundation of a charity supporting people of colour in my city, I enjoy representing and advocating for people in my community. Together with friends and colleagues, we find enjoyment in brainstorming new ways to reduce social barriers and make our positions more accessible for future generations. For example, we have recently begun developing a neurodivergent-friendly networking course, with the aim of increasing everyone’s chances of succeeding in professional spaces.